JP5679856B2 - Positioning device and positioning method - Google Patents

Description

  The present invention relates to a positioning apparatus and a positioning method for observing a signal coming in time series from a target that is a positioning object on a mobile platform and positioning the target.

FIG. 8 is an explanatory diagram showing an example of a situation to which the conventional positioning method disclosed in Non-Patent Document 1, for example, is applied, and FIG. 9 is an explanatory diagram showing an overview of the conventional positioning method.
FIG. 10 is a flowchart showing the grouping process of angle values.
In the conventional positioning method, as shown in FIG. 8, it is assumed that some measurement amounts related to a plurality of targets are obtained in time series on the mobile platform.
The mobile platform only needs to be a mobile body equipped with a device for observing a certain measurement amount related to the target, and includes, for example, a vehicle, a ship, an aircraft, a satellite, and the like.

In the positioning method shown in FIG. 9, the arrival angle value indicating the angle of the signal arriving from the target is observed in time series as the measurement amount related to the target, and the target is positioned from the arrival angle value obtained in time series. .
In the example of FIG. 9, the intersection of the normals extending in the angle measuring direction is the measurement position.
However, in practice, it is unknown which target the measured quantity on the mobile platform is related to the signal coming from. Therefore, each measured quantity is grouped for each target in some way, It is necessary to measure the target.

Therefore, in the conventional positioning method, the residual of the measured amount is calculated, and positioning is performed while grouping the measured amount into each target so that the residual becomes small.
For example, when an arrival angle value (measurement value) is obtained as a measurement quantity, grouping and positioning are performed such that the sum of squares of the residual of the measurement value is minimized.
Specifically, grouping and positioning are performed so that the index value of the following equation (1) is minimized.

In Expression (1), J is the number of targets, and θ (t _k ) is an angle measurement value (k = 1,..., K) at time t _k .
θ hat _j (t _k ) is an estimated angle value of the j th target at time t _k , and x hat _j is a position vector (j = 1,..., J) of the j th target.
Here, for the purposes of electronic filing, “^” attached to alphabet letters is described as a hat.
σ _θ is the angle measurement error standard deviation.

In the positioning method of FIG. 9, as an example of the residual, first, using the measured angle values {θ (t ₁ ), θ (t ₃ ), θ (t ₆ )} from the first target, The position vector x of hat ₁ is calculated.
For example, the positioning vector x hat ₁ can be calculated by the following least squares solution.

Next, the angle estimate value θ hat ₁ (t _k ) of the first target at time t _k is calculated by the following equation (8).

When calculating equation (8) for time t _k = t ₁ , t ₃ , t ₆ , the angle measurement residual of the first target is as shown in equation (9) below.

When the angle measurement residual of the first target is calculated as described above, the angle measurement residual is calculated in the same manner for the second target.
Then, the sum of the angle measurement residual of the first target and the angle measurement residual of the second target is calculated, and the angle measurement θ (t _k ) is grouped so that the sum of the residuals is minimized. I do.
Then, the target is measured for each group using the angle measurement value θ (t _k ) belonging to each group.

Here, a method for minimizing the index value of Expression (1) will be described.
There are various minimization methods. For example, a grouping process as shown in FIG. 10 is conceivable.
The grouping process of FIG. 10 executes the following procedures (1) to (4).

(1) Initial group setting A group to which the angle measurement value θ (t _k ) (k = 1,..., K) at time t _k belongs is randomly assigned.
(2) Each group positioning Positioning vector x hat _j (j = 1,..., J), which is a positioning value of a gate for each group, using an angle value θ (t _k ) belonging to each group. Calculate

(3) Group update by θ From the moving platform position X _p (t _k ) at time t _k and the positioning vector x hat _j which is the positioning value of the j th gate, the angle estimate value θ hat _{j of} the j th target Calculate (t _k ).
Then, the residual of the estimated angle value θ hat _j (t _k ) of the jth target and each measured angle value θ (t _k ) is calculated, and the group to which each measured angle value θ (t _k ) belongs is determined as the most residual. Is changed to a group of position vectors x hat _j .
(4) Convergence determination Even if the steps (2) to (3) are repeated, if there is no change in the group to which all the angle measurement values θ (t _k ) belong, it is determined that the angle has converged, and a series of processes Exit.
When the group to which the angle measurement value θ (t _k ) belongs is changed, the procedures (2) to (3) are repeated.

Pei-yih Ting and Ronald A. Iltis, “Multitarget Motion Analysis in a DSN”, IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS, VOL. 21. NO. 5, 1991.

  Since the conventional positioning method is configured as described above, the group to which the angle measurement value belongs is updated so that the residual angle measurement value becomes small. However, even if the group is updated based only on the residual of the angle measurement value, the angle measurement value cannot be grouped with high accuracy, and sufficient positioning performance cannot be obtained.

  The present invention has been made to solve the above-described problems, and an object thereof is to obtain a positioning device and a positioning method capable of increasing the positioning accuracy of a target.

The positioning device according to the present invention observes a signal that arrives in time series from a positioning object, outputs a signal observation value that is the observation result, observes the power of the signal, and outputs the power that is the observation result. Observation means for outputting observation values, grouping means for grouping signal observation values output in time series from the observation means, and signal observation belonging to the group for each group divided by the grouping means using the value, and positioning means for positioning a positioning object, using the positioning value of the positioning object by positioning means, calculating a residual of all signals observed values outputted from the observation means, the sum of the residual A residual sum calculating means for calculating the residual sum, and a group updating means for updating the group to which the signal observation value belongs so that the sum of the residuals calculated by the residual sum calculating means is minimized. Total The output means obtains a function indicating the relationship between the power of the signal and the distance from the observation position to the positioning object for each group using the positioning value of the positioning object by the positioning means and the power observation value output from the observation means. , Calculate the residual of all the power observations and the residual of all the signal observations by adding the difference between the function and the power observations at each observation time. The sum is calculated .

According to the present invention, a signal arriving in time series from a positioning object is observed, a signal observation value that is the observation result is output, and the power of the signal is observed, and a power observation value that is the observation result For each of the groups divided by the grouping means, the grouping means for grouping the signal observation values output in time series from the observation means, and the signal observation values belonging to the group Using the positioning means to measure the positioning object and the positioning value of the positioning object by the positioning means, the residual of all signal observation values output from the observation means is calculated, and the sum of the residuals is calculated A residual sum calculating means, and a group updating means for updating the group to which the signal observation value belongs so that the sum of the residuals calculated by the residual sum calculating means is minimized, and calculating the residual sum means Using the positioning value of the positioning object by the positioning means and the power observation value output from the observation means, a function indicating the relationship between the power of the signal and the distance from the observation position to the positioning object is obtained for each group. Is calculated as the residual of all power observations, and the sum of the residuals of all power observations and the residuals of all signal observations is calculated. Since it comprised so that there may be an effect which can improve the positioning precision of the target which is a positioning target object.

It is a block diagram which shows the positioning apparatus by Embodiment 1 of this invention. It is a flowchart which shows the processing content (positioning method) of the positioning apparatus by Embodiment 1 of this invention. It is explanatory drawing which shows the relationship of a power-distance and fitting of an unknown coefficient. It is a block diagram which shows the positioning apparatus by Embodiment 2 of this invention. It is a flowchart which shows the processing content (positioning method) of the positioning apparatus by Embodiment 2 of this invention. It is a block diagram which shows the positioning apparatus by Embodiment 3 of this invention. It is a flowchart which shows the processing content (positioning method) of the positioning apparatus by Embodiment 3 of this invention. It is explanatory drawing which shows an example of the situation where the conventional positioning method currently disclosed by the nonpatent literature 1 is applied. It is explanatory drawing which shows the outline | summary of the conventional positioning method. It is a flowchart which shows the grouping process of a measured angle value.

Embodiment 1 FIG.
1 is a block diagram showing a positioning apparatus according to Embodiment 1 of the present invention.
In FIG. 1, the signal receiving unit 1 includes, for example, an antenna, and performs a process of receiving a signal that arrives in time series from a target that is a positioning object on a mobile platform.
The angle measurement observation unit 2 is an observation device that observes an angle measurement value (signal observation value) indicating a reception angle of a signal received in time series by the signal reception unit 1.
The power observation unit 3 is an observation device that observes the power of the signals received in time series by the signal reception unit 1.
The signal receiving unit 1, the angle measuring unit 2, and the power observing unit 3 constitute observation means.
Here, an example is shown in which the observation means is composed of the signal reception unit 1, the angle measurement unit 2, and the power observation unit 3, but the signal reception unit 1, the angle measurement unit 2 and the power observation unit 3 are integrated. It may be realized.

The angle measurement value storage unit 4 is a memory that stores angle measurement values observed by the angle measurement observation unit 2.
The power observation value storage unit 5 is a memory for storing the power observation value observed by the power observation unit 3.
The grouping unit 6 is composed of, for example, a semiconductor integrated circuit on which a CPU is mounted, a one-chip microcomputer, or the like, and performs a process of randomly grouping the angle measurement values stored in the angle measurement value storage unit 4 To do. The grouping unit 6 constitutes grouping means.

The group memory unit 7 has memory areas divided into groups, and stores angle measurement values belonging to each group.
The positioning processing unit 8 is composed of, for example, a semiconductor integrated circuit on which a CPU is mounted, a one-chip microcomputer, or the like. For each group divided by the grouping unit 6, angle measurement values belonging to the group are used. Then, perform the process of positioning the target. The positioning processing unit 8 constitutes positioning means.

The residual sum calculation unit 9 is composed of, for example, a semiconductor integrated circuit on which a CPU is mounted, a one-chip microcomputer, or the like, and the measured value storage unit 4 uses the measured value of the target by the positioning processing unit 8. The residuals of all stored angle measurement values and the residuals of all power observation values stored by the power observation value storage unit 5 are calculated, and the residuals of all signal observation values and all power observations are calculated. A process for calculating the sum of the residual values is performed. The residual sum calculation unit 9 constitutes residual sum calculation means.
The group update processing unit 10 is composed of, for example, a semiconductor integrated circuit on which a CPU is mounted, or a one-chip microcomputer, so that the total sum of residuals calculated by the residual total calculation unit 9 is minimized. The group memory unit 7 performs processing for updating the group to which the angle measurement value stored for each group belongs. The group update processing unit 10 constitutes a group update unit.

In FIG. 1, the signal receiving unit 1, the angle measurement unit 2, the power observation unit 3, the angle measurement value storage unit 4, the power observation value storage unit 5, the grouping unit 6, the group memory unit 7, which are components of the positioning device, Although the positioning processing unit 8, the residual sum calculation unit 9, and the group update processing unit 10 are each configured by dedicated hardware, the positioning device may be entirely or partially configured by a computer. Good. In this case, the processing contents of the signal reception unit 1, the angle measurement unit 2, the power observation unit 3, the grouping unit 6, the positioning processing unit 8, the residual sum calculation unit 9, and the group update processing unit 10 are described. All or part of the program may be stored in the memory of the computer, and the CPU of the computer may execute the program stored in the memory.
FIG. 2 is a flowchart showing the processing contents (positioning method) of the positioning apparatus according to Embodiment 1 of the present invention.

Next, the operation will be described.
The signal receiving unit 1 receives a signal that arrives in time series from a target that is a positioning object on the mobile platform (step ST1).
When the signal receiving unit 1 receives a signal that arrives in time series from the target, the angle measurement unit 2 observes the reception angle of the signal, and the angle measurement value θ (t _k at the observation time t _k that is the observation result. ) (K = 1,..., K) are stored in the measured angle value storage unit 4 (step ST2).
Power monitoring unit 3, the signal receiving unit 1 receives a signal arriving in time series from the target, and observing the power of the signal, the observation result at a measurement time t _k of the power observed value P (t _k) ( k = 1,..., K) are stored in the power observation value storage unit 5 (step ST3).

The grouping unit 6 randomly groups the angle measurement values θ (t _k ) at the observation time t _k stored by the angle measurement value storage unit 4, and the angle measurement values θ (t _k ) are grouped by the group memory unit 7. (Step ST4).
For example, if the group to which the angle measurement value θ (t _k ) belongs is the first group, the angle measurement value θ (t _k ) is stored in the corresponding area of the first group in the group memory unit 7, and the angle measurement value θ If the group to which (t _k ) belongs is the second group, the angle measurement value θ (t _k ) is stored in the corresponding region of the second group in the group memory unit 7.

When the grouping unit 6 randomly groups the angle measurement values θ (t _k ) at the observation time t _k , the positioning processing unit 8 determines the angle measurement values θ (belonging to each group stored in the group memory unit 7. Using t _k ), the target is positioned for each group (step ST5).
That is, for example, as shown in FIG. 9, the positioning processing unit 8 receives signals from two targets, and the angle measurement value at the observation time t _k (k = 1, 2, 3,..., 6). When θ (t _k ) is divided into two groups, for example, with respect to the positioning vector x hat ₁ that is the positioning value of the first target, the angle measurement values {θ (t ₁ ), θ (t ₃ ), θ (T ₆ )} can be used to calculate.

The positioning vector x hat ₁ which is the positioning value of the first target can be calculated by, for example, the following least squares solution.

The positioning vector x hat ₂ , which is the positioning value of the second target, can be calculated in the same manner using the angle measurement values {θ (t ₂ ), θ (t ₄ ), θ (t ₅ )}. .
Thereby, the positioning value of each target is obtained, but the grouping of the angle measurement value θ (t _k ) by the grouping unit 6 is performed at random, and the angle measurement value θ (t _k ) arrives. It is not a grouping by accurately identifying the origin.
Therefore, the positioning value of each target at this stage includes an error, and in order to obtain a highly accurate positioning value, it is necessary to update the group to which each angle value θ (t _k ) belongs.

In the first embodiment, grouping is performed so that the index value of the following equation (17) is minimized.

In Expression (17), J is the number of targets, and θ (t _k ) is an angle measurement value (k = 1,..., K) at time t _k .
θ hat _j (t _k ) is an estimated angle value of the j th target at time t _k , x hat _j is a position vector (j = 1,..., J) of the j th target, and σ _θ is an angle value. Measurement error standard deviation.
P (t _k ) is the power observation value at time t _k , P hat _j (t _k ) is the power estimation value of the jth target at time t _k , and σ _P is the measurement error standard deviation of the power observation value.
Here, for the purposes of electronic filing, “^” attached to alphabet letters is described as a hat.

The group update process will be specifically described below.
The residual sum calculation unit 9 calculates the residuals of all the angle measurement values θ (t _k ) stored by the angle measurement value storage unit 4 (step ST6).
That is, the residual sum calculation unit 9 calculates the time t _{k from the} positioning vector x hat _j which is the positioning value of the j-th target by the positioning processing unit 8 and the position X _p (t _k ) of the moving platform at the time t _k. The angle estimate value θ hat _j (t _k ) of the jth target at is calculated.
In the example of FIG. 9, the angle estimate value θ hat ₁ (t _k ) of the first target can be calculated by the following equation (18).

After calculating the estimated angle value θ hat _j (t _k ) of the j-th target at time t _k , the residual sum calculation unit 9 calculates the estimated angle value θ hat _j (t _k ) and the measured angle value θ at time t _k . From (t _k ), the angle measurement residual of the jth target is calculated.
In the example of FIG. 9, when calculating Equation (18) for times t _k = t ₁ , t ₃ , and t ₆ , the angle measurement residual of the first target is as shown in Equation (19) below. .

Next, the residual sum total calculation unit 9 calculates the residuals of all the power observation values P (t _k ) stored in the power observation value storage unit 5 (step ST7).
That is, the residual sum calculation unit 9 performs the fitting for the unknown coefficient α in the function of the following equation (20) because the power of the signal is inversely proportional to the square of the distance r between the target and the mobile platform. And the difference between the observed power values P (t _k ) is the residual.
The fitting method is not particularly limited. For example, the solution of the least square fitting is given by the following equation.

The residual sum calculation unit 9 calculates the fitting function of each group by calculating each group. For example, as shown in FIG. 3, when there are two targets, a fitting function is obtained for the first target and the second target.
The difference between these fitting functions and the power observation value P (t _k ) at each time t _k becomes a residual, and the sum of these becomes the final power observation value residual.

When the residual sum calculation unit 9 calculates the residuals of all the angle measurement values θ (t _k ) and the residuals of all the power observation values P (t _k ), as shown in Expression (17), The sum of the residuals of all angle measurement values θ (t _k ) and the residuals of all power observation values P (t _k ) is calculated (step ST8).

The group update processing unit 10 stores, for each group, in the group memory unit 7 so as to minimize the sum when the residual sum calculation unit 9 calculates the sum of the angle measurement value residual and the power observation value residual. The group to which the measured angle value θ (t _k ) belongs is updated (step ST9).
For example, when there are two targets, the angle measurement residual and the power observation value belong to the second group rather than the case where a certain angle measurement value θ (t _k ) belongs to the first group. When the total sum of residuals becomes small, the group to which the angle measurement value θ (t _k ) belongs is changed from the first group to the second group.

The group update processing unit 10 minimizes the sum of the angle measurement value residual and the power observation value residual, and when there is no need to change the group to which the angle measurement value θ (t _k ) belongs, the angle measurement value θ (t _k ) is determined to have converged (step ST10), and the series of processes is terminated.
When the group to which the angle measurement value θ (t _k ) belongs is changed, the group update processing unit 10 determines that it has not converged (step ST10), returns to the process of step ST5, and performs steps ST5 to ST10. The process is repeated.

  As is apparent from the above, according to the first embodiment, the angle measurement observation unit 2 that observes the angle measurement value indicating the reception angle of the signal that arrives in time series from the target, and the power that observes the power of the signal. Using the observation unit 3, the grouping unit 6 that performs grouping of the angle measurement values observed by the angle measurement unit 2, and the angle measurement values belonging to the group for each group divided by the grouping unit 6. Using the positioning processing unit 8 for positioning the target and the positioning values of the target by the positioning processing unit 8, the residuals of all the measured values observed by the angle measuring unit 2 and the power observing unit 3 were observed. A group update processing unit is provided, which calculates residuals of all power observation values and calculates a sum of residuals of all angle measurement values and residuals of all power observation values. 10 is calculated by the residual sum calculation unit 9. So that the sum of the residual becomes minimum, since it is configured to update the group including the respective measured angle value, grouping the accuracy of angle measurement value is improved. As a result, the target positioning accuracy can be improved.

In the first embodiment, the residual sum calculation unit 9 calculates the sum of the residuals of all the measured angle values θ (t _k ) and the residuals of all the observed power values P (t _k ). As shown in the following formula (24), the weighted sum of the residuals of all the angle measurement values θ (t _k ) and the residuals of all the power observation values P (t _k ) is calculated. Then, the group update processing unit 10 may update the group to which each angle measurement value θ (t _k ) belongs so that the weighted sum calculated by the residual sum calculation unit 9 is minimized.

In the first embodiment, the angle measurement unit 2 observes the angle measurement value θ (t _k ) as the observation value of the signal received in time series by the signal reception unit 1. Is not limited to the angle measurement value θ (t _k ) as long as it is a measurement amount related to the target.
For example, the observed value of the signal may be a TOA (Time Of Arrival) value indicating the arrival time of the signal, a FOA (Frequency Of Arrival) value indicating the arrival frequency of the signal, or the like.
In addition, when there are two mobile platforms, the TDOA (Time Difference Of Arrival) value indicating the arrival time difference between signals received on the two mobile platforms, the FDOA (Frequency Difference Of Arrival) value indicating the difference in arrival frequency, etc. Good.

When a TOA value, FOA value, TDOA value, or FDOA value is used as an observed value of a signal, a TOA value, FOA value, TDOA value, or FDOA value may be used instead of θ in Equation (17).
Specifically, when the TOA value is τ, the FOA value is f, the TDOA value is Δτ, and the FDOA value is Δf, the following equations (25) to (28) may be used instead of the equation (17).

Here, σ _τ is the measurement error standard deviation of the TOA value, σ _f is the measurement error standard deviation of the FOA value, σ _Δτ is the measurement error standard deviation of the TDOA value, and σ _Δf is the measurement error standard deviation of the FDOA value.
In the positioning method based on the TOA value, the FOA value, the TDOA value, and the FDOA value, if the simultaneous equations similar to the equations (11) to (16) are established, the least square solution is calculated for the positioning position vector x hat of the target. Good.
Details are disclosed in Non-Patent Documents 2 and 3 below, for example.
[Non-Patent Document 2]
PAUL C.I. CHESTNUT, “Emitter Location Accuracy Using TDOA and Differential Doppler”, IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS VOL. AES-18, NO. 2 MARCH 1982
[Non-Patent Document 3]
U. Engel, “A Geomation Methodology TOA and FOA Measurements”, PROCEEDINGS OF THE 6th WORKSHOP ON POSITIONING, NAVIGATION AND COMMUNICATION 2009 '.

In addition, a plurality of types of signal observation values may be obtained at each time. For example, when a pair of TDOA value and FDOA value is obtained, the following equation (29) may be used.

Further, when a pair of the azimuth angle Az and the elevation angle El is obtained as an angle measurement value, the following equation (30) may be used.

Embodiment 2. FIG.
FIG. 4 is a block diagram showing a positioning apparatus according to Embodiment 2 of the present invention. In the figure, the same reference numerals as those in FIG.
The grouping unit 11 is composed of, for example, a semiconductor integrated circuit on which a CPU is mounted, a one-chip microcomputer, or the like, and performs processing for grouping the measured angle values stored by the measured angle value storage unit 4 in a round robin manner. carry out. The grouping unit 11 constitutes grouping means.

The positioning processing unit 12 is composed of, for example, a semiconductor integrated circuit on which a CPU is mounted, a one-chip microcomputer, or the like. From the combinations of all groups divided by the grouping unit 11, any group can be selected. The combination is selected, and for each group of the combination, the process of positioning the target is performed using the angle measurement value belonging to the group. The positioning processing unit 12 constitutes positioning means.
The group selection unit 13 is composed of, for example, a semiconductor integrated circuit on which a CPU is mounted, a one-chip microcomputer, or the like. From the combinations of all groups divided by the brute force by the grouping unit 11, the residual summation is performed. A process of selecting a combination of groups having the smallest sum of residuals calculated by the calculation unit 9 is performed. The group selection unit 13 constitutes a group selection unit.

In FIG. 4, the signal receiving unit 1, the angle observation unit 2, the power observation unit 3, the angle measurement value storage unit 4, the power observation value storage unit 5, the grouping unit 11, the group memory unit 7, Although the positioning processing unit 12, the residual sum calculation unit 9, and the group selection unit 13 are each configured by dedicated hardware, all or a part of the positioning device may be configured by a computer. . In this case, a program describing the processing contents of the signal receiving unit 1, the angle measuring unit 2, the power observing unit 3, the grouping unit 11, the positioning processing unit 12, the residual sum calculating unit 9, and the group selecting unit 13. May be stored in the memory of the computer, and the CPU of the computer may execute the program stored in the memory.
FIG. 5 is a flowchart showing the processing contents (positioning method) of the positioning device according to Embodiment 2 of the present invention.

Next, the operation will be described.
In the second embodiment, as the observed value of the signal received in time series by the signal receiving unit 1, the angle measuring unit 2 observes the angle measuring value θ (t _k ). As in the first embodiment, the signal observation value is not limited to the angle measurement value θ (t _k ) as long as it is a measurement amount related to the target. For example, as the signal observation value, the TOA value, the FOA value, the TDOA value, and the FDOA You may make it observe a value.

In the grouping unit 11, as in the first embodiment, the angle measurement observation unit 2 stores the angle measurement values θ (t _k ) (k = 1,..., K) at the observation time t _k as angle measurement values. When stored in the unit 4, the angle measurement values θ (t _k ) at the observation time t _k stored by the angle measurement value storage unit 4 are grouped by round robin, and the angle measurement values θ (t _k ) are grouped into the group memory. Store in the unit 7 (step ST11).
For example, when there are two targets, when three angle measurement values θ (t ₁ ), θ (t ₂ ), θ (t ₃ ) are obtained, three angle measurement values θ (t ₁ ), θ Since (t ₂ ) and θ (t ₃ ) are divided into two groups in the following eight combinations, three angle measurement values θ (t ₁ ), θ (t ₂ ), and θ (t ₃ ) are set to 8 Sort into combinations of street groups.

First group Second group (1) θ (t ₁ ) θ (t ₂ ), θ (t ₃ )
(2) θ (t ₂ ) θ (t ₁ ), θ (t ₃ )
(3) θ (t ₃ ) θ (t ₁ ), θ (t ₂ )
(4) θ (t ₁ ), θ (t ₂ ) θ (t ₃ )
(5) θ (t ₁ ), θ (t ₃ ) θ (t ₂ )
(6) θ (t ₂ ), θ (t ₃ ) θ (t ₁ )
(7) θ (t ₁ ), θ (t ₂ ), θ (t ₃ ) None (8) None θ (t ₁ ), θ (t ₂ ), θ (t ₃ )

When the grouping unit 11 divides the angle measurement value θ (t _k ) at the observation time t _k into brute force groups, the positioning processing unit 12 has not yet selected from all the combinations of the brute force groups. A combination of arbitrary arbitrary groups is selected (step ST12).
When selecting a combination of arbitrary groups, the positioning processing unit 12 measures the target for each group of the combinations using the angle value θ (t _k ) belonging to the group (step ST13).
Since the target positioning process itself is the same as that of the positioning processing unit 8 in FIG. 1, detailed description thereof is omitted. For example, when the combination (1) is selected, the measured angle value θ (t ₁ ) is used. Positioning of the first target is performed, and positioning of the second target is performed using the angle measurement values θ (t ₂ ) and θ (t ₃ ).

When the positioning processing unit 12 measures the target, the residual sum calculation unit 9 stores the remaining angle values θ (t _k ) stored in the angle value storage unit 4 as in the first embodiment. The difference is calculated (step ST6).
For example, when the combination (1) is selected, the angle measurement value θ (t ₁ ) belongs to the first group, and the angle measurement values θ (t ₂ ) and θ (t ₃ ) belong to the second group. As a thing, the residual of the measured angle value θ (t _k ) is calculated.
Further, the residual sum calculation unit 9 calculates the residuals of all the power observation values P (t _k ) stored by the power observation value storage unit 5 as in the first embodiment (step ST7). .
Also, the residual sum calculation unit 9 calculates the sum of the residuals of all the angle measurement values θ (t _k ) and the residuals of all the power observation values P (t _k ), as in the first embodiment. Calculate (step ST8).

  The positioning processing unit 12 determines whether or not there is a group combination that has not been selected among all the group combinations divided by the brute force by the grouping unit 11 (step ST14). If there is a remaining group combination, the process returns to step ST12 to select an unselected group combination. Thereafter, the processes of steps ST13, ST6 to ST8, ST14 are repeated.

When all group combinations are selected and the total sum of residuals is calculated by the residual sum calculation unit 9, the group selection unit 13 selects all the group combinations divided by the round robin by the grouping unit 11. Thus, the combination of the groups having the smallest residual sum calculated by the residual sum calculating unit 9 is selected (step ST15).
For example, when the sum of the residuals when the combination (3) is selected is the minimum, the positioning value x hat ₁ of the first target measured using the positioning value θ (t ₃ ), and the measuring value The positioning value x hat ₂ of the second target measured using θ (t ₁ ) and θ (t ₂ ) is output as a positioning result.

  As is apparent from the above, according to the second embodiment, the angle measurement unit 2 that observes the angle measurement value indicating the reception angle of the signal that arrives in time series from the target, and the power that observes the power of the signal. The grouping unit 11 that performs grouping of the angle measurement values observed by the observation unit 3 and the angle measurement observation unit 2 from the brute force, and any combination of all the groups divided by the brute force by the grouping unit 11 For each group of the combination, the positioning processing unit 12 for positioning the target using the angle value belonging to the group, and the positioning value of the target by the positioning processing unit 12 are used. , Calculating the residuals of all the measured values observed by the angle measuring unit 2 and the residuals of all the power observed values observed by the power observing unit 3, of A residual sum calculating unit 9 for calculating the sum of the residuals of the force observation values, and the group selecting unit 13 selects the residual sum from among all the combinations of the groups divided by the grouping unit 11 Since the combination of the groups with the smallest sum of the residuals calculated by the calculation unit 9 is selected, the angle measurement value grouping accuracy is improved. As a result, the target positioning accuracy can be improved.

Embodiment 3 FIG.
6 is a block diagram showing a positioning apparatus according to Embodiment 3 of the present invention. In the figure, the same reference numerals as those in FIG.
The positioning processing unit 21 is the same processing unit as the positioning processing unit 8 of FIG. 1, and the positioning processing unit 21 constitutes a first measuring unit.
The residual sum total calculation unit 22 is composed of, for example, a semiconductor integrated circuit on which a CPU is mounted, a one-chip microcomputer, or the like, and the measured value storage unit 4 uses the measured value of the target by the positioning processing unit 21. Processing for calculating the residuals of all stored angle measurement values and calculating the sum of the residuals of all angle measurement values is performed. The residual sum calculation unit 22 constitutes residual sum calculation means.

The group update processing unit 23 is composed of, for example, a semiconductor integrated circuit on which a CPU is mounted, or a one-chip microcomputer, so that the total sum of residuals calculated by the residual total calculation unit 22 is minimized. The group memory unit 7 performs processing for updating the group to which the angle measurement value stored for each group belongs. The group update processing unit 23 constitutes a first group update unit.
The signal observation value exclusion unit 24 is composed of, for example, a semiconductor integrated circuit mounted with a CPU or a one-chip microcomputer, and has the same observation as the angle measurement value belonging to the group updated by the group update processing unit 23. Calculate the residual of the power observation value of the signal at the time, and if the residual of the angle measurement value or the residual of the power observation value is greater than or equal to a predetermined threshold, perform the process of excluding the angle measurement value from the group To do. The signal observation value exclusion unit 24 constitutes signal observation value exclusion means.

The positioning processing unit 25 is composed of, for example, a semiconductor integrated circuit on which a CPU is mounted, a one-chip microcomputer, or the like, and uses the measured angle values that are not excluded from the group by the signal observation value exclusion unit 24. Execute the process of positioning the positioning object for each group. The positioning processing unit 25 constitutes second positioning means.
In the example of FIG. 6, the two positioning processing units 21 and 25 are mounted, but the positioning processing unit 21 and the positioning processing unit 25 may be integrated.

The group update processing unit 26 is configured by, for example, a semiconductor integrated circuit on which a CPU is mounted, a one-chip microcomputer, or the like, and the signal observation value exclusion unit 24 is used by using the positioning value of the positioning object by the positioning processing unit 25. To calculate the residuals of all the measured values that are not excluded from the group, and update the group to which the measured values belong so that the sum of the residuals of all measured values is minimized. Perform the process. The group update processing unit 26 constitutes a second group update unit.
In the example of FIG. 6, the two group update processing units 23 and 26 are implemented, but the group update processing unit 23 and the group update processing unit 26 may be integrated.

In FIG. 6, the signal receiving unit 1, the angle measurement unit 2, the power observation unit 3, the angle measurement value storage unit 4, the power observation value storage unit 5, the grouping unit 6, the group memory unit 7, which are components of the positioning device, The positioning processing units 21 and 25, the residual sum calculation unit 22, the signal observation value exclusion unit 24, and the group update processing units 23 and 26 are each configured by dedicated hardware. Or a part may be comprised with the computer. In this case, the signal reception unit 1, the angle measurement unit 2, the power observation unit 3, the grouping unit 6, the positioning processing units 21 and 25, the residual sum calculation unit 22, the signal observation value exclusion unit 24, and the group update processing unit All or a part of the program describing the processing contents 23 and 26 may be stored in the memory of the computer, and the CPU of the computer may execute the program stored in the memory.
FIG. 7 is a flowchart showing the processing contents (positioning method) of the positioning device according to Embodiment 3 of the present invention.

Next, the operation will be described.
In the third embodiment, as the observed value of the signal received in time series by the signal receiving unit 1, the angle measuring unit 2 observes the angle measuring value θ (t _k ). As in the first embodiment, the signal observation value is not limited to the angle measurement value θ (t _k ) as long as it is a measurement amount related to the target. For example, as the signal observation value, the TOA value, the FOA value, the TDOA value, and the FDOA You may make it observe a value.

In FIG. 7, the processing contents of steps ST1 to ST4 are the same as those in the first embodiment, and the description thereof is omitted.
As with the positioning processing unit 8 in FIG. 1, the positioning processing unit 21 measures the target for each group divided by the grouping unit 6 using the measured angle value θ (t _k ) belonging to the group. (Step ST5).
When the positioning processing unit 21 measures the target, the residual sum calculation unit 22 measures all the angle measurement values θ (t) stored in the angle measurement value storage unit 4 like the residual sum calculation unit 9 of FIG. _k ) is calculated (step ST6), and the sum of the residuals of all the angle measurement values θ (t _k ) is calculated (step ST21).

When the residual sum calculation unit 22 calculates the sum of the residuals of all angle measurement values θ (t _k ), the group update processing unit 23 minimizes the sum as in the group update processing unit 10 of FIG. In the group memory unit 7, the group to which the angle measurement value θ (t _k ) stored for each group belongs is updated (step ST9).

Group update processing unit 23, the sum of the residuals of all the measured angle value θ (t _k) to minimize, Hakakakuchi theta when (t _k) need to change the group is no longer belongs, Hakakakuchi theta It is determined that the group to which (t _k ) belongs has converged (step ST10), and the process proceeds to the next step ST22.
When the group to which the angle measurement value θ (t _k ) belongs is changed, it is determined that the group update processing unit 23 has not converged (step ST10), the process returns to step ST5, and steps ST5, ST6, The processing of ST21, ST9, ST10 is repeated.

When the signal observation value exclusion unit 24 determines that the group update processing unit 23 has converged, the residual (residual) of the angle measurement value θ (t _k ) belonging to the group updated by the group update processing unit 23 The residual of the angle measurement value θ (t _k ) calculated by the sum calculation unit 22 is compared with a preset threshold θ _th, and the residual of the angle measurement value θ (t _k ) is greater than or equal to the threshold θ _th If it is, the angle measurement value theta (t _k) is erroneously detected is regarded as a (for some reason, large off and are measured values from the correct value), the angle measurement value from the group theta (t _k ) Is excluded (step ST22). In other words, since the erroneously detected angle measurement value θ (t _k ) does not belong to any target, a new erroneous detection group is prepared and the measured angle value θ (t _k ) is moved to the erroneous detection group.

Next, the signal observation value exclusion unit 24 receives the signal of the same observation time t _k as the angle measurement value θ (t _k ) belonging to the group updated by the group update processing unit 23 from the power observation value storage unit 5. The power observation value P (t _k ) is acquired, and the residual of the power observation value P (t _k ) is calculated by the same method as the residual sum calculation unit 9 in FIG.
Then, the signal observation value exclusion unit 24 compares the residual of the power observation value P (t _k ) with a preset threshold value P _th, and the residual of the power observation value P (t _k ) is the threshold value P. If it is greater than or equal to _th , the power observation value P (t _k ) is regarded as a false detection, and the angle measurement value of the signal at the same observation time t _k as the power observation value P (t _k ) from the group. Exclude θ (t _k ) (step ST23).

The positioning processing unit 25 uses the measured angle value θ (t _k ) that remains without being excluded from the group by the signal observation value excluding unit 24 to position the positioning object for each group (step ST24).
Since the target positioning process itself is the same as that of the positioning processing unit 8 in FIG. 1, detailed description thereof is omitted.

When the positioning processing unit 25 measures the target, the group update processing unit 26 uses the same method as the residual sum calculation unit 22 to all the angle measurement values remaining without being excluded from the group by the signal observation value exclusion unit 24. The residual of θ (t _k ) is calculated, and the sum of the residuals of all angle measurement values θ (t _k ) is calculated (step ST25).
Here, the group update processing unit 26 calculates the residual of measured angle value θ (t _k), utilizing the residual of angle measurement value calculated by the residual sum calculating unit 22 θ (t _k) You may make it do.

When the group update processing unit 26 calculates the sum of the residuals of all the angle measurement values θ (t _k ) remaining without being excluded from the group, the group memory unit 7 The group to which the measured angle value θ (t _k ) stored for each group belongs is updated (step ST26).
For example, when two targets are present, there angle measurement value θ (t _k) than if they belong to the first group, is better to belong to the second group, Hakakakuchi theta of (t _k) When the total sum of residuals becomes small, the group to which the angle measurement value θ (t _k ) belongs is changed from the first group to the second group.

Here, the group to which the angle measurement value θ (t _k ) belongs is updated so that the sum of the residuals of all the angle measurement values θ (t _k ) remaining without being excluded from the group is minimized. However, as in the group update processing unit 10 of FIG. 1, the sum of the residual of the measured angle value θ (t _k ) and the residual of the power observation value P (t _k ) is minimized. The group to which the angle measurement value θ (t _k ) belongs may be updated.

When the total sum of residuals is minimized and the group to which the angle measurement value θ (t _k ) belongs does not need to be changed, the group update processing unit 26 converges the group to which the angle measurement value θ (t _k ) belongs. (Step ST27), and a series of processing is terminated.
When the group to which the angle measurement value θ (t _k ) belongs is changed, it is determined that the group update processing unit 26 has not converged (step ST27), the process returns to step ST22, and steps ST22 to ST27 are performed. The process is repeated.

As is apparent from the above, according to the third embodiment, the group to which the angle measurement value θ (t _k ) belongs is updated in two stages, and the angle measurement value θ (t _k ) and the power observation value P Since (t _k ) is compared with the threshold value and the erroneously detected angle value θ (t _k ) is excluded from the group, the grouping accuracy of the angle value P (t _k ) is improved. As a result, the target positioning accuracy can be improved.

  In the present invention, within the scope of the invention, any combination of the embodiments, or any modification of any component in each embodiment, or omission of any component in each embodiment is possible. .

  1. Signal receiving unit (observation means), 2. Angle measurement observation unit (observation means), 3. Electric power observation unit (observation means), 4. Angle measurement value storage unit, 5. Electric power observation value storage unit, 6, 11. Grouping unit (grouping) Means), 7 group memory section, 8, 12 positioning processing section (positioning means), 9 residual sum calculating section (residual sum calculating means), 10 group updating processing section (group updating means), 13 group selecting section (group) Selection means), 21 positioning processing section (first measurement means), 22 residual sum calculation section (residual sum calculation means), 23 group update processing section (first group update means), 24 signal observation value exclusion section (Signal observation value exclusion means), 25 positioning processing section (second positioning means), 26 group update processing section (second group updating means).

Claims (14)

Observing means for observing signals coming from a positioning object in time series, outputting signal observation values as the observation results, observing the power of the signals, and outputting power observation values as the observation results When,
Grouping means for grouping signal observation values output in time series from the observation means;
For each group divided by the grouping means, using the signal observation values belonging to the group, positioning means for positioning the positioning object;
Using the positioning values of the positioning object by the positioning means , calculating residuals of all signal observation values output from the observation means, and calculating a residual sum total calculating means for calculating the sum of residuals;
Group updating means for updating the group to which the signal observation value belongs so that the sum of the residuals calculated by the residual sum calculating means is minimized ,
The residual sum calculation means uses the positioning value of the positioning object by the positioning means and the power observation value output from the observation means to determine the power of the signal and the distance from the observation position to the positioning object for each group. A function indicating the relationship is obtained, and a value obtained by adding the difference between the function and the observed power value at each observation time is calculated as a residual of all the observed power values. Calculate the sum of the residuals of signal observations
A positioning device characterized by that . Observing means for observing signals coming from a positioning object in time series, outputting signal observation values as the observation results, observing the power of the signals, and outputting power observation values as the observation results When,
A grouping means for grouping the signal observation values output in time series from the observation means by brute force;
From the combinations of all the groups divided by the grouping means, select a combination of arbitrary groups, and for each group of the combinations, using the signal observation values belonging to the group, the above Positioning means for positioning the positioning object;
Using the positioning values of the positioning object by the positioning means , calculating residuals of all signal observation values output from the observation means, and calculating a residual sum total calculating means for calculating the sum of residuals;
A group selection means for selecting a combination of groups having the smallest total sum of residuals calculated by the residual sum calculation means from among all combinations of groups divided by the round robin by the grouping means ;
The residual sum calculation means uses the positioning value of the positioning object by the positioning means and the power observation value output from the observation means to determine the power of the signal and the distance from the observation position to the positioning object for each group. A function indicating the relationship is obtained, and a value obtained by adding the difference between the function and the observed power value at each observation time is calculated as a residual of all the observed power values. Calculate the sum of the residuals of signal observations
A positioning device characterized by that . Observing means for observing signals coming from a positioning object in time series, outputting signal observation values as the observation results, observing the power of the signals, and outputting power observation values as the observation results When,
Grouping means for grouping signal observation values output in time series from the observation means;
For each group divided by the grouping means, first positioning means for positioning the positioning object using signal observation values belonging to the group;
The residual of all the signal observation values output from the observation means is calculated using the positioning values of the positioning object by the first positioning means, and the residual for calculating the sum of the residuals of all the signal observation values A difference sum calculating means;
First group updating means for updating a group to which the signal observation value belongs so that the sum of residuals calculated by the residual sum calculating means is minimized;
The residual of the power observation value of the signal at the same observation time as the signal observation value belonging to the group updated by the first group updating means is calculated, and the residual of the signal observation value or the residual power observation value is calculated. A signal observation value exclusion means for excluding the signal observation value from the group when the difference is equal to or greater than a predetermined threshold;
Second positioning means for positioning the positioning object for each group using the signal observation values that remain without being excluded from the group by the signal observation value exclusion means;
Using the positioning values of the positioning object by the second positioning means, the residuals of all signal observation values remaining without being excluded from the group by the signal observation value exclusion means are calculated, and all signal observation values are calculated. of so that the sum of the residual becomes minimum, and a second group update means for updating the group which the signal observed value belongs,
The signal observation value exclusion means uses the positioning value of the positioning object by the first positioning means and the power observation value output from the observation means, from the power of the signal and the observation position to the positioning object for each group. A function indicating the relationship between the distances is calculated, and the difference between the function and the observed power value at each observation time is calculated as the residual of the observed power value.
A positioning device characterized by that . The observation means observes the signal coming from the positioning object in time series, outputs the signal observation value that is the observation result, and also observes the power of the signal and outputs the power observation value that is the observation result Observation processing steps to
A grouping processing step in which the grouping means groups the signal observation values output in time series in the observation processing step;
For each group in which the positioning means is divided in the grouping processing step, a positioning processing step for positioning the positioning object using a signal observation value belonging to the group; and
Of remaining residual sum calculating means using the positioning value of the positioning object in the positioning process step, to calculate the residual of all signal observation value output by the observation processing step, to calculate the sum of the residual Difference sum calculation processing step;
A group update processing step for updating the group to which the signal observation value belongs so that the group update means minimizes the total sum of the residuals calculated in the residual sum calculation processing step ,
In the residual sum calculation processing step, the residual sum calculation means uses the positioning value of the positioning object obtained in the positioning processing step and the power observation value output in the observation processing step, and the signal power for each group. And a function indicating the relationship between the distance from the observation position to the positioning object, and a value obtained by adding the difference between the function and the power observation value at each observation time is calculated as a residual of all power observation values. Calculate the sum of the residuals of the power observations and the residuals of all the above signal observations
A positioning method characterized by that . The observation means observes the signal coming from the positioning object in time series, outputs the signal observation value that is the observation result, and also observes the power of the signal and outputs the power observation value that is the observation result Observation processing steps to
A grouping processing step in which the grouping means groups the signal observation values output in time series in the observation processing step in a round robin,
The positioning means selects an arbitrary group combination from all the group combinations divided by the round robin in the grouping processing step, and for each combination group, the signal observation value belonging to the group is selected. And using the positioning processing step for positioning the positioning object,
Of remaining residual sum calculating means using the positioning value of the positioning object in the positioning process step, to calculate the residual of all signal observation value output by the observation processing step, to calculate the sum of the residual Difference sum calculation processing step;
A group in which the group selection means selects a combination of groups having the smallest residual sum calculated in the residual sum calculation processing step from among all the combinations of the brute force in the grouping processing step. A selection processing step ,
In the residual sum calculation processing step, the residual sum calculation means uses the positioning value of the positioning object obtained in the positioning processing step and the power observation value output in the observation processing step, and the signal power for each group. And a function indicating the relationship between the distance from the observation position to the positioning object, and a value obtained by adding the difference between the function and the power observation value at each observation time is calculated as a residual of all power observation values. Calculate the sum of the residuals of the power observations and the residuals of all the above signal observations
A positioning method characterized by that . The observation means observes the signal coming from the positioning object in time series, outputs the signal observation value that is the observation result, and also observes the power of the signal and outputs the power observation value that is the observation result Observation processing steps to
A grouping processing step in which the first positioning means groups signal observation values output in time series in the observation processing step;
A first positioning processing step of positioning the positioning object using a signal observation value belonging to the group for each group divided by the grouping processing step by the first positioning means;
The residual sum calculation means calculates the residuals of all the signal observation values output in the observation processing step using the positioning values of the positioning object in the first positioning processing step, and all the signal observation values A residual sum calculation processing step for calculating a residual sum of
A first group update processing step for updating a group to which the signal observation value belongs so that the first group update means has a minimum sum of the residuals calculated in the residual sum calculation processing step;
The signal observation value exclusion means calculates a residual of the power observation value of the signal at the same observation time as the signal observation value belonging to the group updated in the first group update processing step, and the residual of the signal observation value Or if the residual of the power observation value is equal to or greater than a predetermined threshold, a signal observation value exclusion processing step of excluding the signal observation value from the group;
A second positioning processing step in which the second positioning means positions the positioning object for each group using the signal observation values remaining without being excluded from the group in the signal observation value exclusion processing step;
The second group updating means uses the positioning value of the positioning object in the second positioning processing step, and the remaining signal observation values remaining without being excluded from the group in the signal observation value exclusion processing step. A second group update processing step of calculating a difference and updating a group to which the signal observation value belongs so that a sum of residuals of all the signal observation values is minimized ,
In the signal observation value exclusion processing step, the signal observation value exclusion means uses the positioning value of the positioning object obtained in the first positioning processing step and the power observation value output in the observation processing step for each group. Obtain a function indicating the relationship between the power of the signal and the distance from the observation position to the positioning object, and calculate the difference between the function and the observed power value at each observation time as the residual of the observed power value
A positioning method characterized by that . In the second group update processing step, the second with the positioning value of the positioning object in the positioning process step, all of the signal observed that remain without being excluded from the group in the signal observed value excluding process step In addition to the residual of the value, calculate the residual of the power observation value of the signal at the same observation time as the above signal observation value, and sum the residual of all the above signal observation values and the residual of all the power observation values The positioning method according to claim 6, wherein the group to which the signal observation value belongs is updated so as to minimize the signal. In the residual sum calculation processing step, the sum of the residuals of all signal observations and the residual of all power observations are calculated as the sum of the residuals of all signal observations and the residuals of all power observations. 6. The positioning method according to claim 4 , wherein a weighted sum with the sum of differences is calculated. In the second group update processing step, the sum of the residuals of all signal observations and the total of the residuals of all signal observations and the total of all power observations The positioning method according to claim 7, wherein a weighted sum with a sum of residuals is calculated. In the above observation processing step, observes the measured angle values of the signal arriving in time series from the positioning object of claim 9 claim 4, characterized in that the output the measured angle value as the signal observed value The positioning method according to any one of the above. In the above observation processing step observes the TOA of the signal arriving in time series from the positioning target, any one of claim 9 claim 4, characterized in that outputs the TOA value as the signal observed value The positioning method according to item 1. In the above observation processing step observes the FOA value of the signal arriving in time series from the positioning target, any one of claim 9 claim 4, characterized in that outputs the FOA value as the signal observed value The positioning method according to item 1. In the above observation processing step observes the TDOA values of the signal arriving in time series from the positioning target, any one of claim 9 claim 4, characterized in that outputs the TDOA value as the signal observed value The positioning method according to item 1. In the above observation processing step, observing FDOA value of the signal arriving in time series from the positioning target, any one of claim 9 claim 4, characterized in that outputs the FDOA value as the signal observed value The positioning method according to item 1.

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