JP2014089057A - Tracking processing device and tracking processing method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a tracking processing device and a tracking processing method which are capable of more accurately estimating motion of a target and of displaying the estimation result of motion of the target in a stable mode, with less computational load.SOLUTION: A tracking processing device 3 includes a capture processing unit 15, a motion estimation unit 16, and a velocity vector smoothing processing unit 20. The motion estimation unit 16 performs first filter processing for computing an estimated velocity vector V1(n) of a tracking target on the basis of data at an observation position P1d(n) of the tracking target. The velocity vector smoothing processing unit 20 performs second filter processing on data specifying the estimated velocity vector V1(n) to compute an estimated velocity vector V2(n) for display. A first filter coefficient C1 for use in the first filter processing and a second filter coefficient C2 for use in the second filter processing are set independently of each other.

Description

  The present invention relates to a tracking processing device and a tracking processing method used for tracking a target.

  2. Description of the Related Art Tracking devices that perform target tracking processing (TT: Target Tracking) based on echo signals received by a radar antenna are known (see, for example, Patent Documents 1 to 6). The radar antenna is configured to transmit a pulse signal and then receive an echo signal from the target. Thereby, the observation data of the target can be obtained. The tracking device predicts the speed of the target, the traveling direction, and the like based on this observation data.

  Patent Documents 1 and 2 each disclose a configuration of a display device as a tracking device. The display device includes first motion estimation means, second motion estimation means, needle change gear shift detection means, and display control means.

  The first motion estimation means is configured to estimate the target course and speed from the target position information, and is configured to be excellent in smooth characteristics. The second motion estimation means is configured to estimate the target course and speed from the target position information, and is configured to have excellent response characteristics. The display control means is configured to change the display contents in accordance with a target needle change or gear shift. More specifically, when it is determined that the target is not changing or shifting, the display control means displays the target course and speed estimated by the first motion estimation means. On the other hand, when it is determined that the target has changed or changed speed, the display control means displays the target course and speed estimated by the second motion estimation means.

Japanese Utility Model Publication No. 5-14966 (Claim 1) Japanese Utility Model Laid-Open No. 5-14967 (Claim 1) JP-A-8-146128 JP-A-8-160120 JP-A-4-363688 JP-A-2005-274300

  Usually, observation data of a target includes noise or the like due to clutter. For this reason, an error occurs in the observation position of the target. In order to perform stable tracking processing in consideration of this error, the tracking device may perform tracking filter processing. As a filter used for this tracking filter process, Patent Documents 1 and 2 mention an α-β filter.

  In the tracking filter process, filter coefficients are used. The filter coefficient is different between a case where a filter process excellent in smoothing characteristics is realized and a case where a filter process excellent in response characteristics is realized. The smoothing characteristic refers to a characteristic that suppresses fluctuations in the tracking filter processing result with respect to changes in the observation position with time. Further, the response characteristic refers to a characteristic regarding a rapid change in the tracking filter processing result with respect to a change in observation position with time. In the tracking filter process, the smoothing characteristic and the response characteristic are in a trade-off relationship.

  Of the smoothing characteristics and the response characteristics, when priority is given to the smoothing characteristics, it is possible to satisfactorily estimate the state in which the target is performing a uniform linear motion by the tracking filter processing. However, when the target performs a needle changing movement, the needle changing movement cannot be quickly reflected in the tracking filter processing. For this reason, although the target has changed, the fact that the target is going straight is displayed on the display screen of the tracking device. On the other hand, when priority is given to the response characteristic of the smoothing characteristic and the response characteristic, the state in which the target is performing the needle changing movement can be quickly reflected in the tracking filter processing. However, in this case, the result of the tracking filter processing greatly fluctuates due to the needle changing movement of the target. For this reason, on the display screen, the motion estimation result of the target is displayed in an unstablely changing manner.

  As described above, in the filtering process, the higher the response characteristic, the quicker the target needle movement can be reflected in the tracking filter process. Therefore, in order to accurately estimate the motion of the target, it is preferable to increase the response characteristics to some extent. On the other hand, the higher the smoothness characteristic, the more the target motion estimation result can be displayed on the display screen in a more stable manner. Therefore, in order to display the motion estimation result of the target in a stable manner, it is preferable to increase the smoothing characteristic to some extent.

  For this reason, it is necessary to set a filter coefficient for determining the response characteristic and the smoothing characteristic in consideration of the balance between the response characteristic and the smoothing characteristic. That is, a certain degree of compromise is required for each of the response characteristics and the smooth characteristics.

  In the tracking devices described in Patent Documents 1 and 2, when the target is moving straight, the motion estimation result by the first motion estimation unit set with a high smoothing characteristic is displayed. On the other hand, when the target is moving in a changing direction, the result of motion estimation by the second motion estimation means having a high response characteristic is displayed. Thereby, in the tracking filter process, a process having excellent smoothing characteristics and a process having excellent response characteristics are properly used. However, in the tracking devices described in Patent Documents 1 and 2, it is necessary to simultaneously perform tracking filter processing with a high calculation load in each of the first motion estimation unit and the second motion estimation unit. For this reason, the calculation load of CPU becomes high.

  In view of the above circumstances, the present invention can estimate the movement of the target more accurately, can display the estimation result of the movement of the target in a stable manner, and is computationally intensive. An object of the present invention is to provide a tracking processing device and a tracking processing method that can be small.

  (1) In order to solve the above problems, a tracking processing apparatus according to an aspect of the present invention includes a capture processing unit, a motion estimation unit, and a display processing unit. The capture processing unit is configured to capture the position of a target selected as a tracking target. The motion estimation unit is configured to perform a first filter process for calculating an estimated velocity vector of the target, which is used for tracking the target, using data that identifies the captured position. ing. The display processing unit is configured to calculate a display estimated speed vector used for display on the display by performing a second filter process on the data specifying the estimated speed vector. The first filter coefficient used for the first filter process and the second filter coefficient used for the second filter process are set independently of each other.

(2) Preferably, the said acquisition process part is comprised so that it may be connected to the receiver for receiving the signal which specifies the said target. The motion estimation unit is configured not to change the first filter coefficient when there is no change in the relative position between the position of the receiving apparatus and the position of the target.

(3) More preferably, the said motion estimation part can change a said 1st filter coefficient according to the change of the relative position of the position of the said receiving device, and the said position of the said target.

(4) Preferably, the motion estimation unit is configured to calculate an estimated position where the target is estimated to arrive. The first filter coefficient is a value that determines a degree of associating data specifying the estimated position with data specifying the position captured by the capture processing unit.

(5) Preferably, a maneuver detecting unit for detecting the presence or absence of a change in the target is further provided. The display processing unit is configured to be able to change the second filter coefficient according to the presence or absence of the needle change. In addition, the changing needle in this case means that the direction of the target changes.

(6) More preferably, the second filter coefficient is calculated based on data specifying the display estimated speed vector calculated at a predetermined first time point, at the time point later than the first time point. It is a value that determines the degree of associating data specifying the velocity vector.

(7) More preferably, the display processing unit sets the second filter coefficient when the needle change is not detected to be smaller than the second filter coefficient when the needle change is detected.

(8) Preferably, the maneuver detecting unit determines whether or not the target has changed based on a relationship between the estimated velocity vector and the captured position.

(9) More preferably, the motion estimation unit calculates the estimated speed vector at a predetermined first time point. The maneuver detection unit calculates a predetermined vector connecting a start point of the estimated velocity vector and the position of the target at a time point later than the first time point, and the predetermined vector, The cross product with the estimated velocity vector is calculated. The calculation of the outer product by the maneuver detection unit is configured to be performed at a plurality of times. The maneuver detection unit determines that the target is moving straight when the sign of the calculation result of the outer product is different at a plurality of successive time points.

(10) More preferably, the maneuver detection unit determines that the target has changed when the sign of the calculation result of the outer product is the same at a plurality of successive time points.

(11) Preferably, the maneuver detection unit calculates a needle change accuracy of the target based on a sign of a calculation result of the outer product at a plurality of successive time points. The display processing unit sets the second filter coefficient in accordance with the needle changing accuracy.

(12) In order to solve the above-described problem, a tracking processing method according to an aspect of the present invention includes a capture processing step, a motion estimation step, and a display processing step. In the supplement processing step, the position of the target selected as the tracking target is captured. In the motion estimation step, a first filter process for calculating an estimated velocity vector of the target used for tracking the target is performed using the data specifying the captured position. In the display processing step, a display estimated speed vector used for display on the display is calculated by performing a second filter process on the data specifying the estimated speed vector. The first filter coefficient used for the first filter process and the second filter coefficient used for the second filter process are set independently of each other.

  According to the present invention, the movement of a target can be estimated more accurately, the estimation result of the movement of a target can be displayed in a stable manner, and the calculation load can be reduced. A processing device and a tracking processing method can be provided.

1 is a block diagram of a radar apparatus including a tracking processing apparatus according to an embodiment of the present invention. It is a typical top view for demonstrating the relationship between the own ship and a target object echo image. It is a typical top view which shows the target echo image detected by the echo detection part. It is a schematic diagram for demonstrating regarding the process in a tracking process part. It is a schematic diagram for demonstrating the process in a maneuver detection part. It is a flowchart for demonstrating an example of the flow of a process in a motion estimation part. It is a flowchart for demonstrating an example of the flow of a process in a maneuver detection part. It is a flowchart for demonstrating an example of the flow of a process in a velocity vector smoothing process part.

  Hereinafter, embodiments for carrying out the present invention will be described with reference to the drawings. The present invention can be widely applied as a tracking processing apparatus. In the following, the same or corresponding parts in the drawings are denoted by the same reference numerals, and description thereof will not be repeated.

  FIG. 1 is a block diagram of a radar apparatus 1 including a tracking processing apparatus 3 according to an embodiment of the present invention. The radar apparatus 1 according to the present embodiment is a marine radar provided in a vessel such as a fishing boat. Hereinafter, the ship provided with the radar device 1 is referred to as “own ship”. The radar apparatus 1 is mainly used for detecting a target such as another ship. The radar apparatus 1 is configured to identify a target selected as a tracking target from one or a plurality of targets as a tracking target, and then calculate an estimated velocity vector of the tracking target. Yes. The estimated speed vector is a vector indicating a traveling direction and a traveling speed estimated for the tracking target. It is a vector which shows the course of a tracking target, and navigation speed. The radar apparatus 1 is configured to calculate a display vector based on the estimated speed vector. In the present embodiment, the display vector is also referred to as a display estimated vector. The radar device 1 is configured to display the estimated speed vector for display on the screen as a motion estimation result of the tracking target.

  As shown in FIG. 1, the radar device 1 includes an antenna unit (receiving device) 2, a tracking processing device 3, and a display 4.

  The antenna unit 2 includes an antenna 5, a receiving unit 6, and an A / D conversion unit 7.

  The antenna 5 is a radar antenna capable of transmitting (radiating) a pulsed radio wave having strong directivity. The antenna 5 is configured to receive an echo signal (reflected wave) from a target. That is, the antenna 5 is configured to receive an echo signal that identifies a target. The radar apparatus 1 measures the time from when a pulsed radio wave is transmitted to when an echo signal is received. Thereby, the radar apparatus 1 can detect the distance r to the target. The antenna 5 is configured to be able to rotate 360 ° on a horizontal plane. The antenna 5 is configured to repeatedly transmit and receive radio waves while changing the transmission direction of pulsed radio waves (changing the antenna angle). With the above configuration, the radar apparatus 1 can detect a target on a plane around the ship over 360 °.

  In the following description, an operation from transmission of a pulsed radio wave to transmission of the next pulsed radio wave is referred to as “sweep”. The operation of rotating the antenna 360 ° while transmitting / receiving radio waves is called “scan”. In addition, each step in the flowchart described later is performed for each scan.

  In the following, a certain scan is referred to as an “n scan”, and a scan immediately before the n scan is referred to as an “n−1 scan”. Similarly, m scans before n scans are referred to as “nm scans”. Note that n and m are natural numbers. In the present embodiment, the (n−1) scan time point is an example of the “first time point” in the present invention, and the n scan time point is an example of the “time point after the first time point” in the present invention.

  The receiving unit 6 detects and amplifies the echo signal received by the antenna 5. The echo signal is a reflected wave at the target with respect to the transmission signal from the antenna 5 among the signals received by the antenna 5. The reception unit 6 outputs the amplified echo signal to the A / D conversion unit 7. The A / D converter 7 samples an analog echo signal and converts it into digital data (echo data) consisting of a plurality of bits. Here, the value of the echo data includes data for specifying the intensity (signal level) of the echo signal received by the antenna 5. The A / D conversion unit 7 outputs the echo data to the signal processing unit 11 of the tracking processing device 3.

  The tracking processing device 3 is configured to calculate an estimated velocity vector V1 (n) of the tracking target. The tracking processing device 3 is configured to calculate a display estimated speed vector V2 (n) based on the estimated speed vector V1 (n). The tracking processing device 3 is configured using hardware including a CPU, a RAM, a ROM (not shown), and the like. The tracking processing device 3 is configured using software including a tracking processing program stored in the ROM.

  The tracking processing program is a program for causing the tracking processing device 3 to execute the tracking processing method according to the present invention. The hardware and software are configured to operate in cooperation. Accordingly, the tracking processing device 3 can function as a signal processing unit 11, an echo detection unit 12, a tracking processing unit 13, a display vector data generation unit 14, and the like which will be described later.

  The tracking processing device 3 includes a signal processing unit 11, an echo detection unit 12, a tracking processing unit 13, and a display vector data generation unit 14.

  The signal processing unit 11 removes interference components included in the echo data and unnecessary waveform data by performing filter processing or the like. The signal processing unit 11 outputs the processed echo data to the echo detection unit 12.

  The echo detector 12 is configured to detect the target echo image and detect the coordinates of the tracking representative point in the target echo image. Specifically, the echo detector 12 is configured to receive the echo data sampled during one sweep in order from the head address. Therefore, the echo detector 12 can obtain the distance r to the position corresponding to the echo data based on the read address when the echo data is read from the signal processor 11. Further, the antenna 5 outputs data indicating which direction the antenna 5 is currently facing (antenna angle) (not shown). With the above configuration, when the echo detection unit 12 reads the echo data, the echo detection unit 12 can acquire the position corresponding to the echo data with polar coordinates of the distance r and the antenna angle θ.

  The echo detector 12 is configured to detect whether an echo source is present at a position corresponding to the echo data. The echo detector 12 determines, for example, the signal level at the position corresponding to the echo data, that is, the signal intensity. The echo detection unit 12 determines that a target is present at a position where the signal level is equal to or higher than a predetermined threshold level value. The echo detection unit 12 performs the above-described determination process every scan time.

  Next, the echo detector 12 detects a range of positions where the target is present. For example, the echo detection unit 12 detects a group of regions (a plurality of positions) where the target is present as a region where an echo image of the target is present. In this way, the echo detector 12 detects the target echo image based on the echo signal. The outline shape of the target echo image substantially matches the outline shape of the target. However, due to noise included in the echo data, the outline shape of the target echo image is slightly different from the outline shape of the target. Next, the echo detector 12 detects the tracking representative point P of the target echo image using the echo data. The tracking representative point P is a representative point used in the tracking process in the target echo image.

  FIG. 2 is a schematic plan view for explaining the relationship between the ship 100 and the target echo image 120. In FIG. 2, the target echo image 120 is illustrated as a rectangular image. As shown in FIGS. 1 and 2, in the polar coordinate system, a straight line distance from the ship position M1 is indicated as a distance r with respect to the ship position M1 as the position of the ship 100. Is shown as the antenna angle θ. When extracting the tracking representative point P of the target echo image 120, the echo detection unit 12 uses the partial image 110 of the ring-shaped portion with the ship position M1 as the center. The image 110 is an image of a region surrounded by the first straight line 111, the second straight line 112, the first arc 113, and the second arc 114.

  The first straight line 111 is a straight line passing through the point closest to the own ship position M1 in the rear edge 120a of the target echo image 120 and the own ship position M1. The second straight line 112 is a straight line passing through the point closest to the ship position M1 in the front edge 120b of the target echo image 120 and the ship position M1. The first arc 113 is an arc passing through the portion 120c closest to the ship position M1 in the target echo image 120, and the center of curvature of the circle is the ship position M1. The second arc 114 is an arc passing through the portion 120d farthest from the ship position M1 in the target echo image 120, and is concentric with the first arc 113. The first arc 113 and the second arc 114 extend between the first straight line 111 and the second straight line 112, respectively.

  The echo detector 12 is configured to detect the center point of the image 110 as the tracking representative point P of the target echo image 120. In this case, the tracking representative point P is located at the center between the first straight line 111 and the second straight line 112 in the antenna angle θ direction, and in the distance direction, the first arc 113 and the second arc 114 are located. Located in the middle between.

  When a plurality of targets are detected, the echo detection unit 12 performs the above process for each target. Thereby, a plurality of target echo images 120 are detected. An example of a plurality of target echo images 120 detected by the echo detector 10 is shown in FIG. FIG. 3 is a schematic plan view showing the target echo image 120 detected by the echo detection unit 12, and shows a state in which each target echo image 120 is viewed from above. FIG. 3 shows an XY coordinate system. In FIG. 3, the X-axis direction of the coordinates indicates the east-west direction, and the Y-axis direction indicates the north-south direction.

  In FIG. 3, as an example, four target echo images 120 (121, 122, 123, 124) at the time of n scanning are shown. The target echo images 121, 122, 123 are, for example, small ships. The target echo image 124 is, for example, a large ship. For example, the echo detection unit 12 includes, as the tracking representative point P, the tracking representative point P1d (n) of the target echo image 121, the tracking representative point P2d (n) of the target echo image 122, and the target echo image 123. The tracking representative point P3d (n) and the tracking representative point P4d (n) of the target echo image 124 are observed. Hereinafter, a case where the target specified by the target echo image 121 is the tracking target 200 will be described as an example. In addition, when the target echo images 121, 122, 123, and 124 are collectively described, they may be referred to as “target echo images 120”. The tracking representative point P1 of the target echo image 121 is also the tracking representative point of the tracking target 200.

  As shown in FIG. 1 and FIG. 3, the echo detection unit 12 outputs the coordinate data of the tracking representative point P to each of the target echo images 120 to the tracking processing unit 13. The tracking processing unit 13 is configured to calculate an estimated velocity vector V1 (n) of the tracking representative point P1 of the tracking target 200.

  The tracking processing unit 13 includes a capture processing unit 15 and a motion estimation unit 16.

  The capture processing unit 15 is configured to supplement the observation position P1d (n) of the tracking representative point P1 (n) of the tracking target 200. The acquisition processing unit 15 is connected to the antenna unit 2 via the echo detection unit 12 and the like. The capture processing unit 15 includes a selection unit 17 and an association unit 18.

  The sorting unit 17 is configured to perform an echo sorting process. Specifically, the selection unit 17 specifies a region where the tracking representative point P1d (n) is estimated to exist at the n-scan time point (latest scan time point).

  For the tracking target 200, the selection unit 17 performs data of the estimated velocity vector V1 (n-1) calculated by the motion estimation unit 16 at the time of (n-1) scan and data of the estimated position P1e (n-1). And refer to. Thereby, the selection unit 17 acquires the coordinate data of the estimated position P1e (n-1) where the tracking representative point P is estimated to exist at the n scan time point. The selection unit 17 sets a selection region S1 (n) with the estimated position P1e (n-1) as the center. This selection area S1 (n) is, for example, a circular area centered on the estimated position P1e (n-1). Usually there are multiple targets. Therefore, there is a possibility that a plurality of echo images exist in the selection area S1 (n). In the present embodiment, tracking representative points P1d (n) and P2d (n) exist in the selection region S1 (n). Even in this case, the tracking processing unit 13 needs to continue the tracking process. Therefore, the associating unit 18 is configured to perform associating processing.

  The associating unit 18 specifies the observation position P1d (n) of the tracking target 200 from the tracking representative points P of one or more target echo images existing in the selection area S1 (n). Specifically, the associating unit 18 refers to the coordinates of the estimated position P1e (n−1) of the tracking representative point P1 calculated by the motion estimating unit 16 at the (n−1) scan time. The estimated position P1e (n-1) is calculated by the motion estimation unit 16 at the time of (n-1) scanning. The estimated position P1e (n-1) is a position where the tracking representative point P1 is estimated to exist at the (n-1) scan time point. The associating unit 18 determines that the point present at the coordinate closest to the coordinate of the estimated position P1e (n-1) is the observation position P1d (n) of the tracking representative point P1. The associating unit 18 outputs data specifying the coordinates of the observation position P1d (n) to the motion estimating unit 16.

  The motion estimation unit 16 is configured to perform tracking filter processing (first filter processing). Examples of the tracking filter used for the tracking filter processing include an α-β filter and a Kalman filter. Explaining the tracking filter process, the motion estimation unit 16 refers to the coordinates of the observation position P1d (n) specified by the associating unit 18 and the result of the tracking filter process at the (n-1) scan time point. Accordingly, the motion estimation unit 16 calculates the smooth position P1s (n), the estimated position P1e (n), and the estimated speed vector V1 (smooth speed vector) (n) for the tracking representative point P1.

  The smooth position P1s (n) is used as a reference position for tracking filter processing at the n scan time point. Further, the estimated position P1e (n) indicates a position where the tracking representative point P1 of the tracking target 200 is estimated to have arrived at the (n + 1) scan time point. The estimated velocity vector V1 (n) indicates a vector obtained by estimating the velocity vector of the tracking representative point P1 at the n scan time point.

  FIG. 4 is a schematic diagram for explaining the processing in the tracking processing unit 13. FIG. 4 shows an XY coordinate system. In FIG. 4, the X-axis direction of the coordinates indicates the east-west direction, and the Y-axis direction indicates the north-south direction. Further, FIG. 4 shows a wake RT1 of the smooth position of the tracking representative point P1 of the tracking target 200.

  Referring to FIGS. 1 and 4, the motion estimation unit 16 calculates a predetermined first filter coefficient when calculating the smooth position P1s (n), the estimated position P1e (n), and the estimated velocity vector V1 (n). C1 is used. The first filter coefficient C1 indicates the degree of associating the data of the observation position P1d (n) observed at the n scan time with the data of the estimated position P1e (n-1) calculated at the (n-1) scan time. The value to be determined. The first filter coefficient C1 is also a value for determining the smooth position P1s (n) at the time of n scanning. The first filter coefficient C <b> 1 is also a coefficient that determines the degree of quickly reflecting the needle changing movement of the tracking target 200 in the tracking filter processing in the motion estimation unit 16. In this case, the change of needle means changing the heading of the tracking target 200. Examples of the turning motion include a right turning motion and a left turning motion. In the present embodiment, a plurality of types of first filter coefficients C1 are prepared and stored in a memory (not shown) of the tracking processing device 3.

  The processing of the motion estimator 16 will be described more specifically. The motion estimator 16 includes a smooth position P1s (n−1) and an estimated position P1e (n−) of the tracking representative point P1 at the (n−1) scan time. 1) and an estimated velocity vector V1 (n-1). Next, the motion estimation unit 16 calculates a smooth position P1s (n) at the n scan time point. The coordinates of the smooth position P1s (n) are located on a line segment LS1 connecting the estimated position P1e (n-1) and the observation position P1d (n) of the tracking representative point P1. When the first filter coefficient C1 is zero, the smooth position P1s (n) matches the estimated position P1e (n-1). Further, as the first filter coefficient C1 is smaller, the smooth position P1s (n) is set closer to the estimated position P1e (n-1). Further, as the first filter coefficient C1 is larger, the smooth position P1s (n) is set closer to the observation position P1d (n). When the first filter coefficient C1 is 1, the smooth position P1s (n) coincides with the observation position P1d (n). In this embodiment, 0 <C1 <1 is set. The first filter coefficient C1 is expressed as a coefficient vector corresponding to each of the coordinate in the X-axis direction, the coordinate in the Y-axis direction, the velocity in the X-axis direction, and the velocity in the Y-axis direction.

  According to the above configuration, the smaller the first filter coefficient C1, the closer the smooth position P1s (n) is to the estimated position P1e (n-1). For this reason, the degree of smoothing of the calculation result in the motion estimation unit 16 increases, and the amount of variation due to the observation error of the tracking target 200 decreases. However, the response when reflecting the needle changing movement of the tracking representative point P1 of the tracking target 200 in the calculation result of the motion estimation unit 16 becomes slower as the first filter coefficient C1 is smaller.

  On the other hand, as the first filter coefficient C1 is larger, the smooth position P1s (n) is closer to the observation position P1d (n). For this reason, the motion estimation unit 16 can reflect the needle change motion of the tracking representative point P1 of the tracking target 200 with high responsiveness in the tracking filter processing. For this reason, the tracking process part 13 can improve the tracking property to the tracking target 200 accompanied by a needle change movement, and can suppress detecting the tracking target 200 and another target by mistake as a result. . Therefore, the tracking processing unit 13 can reliably keep track of the tracking target 200. However, the larger the first filter coefficient C1, the greater the amount of fluctuation at each scan time for the estimated speed vector V1 (n). In the present embodiment, the motion estimation unit 16 places importance on the responsiveness, and sets the first filter coefficient C1 to a relatively large value. However, the motion estimation unit 16 is configured to be able to change the first filter coefficient C1. Details of the setting of the first filter coefficient C1 will be described later.

  The motion estimation unit 16 outputs data specifying the result of the tracking filter process to the selection unit 17. In the sorting unit 17, the data is used for sorting processing at the (n + 1) scan time point. In addition, the motion estimation unit 16 outputs data specifying the estimated velocity vector V1 (n) to the display vector data generation unit 14.

  The display vector data generation unit 14 is configured to generate data (information) to be displayed on the display 4. More specifically, the display vector data generation unit 14 calculates a display estimated speed vector V2 (n) related to the tracking target 200. The display vector data generating unit 14 outputs data (estimated speed vector data) for specifying the calculated display estimated speed vector V2 (n) to the display 4. The estimated display speed vector V2 (n) refers to a vector displayed on the display 4. The display estimated speed vector V2 (n) is not used for the tracking filter processing in the tracking processing unit 13.

  The display vector data generation unit 14 includes a maneuver detection unit 19 and a velocity vector smoothing unit (display processing unit) 20.

  FIG. 5 is a schematic diagram for explaining processing in the maneuver detection unit 19. FIG. 5 shows an XY coordinate system. In FIG. 5, the X-axis direction of coordinates indicates the east-west direction, and the Y-axis direction indicates the north-south direction.

  As shown in FIGS. 1 and 5, the maneuver detection unit 19 is configured to detect the presence / absence of a change in the tracking target 200. The maneuver detection unit 19 is connected to the motion estimation unit 16. The maneuver detection unit 19 reads the data of the smooth position P1s (n−1) of the tracking representative point P1 and the data of the estimated velocity vector V1 (n−1) from the motion estimation unit 16. Next, the maneuver detection unit 19 reads data of the observation position P1d (n) of the tracking representative point P at the n-scan time point from the motion estimation unit 16.

  Next, the maneuver detection unit 19 determines the relationship of the observation position P1d (n) with respect to the estimated velocity vector V1 (n−1). When the observation position P1d (n) is located on the right side with respect to the estimated velocity vector V1 (n−1), the maneuver detection unit 19 determines that the tracking representative point P1 has changed to the right. FIG. 5 shows a state in which the tracking representative point P1 changes to the right. On the other hand, when the observation position P1d (n) is located on the left side with respect to the estimated speed vector V1 (n−1), the maneuver detection unit 19 determines that the tracking representative point P1 has changed to the left. .

  In the estimated speed vector V1 (n−1) calculated by the motion estimation unit 16, a response delay to the actual motion of the tracking target 200 occurs. For this reason, by determining the position of the observation position P1d (n) with respect to the estimated speed vector V1 (n−1), the direction of change of the tracking target 200 can be determined. The determination of the direction of change of the needle can be realized by using outer product calculation. Details of the needle change determination of the tracking representative point P will be described later.

  In addition, the maneuver detection unit 19 is configured to set the needle changing accuracy Acc (n) according to the motion state of the tracking representative point P1. The needle changing accuracy Acc (n) is a variable for specifying the accuracy with which the tracking representative point P performs the needle changing motion. Details of setting the needle changing accuracy Acc (n) will be described later. The maneuver detection unit 19 outputs data specifying the needle changing accuracy Acc (n) to the speed vector smoothing processing unit 20.

  The speed vector smoothing processing unit 20 performs speed vector smoothing processing (second filter processing) on the data specifying the estimated speed vector V1 (n). Thereby, the speed vector smoothing processing unit 20 calculates the display estimated speed vector V2 (n) used for display on the display 4. The display estimated speed vector V2 (n) is a vector to be displayed on the display unit 4.

  The speed vector smoothing process in the speed vector smoothing processing unit 20 includes the display estimated speed vector V2 (n-1) calculated at the (n-1) scan time point and the estimated speed vector V1 ( n) is weighted using the second filter coefficient C2. In the present embodiment, the second filter coefficient C2 is a value that determines the degree of associating the data of the estimated speed vector V2 (n−1) with the data of the estimated speed vector V2 (n−1).

  The second filter coefficient C2 is configured to be set independently of the first filter coefficient C1. The speed vector smoothing processing unit 20 is configured to set the second filter coefficient C2 based on the needle changing accuracy Acc (n). That is, the velocity vector smoothing processing unit 20 is configured to be able to change the second filter coefficient C2 in accordance with the presence / absence of a change in the tracking target 200. Details of the processing flow for setting the second filter coefficient C2 will be described later.

  As a result of the speed vector smoothing unit 20 performing the above-described speed vector smoothing process, the display estimated speed vector V2 (n) at the n-scan time point is suppressed from excessive fluctuation due to a change with time.

  Specifically, the speed vector smoothing processing unit 20 performs digital filter processing. As a method for realizing a low-pass filter as a digital filter, cyclic digital filter processing can be mentioned. An example of the filter processing will be described. First, the velocity vector smoothing processing unit 20 multiplies the estimated velocity vector V1 (n) and the second filter coefficient C2 (first multiplication). Further, the speed vector smoothing processing unit 20 multiplies the display estimated speed vector V2 (n−1) and the coefficient (1-C2) related to the second filter coefficient C2 (second multiplication). Next, the velocity vector smoothing unit 20 adds the result of the first multiplication and the result of the second multiplication (third operation). The addition result is the display estimated speed vector V2 (n) at the n-scan time point.

  The range of the second filter coefficient C2 is 0 <C2 <1, and the sum of the filter coefficients C2 and (1-C2) is 1. In the present embodiment, the lower limit value C2min of the second filter coefficient C2 is set to 0.01. In the present embodiment, the upper limit value C2max of the second filter coefficient C2 is set to 0.95.

  As a result of the above processing performed by the velocity vector smoothing processing unit 20, as the second filter coefficient C2 is smaller, the display estimated velocity vector V2 (n) is equal to the estimated velocity vector V1 (n) calculated at the n scan time point. Not easily affected. For this reason, the display estimated speed vector V2 (n) increases in the degree of smoothing, and decreases with time. On the other hand, the responsiveness when reflecting the needle changing movement of the tracking representative point P1 of the tracking target 200 to the display estimated speed vector V2 (n) decreases as the second filter coefficient C2 decreases.

  On the other hand, as the second filter coefficient C2 is larger, the display estimated speed vector V2 (n) is a value that takes into account more of the needle changing motion of the estimated speed vector V1 (n). For this reason, the estimated display speed vector V2 (n) is a value that more accurately represents the motion state of the tracking target 200. However, in this case, the fluctuation amount for each scanning time is increased for the display estimated speed vector V2 (n) displayed on the display 4. In the present embodiment, as described above, the velocity vector smoothing processing unit 20 is configured to be able to change the second filter coefficient C2 in accordance with the needle changing accuracy Acc (n) determined by the maneuver detecting unit 19.

  Specifically, in this embodiment, when the straight movement of the tracking target 200 is detected by the maneuver detection unit 19, the velocity vector smoothing unit 20 sets the second filter coefficient C2 to a relatively small value close to zero. The value is set to C2min (second filter coefficient when going straight). On the other hand, when the maneuver detection unit 19 detects a change in movement of the tracking target 200, the velocity vector smoothing unit 20 sets the second filter coefficient C2 to a value larger than C2min. More detailed processing in the velocity vector smoothing processing unit 20 will be described later.

  The velocity vector smoothing processing unit 20 outputs the calculated display estimated velocity vector V2 (n) to the display 4.

  The display 4 is a liquid crystal display capable of color display, for example. The display 4 is configured to read data from the estimated speed vector data generation unit 14 and display an image specified by the data. Thus, an image indicating the target display estimated speed vector V2 (n) is displayed on the display 4 such as a liquid crystal display. The operator of the radar apparatus 1 can confirm the traveling direction and traveling speed of the tracking target 200 by confirming the radar image displayed on the display 4.

  Next, an example of the flow of processing in the tracking processing device 3 will be described. Specifically, (1) an example of the flow of processing in the motion estimation unit 16, (2) an example of the flow of processing in the maneuver detection unit 19, and (3) the processing in the velocity vector smoothing processing unit 20 An example of the flow will be described in order. The processes (1), (2), and (3) are performed at each scanning time point, and are repeatedly performed at a plurality of scanning time points.

  First, (1) an example of the flow of processing in the motion estimation unit 16 will be described. FIG. 6 is a flowchart for explaining an example of a processing flow in the motion estimation unit 16. The tracking processing device 3 reads and executes each step of the flowchart shown below from a memory (not shown). This program can be installed externally. The installed program is distributed in a state stored in a recording medium, for example.

  The following description will be made with reference to FIGS. 1 to 5 as appropriate in addition to FIG. First, the motion estimation unit 16 sets the first filter coefficient C1, and then performs a tracking filter process using the first filter coefficient C1 (step S101). The first filter coefficient C1 is read from the memory of the tracking processing device 3 based on the predicted position P1e (n) calculated at the n scan time point. The first filter coefficient C1 may be read from the memory of the tracking processing device 3 based on the predicted position P1e (n-1) calculated at the (n-1) scan time. Further, the first filter coefficient C1 may be a constant value.

  Next, the motion estimation unit 16 outputs data specifying the result of the tracking filter process to the selection unit 17 and the display estimated speed vector data generation unit 14 (step S102).

  Next, (2) an example of the flow of processing in the maneuver detection unit 19 will be described. FIG. 7 is a flowchart for explaining an example of a processing flow in the maneuver detection unit 19. First, the maneuver detection unit 19 reads out coordinate data specifying the smooth position P1s (n-1) and data specifying the estimated velocity vector V1 (n-1) from the motion estimation unit 16 (step S201). Next, the maneuver detection unit 19 reads data of the observation position P1d (n) of the tracking representative point P1 at the n scan time point from the motion estimation unit 16 (step S202).

  Next, the maneuver detection unit 19 determines the presence or absence of a change in the tracking target 200 based on the relationship between the estimated velocity vector V1 (n−1) and the observation position P1d (n). Specifically, the maneuver detection unit 19 performs outer product calculation (step S203). In this case, first, the maneuver detector 19 calculates a vector V3 (n). The starting point of the vector V3 (n) is the smooth position P1s (n-1) and the starting point of the estimated velocity vector V1 (n-1). The end point of the vector V3 (n) is the observation position P1d (n). Next, the maneuver detection unit 19 calculates the outer product of the vector V3 (n) and the estimated speed vector V1 (n-1).

  Next, the maneuver detection unit 19 determines the direction of change of the tracking representative point P (step S204). Specifically, the maneuver detection unit 19 determines whether the calculation result of the outer product is a positive value or a negative value. For example, when the calculation result of the outer product is a positive value (YES in step S204), the observation position P1d (n) of the tracking target 200 is located on the left side with respect to the estimated speed vector V1 (n−1). Will be. In this case, the maneuver detector 19 sets the variable ε = 1 (step S205).

  On the other hand, when the calculation result of the outer product is a negative value (NO in step S204), the observation position P1d (n) of the tracking target 200 is the estimated velocity vector V1 (n−1) as shown in FIG. It is located on the right side. In this case, the maneuver detector 19 sets the variable ε = −1 (step S206).

  As described above, an error occurs at the observation position P1d (n). As a result of the presence of this error and the like, even when the tracking target 200 is not moving in a changing direction, the observation position P1d (n) is unlikely to exist on the estimated velocity vector V1 (n-1). Therefore, when the calculation result of the outer product is zero, there is no problem even if it is not taken into consideration. However, when the result of the outer product calculation is zero, the maneuver detection unit 19 may set the variable ε to 1 or −1.

  Next, the maneuver detection unit 19 determines whether or not a change has occurred in the direction of change of needle (step S207). Specifically, the maneuver detection unit 19 compares the variable ε set in step S205 or step S206 at the (n−1) scan time with the variable ε set in step S205 or step S206 at the n scan time. .

  When the variable ε at the two consecutive scan times is the same (YES in step S207), that is, when the sign of the variable ε has not changed, the maneuver detection unit 19 has changed the tracking target 200, In addition, it is determined that there is no change in the direction of change of needle. In this case, the maneuver detection unit 19 sets the needle changing accuracy Acc (n) according to the needle changing state (step S208). The needle changing accuracy Acc (n) is a variable for specifying the accuracy with which the tracking representative point P1 is changing. In the present embodiment, the maneuver detection unit 19 sets a range of −1 ≦ Acc (n) ≦ 1.

  In this case, the maneuver detection unit 19 sets the needle changing accuracy Acc (n) so that the absolute value of the needle changing accuracy Acc (n) increases as the number of times determined that there is no change in the direction of changing the needle. In the present embodiment, the maneuver detection unit 19 calculates the needle changing accuracy Acc (n) using a recursive filter. This recursive filter weights and adds the needle changing accuracy Acc (n−1) calculated at the (n−1) scan time and the variable ε set at the n scan time using a predetermined coefficient γ. The coefficient γ is set independently for both the first filter coefficient C1 and the second filter coefficient C2.

  An example of the cyclic filter processing in the maneuver detection unit 19 will be described. First, the maneuver detection unit 19 calculates the needle change accuracy Acc (n−1) calculated at the time of (n−1) scan and the coefficient γ. Multiply (first multiplication). Further, the velocity vector smoothing unit 20 multiplies the variable ε set at the n-scan time point by the coefficient (1-γ) related to the coefficient γ (second multiplication). Next, the maneuver detection unit 19 adds the calculation result of the first multiplication and the calculation result of the second multiplication (third calculation). This addition result is the needle changing accuracy Acc (n) of the tracking target 200 at the time of n scanning.

  The range of the coefficient γ is (0 <γ <1), and the sum of the coefficients γ and (1−γ) is 1. When the absolute value of the calculation result of the needle changing accuracy Acc (n) exceeds 1, the maneuver detection unit 19 sets the absolute value to 1.

  Next, the maneuver detection unit 19 outputs data specifying the needle changing accuracy Acc (n) to the speed vector smoothing processing unit 20 (step S209).

  On the other hand, when the variable ε set at the (n−1) scan time and the variable ε set at the n scan time are different, that is, when the signs of ε are different (NO in step S207), The maneuver detection unit 19 determines that the tracking target 200 is moving straight at the n-scan time point. In this case, due to the observation error of the observation positions P1d (n−1) and P1d (n), the observation position P1d appears alternately on the left and right with respect to the corresponding estimated velocity vector V1.

  In this case (NO in step S207), the maneuver detection unit 19 sets the needle changing accuracy Acc (n) to zero (step S210). Next, the maneuver detection unit 19 outputs data specifying the needle changing accuracy Acc (n) to the speed vector smoothing processing unit 20 (step S209).

  Next, (3) an example of the flow of processing in the velocity vector smoothing processing unit 20 will be described. FIG. 8 is a flowchart for explaining an example of a processing flow in the velocity vector smoothing processing unit 20. First, the speed vector smoothing processing unit 20 reads out data specifying the needle changing accuracy Acc (n) and data specifying the estimated speed vector V1 (n) from the maneuver detection unit 19 (step S301).

  Next, the speed vector smoothing processing unit 20 sets the second filter coefficient C2 according to the needle changing accuracy Acc (n) (step S302). The second filter coefficient C2 is set to increase as the absolute value of the needle changing accuracy Acc (n) increases. More specifically, when the needle changing accuracy Acc (n) ≠ zero, the speed vector smoothing processing unit 20 sets the second filter coefficient C2 to the same value as the absolute value of the needle changing accuracy Acc (n). (Step S302). However, when the needle changing accuracy Acc (n) exceeds the second filter coefficient C2max, the speed vector smoothing processing unit 20 sets the second filter coefficient C2 = C2max. On the other hand, when the needle changing accuracy Acc (n) = zero, the speed vector smoothing processing unit 20 sets the second filter coefficient C2 to the lowest value C2min of the second filter coefficient C2 (step S302).

  Next, the speed vector smoothing processing unit 20 calculates a display estimated speed vector V2 (n) by performing a speed vector smoothing process (step S303). That is, the speed vector smoothing processing unit 20 includes the second filter coefficient C2 set at the n-scan time point, the coefficient (1-C2) related to the second filter coefficient C2, and the data of the estimated speed vector V1 (n). Using the display estimated speed vector V2 (n-1) data, the speed vector smoothing process is performed. Thereby, the display estimated speed vector V2 (n) is calculated (step S303).

  The speed vector smoothing processing unit 20 outputs data specifying the display estimated speed vector V2 (n) to the display 4 (step S304). As a result, the display estimated speed vector V2 (n) of the tracking target 200 is displayed on the display 4.

  As described above, according to the tracking processing device 3, the first filter coefficient C1 used for calculating the estimated speed vector V1 (n) and the second filter coefficient used for calculating the display estimated speed vector V2 (n). C2 is set independently of each other. Thereby, the estimated speed vector V1 (n) can be calculated more accurately in a mode in which the responsiveness to the movement of the tracking target 200 is high. Further, the display 4 can suppress the display estimated speed vector V2 (n) from being displayed in an unstable manner. Thus, even if the conditions required for calculating the estimated speed vector V1 (n) and the conditions required for calculating the estimated display speed vector V2 (n) are contradictory, both conditions must be satisfied. Can do.

  Further, according to the tracking processing device 3, the speed vector smoothing processing unit 20 calculates the display estimated speed vector V <b> 2 (n) using the estimated speed vector V <b> 1 (n) calculated by the motion estimation unit 16. For this reason, it is not necessary for the display vector data generation unit 14 to perform an operation with high calculation load (tracking filter processing). Therefore, the calculation load in the tracking processing device 3 can be small.

  As described above, the estimated speed vector V1 (n) of the tracking target 200 can be calculated more accurately, the display estimated speed vector V2 (n) can be displayed in a stable manner, and the calculation can be performed. The tracking processing device 3 can be realized with a small load.

  Further, according to the tracking processing device 3, the first filter coefficient C1 is a value that determines a degree of associating data specifying the observation position P1d (n) with data specifying the estimated position P1e (n-1). Thereby, when calculating the estimated velocity vector V1 (n), the degree of reflecting the observation result at the n scan time can be easily determined by setting the first filter coefficient C1.

  Further, according to the tracking processing device 3, the velocity vector smoothing processing unit 20 is configured to be able to change the second filter coefficient C <b> 2 according to the presence / absence of a change in the tracking target 200. Thereby, the velocity vector smoothing process part 20 can set the suitable 2nd filter coefficient C2 according to the motion state of the tracking target 200. FIG.

  Further, according to the tracking processing device 3, the second filter coefficient C2 is calculated at the n-scan time point to data specifying the display estimated velocity vector V2 (n-1) calculated at the (n-1) scan time point. It is a value that determines the degree of associating the data specifying the estimated speed vector V1 (n). With this configuration, as the second filter coefficient C2 becomes smaller, the estimated display speed vector V2 (n) is strongly influenced by the past estimated display speed vector V2 (n−1). Become. As a result, the display estimated speed vector V2 (n) is hardly affected by the estimated speed vector V1 (n). Therefore, the display estimated speed vector V2 (n) is displayed on the display 4 in a manner in which unnecessary fluctuations are suppressed. On the other hand, as the second filter coefficient C2 increases, the display estimated speed vector V2 (n) is strongly influenced by the estimated speed vector V1 (n) calculated at the n-scan time point. Therefore, more calculation results of the estimated speed vector V1 (n) can be reflected in the display estimated speed vector V2 (n). As a result, the display estimated speed vector V2 (n) can be set to a more responsive value with respect to a change in the movement of the tracking target 200.

  More specifically, the velocity vector smoothing processing unit 20 uses the second filter coefficient C2 when the tracking target 200 has not been detected as the second filter coefficient C2 when the tracking target 200 has been detected as the second filter coefficient C2. Set smaller than C2. Thereby, when the tracking target 200 is moving straight, that is, when it is not necessary to change the display estimated speed vector V2 (n), unnecessary change in the display estimated speed vector V2 (n) is performed. Can be suppressed. On the other hand, when the tracking target 200 is changing the needle movement, the estimated velocity vector V2 (n) can be changed with good responsiveness in accordance with the above-described needle movement.

  Further, according to the tracking processing device 3, the maneuver detection unit 19 determines whether or not the tracking target 200 has changed the course based on the relationship between the estimated velocity vector V1 (n-1) and the observation position P1d (n). Determine. With such a simple configuration, it is possible to reduce a calculation load in detecting a change in the tracking target 200.

  More specifically, the motion estimation unit 16 calculates the outer product of the vector V3 and the estimated speed vector V1 at each of the consecutive (n-1) scan points and n scan points. And the maneuver detection part 19 determines with the tracking target 200 moving straight, when the code | symbol of the calculation result of an outer product differs in the said some continuous said scanning time. In this way, it is possible to determine that the tracking target 200 is moving straight by simple determination using cross product calculation.

  Moreover, the maneuver detection part 19 determines with the tracking target 200 having changed the needle | hook when the code | symbol of the calculation result of an outer product is the same in several said continuous time points. In this way, it is possible to determine that the tracking target 200 is moving by a simple determination using outer product calculation.

  Further, according to the tracking processing device 3, the velocity vector smoothing processing unit 20 sets the second filter coefficient C <b> 2 according to the needle changing accuracy Acc (n) of the tracking target 200. Thus, the display estimated speed vector V2 (n) can be calculated in accordance with the needle changing accuracy Acc (n) of the tracking target 200.

  More specifically, the second filter coefficient C2 at the n scan time is increased as the needle changing accuracy Acc (n) is increased. That is, for the tracking target 200, the second filter coefficient C2 is increased as the duration of the needle changing movement is longer. As a result, it is possible to calculate an accurate display estimated speed vector V2 (n) in which more of the needle changing movement of the tracking target 200 is considered. In this case, the estimated display speed vector V2 (n) and the estimated speed vector V1 (n) are closer to each other. On the other hand, when the needle changing accuracy Acc (n) is zero, the second filter coefficient C2 is set to the minimum value C2min on the setting. That is, when the tracking target 200 is moving straight, the second filter coefficient C2 is set to a minimum value on setting. As a result, the display estimated speed vector V2 (n) can be accurately calculated in a manner in which the rectilinear movement of the tracking target 200 is more considered.

  Here, for example, when the error between the observed position of the tracking representative point and the predicted position is greater than or equal to a predetermined threshold value, a configuration in which it is determined that the tracking target is moving in a changing direction can be considered. However, in such a configuration, the above-described error becomes large when a shake motion (swing) occurs in the antenna or when the ship is in a aging environment. For this reason, it is difficult to detect the change of the tracking target with high accuracy.

  On the other hand, according to the tracking processing device 3, the needle changing accuracy Acc (n) is calculated based on the outer product calculation. Then, the second filter coefficient C2 is set based on the needle changing accuracy Acc (n). According to such a configuration, even when the antenna 5 is shaken, or when the ship 100 is in a stormy environment, it is possible to detect the change of the tracking target 200 with high accuracy. It becomes. As a result, the speed vector smoothing processing unit 20 can calculate the display estimated speed vector V2 (n) more accurately even under bad weather conditions.

  For example, in the tracking devices described in Patent Documents 1 and 2, the filter coefficient in the first motion estimation unit and the filter coefficient in the second motion estimation unit are fixed. For this reason, the filter coefficient that can be set in the tracking device is limited to two types. As a result, when the tracking target changes its needle at an extremely large changing speed, the movement of the tracking target cannot be tracked with good responsiveness. In addition, there is a limit to the processing for reducing the observation error when an observation error more than expected occurs in the tracking target observation. In addition, it is not easy to set an optimal relationship between the filter coefficient of the first motion estimation unit and the filter coefficient of the second motion estimation unit. That is, the work for optimal setting of the filter coefficient becomes complicated.

  On the other hand, according to the tracking processing device 3, the first filter coefficient C1 and the second filter coefficient C2 are set to be freely changeable in a wide range. Therefore, the degree of freedom in setting these filter coefficients C1 and C2 is high. Therefore, according to the tracking processing device 3, there is no problem with the tracking device described in Patent Documents 1 and 2.

  As mentioned above, although embodiment of this invention was described, this invention is not limited to the above-mentioned embodiment, As long as it described in the claim, various changes are possible. For example, the following modifications may be made.

(1) In the above-described embodiment, the maneuver detection unit has been described as an example of the configuration in which the movement of the tracking target is detected. However, this need not be the case. For example, the maneuver detector may detect the presence or absence of a speed change (shift) of a tracking target that is moving straight ahead. In this case, the maneuver detection unit calculates a vector (orthogonal vector) that is orthogonal to the estimated velocity vector and that starts from the tip of the estimated velocity vector. The maneuver detection unit calculates a vector passing through the origin of the orthogonal vector and the observation position of the tracking target, and calculates an outer product of the vector and the orthogonal vector. By determining the sign of this outer product, it is possible to determine whether or not the tracking target is shifted.

(2) When calculating the estimated display speed vector V2 (n), the estimated display speed vector V2 (n) is divided into an X-direction component and a Y-direction component, and the speed vector smoothing process is performed. You may go. In addition, the display estimated speed vector V2 (n) may be subjected to speed vector smoothing processing separately for the azimuth component and the speed component.

(3) In the above-described embodiment, a configuration in which more specific consideration is given to the observation error in the direction of the antenna angle may be employed.

(4) In the above-described embodiment, an example in which the center point of the target echo image is used as the tracking representative point has been described. However, this need not be the case. For example, the forefront edge point that is the closest point to the ship in the target echo image may be used as the tracking representative point.

(5) In the above-described embodiment, when the sign of the variable ε is different between the (n−1) scan time and the n scan time (NO in step S207), the maneuver detection unit 19 uses the needle change accuracy Acc ( An example in which n) is uniformly set to zero has been described. However, this need not be the case. For example, in this case, the needle changing accuracy Acc (n) may be configured to gradually approach zero each time NO is determined in step S207.

(6) In the above-described embodiment, the first filter coefficient C1 is exemplified by the form set based on the predicted position P1e (n) or the predicted position P1e (n-1) and the form having a constant value. explained. However, this need not be the case.

  For example, the motion estimation unit 16 may be configured not to change the first filter coefficient C1 when there is no change in the relative position between the position of the antenna 5 and the position of the tracking target 200. Thereby, the motion estimation unit 16 can calculate the estimated velocity vector V1 (n) in a more stable manner. As a result, the motion estimation unit 16 can calculate the estimated speed vector V1 (n) more accurately.

  In this case, the motion estimation unit 16 may be configured to be able to change the first filter coefficient C1 according to a change in the relative position between the position of the antenna 5 and the position of the tracking target 200. Thereby, the motion estimation unit 16 can set the first filter coefficient C1 suitable for calculating the estimated velocity vector V1 (n) of the tracking target 200. As a result, the motion estimation unit 16 can calculate the estimated velocity vector V1 (n) of the tracking target 200 with high responsiveness to the motion of the tracking target 200. Further, the motion estimation unit 16 can calculate the estimated speed vector V1 (n) so that the error of the estimated speed vector V1 (n) becomes small.

(7) In the above-described embodiment, the display vector data generation unit has been described as an example having a maneuver detection unit. However, this need not be the case. The maneuver detection unit may be omitted. In this case, the speed vector smoothing processing unit can calculate the estimated speed vector for display regardless of the needle changing movement of the tracking target. Therefore, the amount of calculation in the tracking processing device can be reduced.

(8) In the above-described embodiment, the tracking processing device is described as an example of a tracking processing device for a ship. However, the present invention is not limited to a tracking processing device for ships, but can be applied as a tracking processing device for other targets.

  The present invention can be widely applied as a tracking processing device and a tracking processing method used for tracking a target.

3 Tracking Processing Device 15 Capture Processing Unit 16 Motion Estimation Unit 20 Speed Vector Smoothing Processing Unit (Display Processing Unit)
200 Tracking target (target selected as tracking target)
C1 first filter coefficient C2 second filter coefficient P1d observation position (captured position)
V1 estimated speed vector V2 display estimated speed vector

Claims (12)

A capture processing unit for capturing the position of the target selected as the tracking target;
A motion estimation unit that performs a first filter process for calculating an estimated velocity vector of the target, which is used for tracking the target, using the data that identifies the captured position;
A display processing unit that calculates a display estimated speed vector used for display on the display by performing a second filter process on the data specifying the estimated speed vector;
With
The tracking processing device, wherein the first filter coefficient used for the first filter processing and the second filter coefficient used for the second filter processing are set independently of each other. The tracking processing device according to claim 1,
The acquisition processing unit is configured to be connected to a receiving device for receiving a signal specifying the target,
The motion estimator is configured not to change the first filter coefficient when there is no change in the relative position between the position of the receiving device and the position of the target. A tracking processing device. The tracking processing device according to claim 2,
The tracking processing device, wherein the motion estimation unit can change the first filter coefficient according to a change in a relative position between the position of the receiving device and the position of the target. The tracking processing device according to any one of claims 1 to 3,
The motion estimation unit is configured to calculate an estimated position where the target is estimated to reach,
The tracking processing device according to claim 1, wherein the first filter coefficient is a value that determines a degree of associating the data specifying the estimated position with the data specifying the position captured by the capture processing unit. The tracking processing device according to any one of claims 1 to 4,
A maneuver detection unit for detecting the presence or absence of a change in the target,
The tracking processing device, wherein the display processing unit is configured to be able to change the second filter coefficient according to the presence or absence of the needle change. The tracking processing device according to claim 5,
The second filter coefficient includes data specifying the estimated speed vector calculated at a time later than the first time in data specifying the display estimated speed vector calculated at a predetermined first time. A tracking processing apparatus characterized by being a value that determines a degree of association. The tracking processing device according to claim 6,
The display processing unit sets the second filter coefficient when the needle change is not detected to be smaller than the second filter coefficient when the needle change is detected. apparatus. The tracking target device according to any one of claims 5 to 7,
The tracking processing apparatus, wherein the maneuver detection unit determines whether or not the target has changed based on a relationship between the estimated velocity vector and the captured position. The tracking target device according to claim 8,
The motion estimation unit calculates the estimated velocity vector at a predetermined first time point,
The maneuver detection unit calculates a predetermined vector connecting a start point of the estimated velocity vector and the position of the target at a time point later than the first time point, and the predetermined vector, Calculate the outer product with the estimated velocity vector,
The calculation of the outer product by the maneuver detection unit is configured to be performed at a plurality of time points,
The tracking processing apparatus according to claim 1, wherein the maneuver detection unit determines that the target is moving straight when the signs of the calculation results of the outer products are different at a plurality of successive time points. The tracking processing device according to claim 9,
The tracking processing device according to claim 1, wherein the maneuver detection unit determines that the target has changed when the sign of the calculation result of the outer product is the same at a plurality of successive time points. The tracking processing device according to claim 9 or 10,
The maneuver detection unit calculates a needle change accuracy of the target based on a sign of a calculation result of the outer product at a plurality of successive time points,
The tracking processing device, wherein the display processing unit sets the second filter coefficient in accordance with the needle changing accuracy. A capture processing step for capturing the position of the target selected as the tracking target;
A motion estimation step for performing a first filter process for calculating an estimated velocity vector of the target, which is used for tracking the target, using the data for identifying the captured position;
A display processing step of calculating a display estimated speed vector used for display on the display by performing a second filter process on the data specifying the estimated speed vector;
Including
The tracking processing method, wherein the first filter coefficient used for the first filter processing and the second filter coefficient used for the second filter processing are set independently of each other.

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