CN106353744B - Multi-parameter combined estimation method based on bistatic FDA-MIMO radars - Google Patents
Multi-parameter combined estimation method based on bistatic FDA-MIMO radars Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/06—Systems determining position data of a target
- G01S13/08—Systems for measuring distance only
- G01S13/10—Systems for measuring distance only using transmission of interrupted, pulse modulated waves
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
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- G01S13/50—Systems of measurement based on relative movement of target
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Abstract
The present invention relates to a kind of multi-parameter combined estimation methods based on bistatic FDA MIMO radars, first with FDA and MIMO radar characteristic design transmitting signal；The docking collection of letters number carries out a matched filtering, vectorization and space smoothing processing；Then estimate joint steering vector and estimation DOA and speed parameter using ESPRIT algorithms and transmitted waveform feature is combined to carry out decoupling and parameter Estimation to DOD and range information；The distance results estimated using ESPRIT algorithms are adjusted the distance in conjunction with impulse time delay estimation and estimate ambiguity solution, and passing through MUSIC algorithms to velocity estimation in conjunction with the signal characteristic under high impulse number carries out ambiguity solution.The present invention can effectively solve the problem that the problem that distance and velocity estimation obscure under single PRF, realize 3 dimension position and speeds estimations of target.Simulation result shows that this method has good estimated accuracy and stability.
Description
Technical Field
The invention belongs to the technical field of multiple-input multiple-output radars, and particularly relates to a bistatic FDA-MIMO radar-based multi-parameter joint estimation method.
Background
The MIMO radar is a novel radar system that transmits a diversity waveform synchronously using a plurality of transmitting antennas, receives an echo signal using a plurality of receiving antennas, and processes the received signal in a concentrated manner. The MIMO radar is largely different from the conventional phased array radar in that the MIMO radar can achieve improvement in degree of freedom by changing an array structure or transmitting an uncorrelated waveform. According to the antenna spatial distribution 'far and near', the MIMO radar is mainly classified into 2 types: centralized MIMO radar and distributed MIMO radar. The distance between the transmitting and receiving antennas of the centralized MIMO radar system is relatively short, and generally cannot reach the distance required by the incoherent MIMO radar. Because each antenna can transmit different signals, the method has good waveform diversity gain, thereby showing good effects in the aspects of parameter identification and estimation capacity improvement, adaptive technology application, flexible waveform design and the like. The antennas of the distributed MIMO radar transceiving array are "far" apart and distributed at spatially different locations. The angles of the respective antennas with respect to the target are significantly different, and thus exhibit good spatial diversity gain. The radar has the advantages that the fluctuation characteristic of the scattering cross section area (RCS) of the target radar in space can be fully utilized, so that the target RCS angular flicker is overcome, and the target detection performance and the parameter estimation precision are improved. The invention mainly takes a bistatic radar in a centralized MIMO radar as an object for research.
The existing methods for solving the contradiction between PRF and range velocity estimation mainly comprise a method of multiple pulse repetition periods or staggered repetition frequency. However, this approach still produces estimation ambiguity. Since the centralized MIMO radar can realize a waveform diversity gain by transmitting different waveforms. Therefore, different from the traditional radar, the MIMO radar can be combined with the FDA technology, and the FDA is utilized to enable the carrier frequency of the transmitted signal to form a frequency increment along with the transmitting array, so that the estimation ambiguity problem is solved by utilizing a single PRF through waveform diversity. However, this method may generate coupling of the DOD and range information on the transmit steering vector, resulting in an inability to estimate the DOD and range information in the case of bistatic MIMO radar. One solution is to divide the transmitting array equally into two sub-arrays, the frequency increment of the two sub-arrays is different; another method is to make the frequency increment in one transmitted pulse be 0 and the frequency increment in the next pulse be different from 0, and transmit alternately, thereby using the signals under different pulses to estimate the angle information and the distance information respectively. The present invention employs a first solution for decoupling. Meanwhile, because the Doppler frequency shift is related to the carrier frequency and the pulse delay number, the influence of the Doppler frequency shift on the emission guide vector can be ignored under the condition that the pulse delay number is small, but can not be ignored under the condition that the pulse delay number is large, the DOD and the distance can be estimated when the pulse delay number is small, and the problem of fuzzy speed estimation is solved when the pulse delay number is large. Meanwhile, for coherent signals, the main methods at present are a spatial smoothing method and a matrix reconstruction method. The former reduces the aperture of the radar; therefore, the estimation precision is reduced, the latter has certain limitation on the estimation of the transmitted signal and the parameter of the radar, and is not as flexible as the former, and the situation of aperture reduction also exists.
Disclosure of Invention
Aiming at the problem of parameter estimation of a bistatic centralized MIMO radar, the invention solves the fuzzy problem of distance estimation and speed estimation under single Pulse Repetition Frequency (PRF) by combining the FDA technology and realizes 3-dimensional positioning of a target.
According to the design scheme provided by the invention, the multi-parameter joint estimation method based on the bistatic FDA-MIMO radar comprises the following steps:
step 1, designing a transmitting signal by utilizing a waveform diversity characteristic, and obtaining a transmitting waveform related to DOD and distance information according to a frequency increment delta f of a carrier wave of the transmitting signal;
step 2, performing matched filtering, vectorization and spatial smoothing on the received transmitting waveform signal to obtain a full-rank signal covariance matrix;
step 3, estimating a joint steering vector by utilizing an ESPRIT algorithm based on the signal covariance matrix;
step 4, estimating DOA and speed parameters by using the joint steering vector, and performing decoupling and parameter estimation on DOD and distance information;
step 5, combining pulse delay estimation to perform deblurring processing on the distance information estimation result;
step 6, combining high pulseNumber LaAnd the lower signal characteristic carries out deblurring processing on the speed parameter estimation result through a MUSIC algorithm.
As described above, step 1 specifically includes the following contents: equally dividing the radar transmitting array into two sub-arrays by taking the center of the array as a reference point, designing the frequency increment of the sub-array 1 to be-delta f, designing the sub-array 2 to be delta f, and obtaining the transmitting guide vector as follows:
wherein, thetapAnd RpRespectively target DOD and DOA, dtFor transmitting the spacing of the antennas, drFor the spacing of the receiving antennas, λ is the signal wavelength, c is the speed of light, v is the target speed, RpIs the sum of the distances from the target to the transmitting end and the receiving end.
The step 2 specifically includes the following contents:
step 201: performing matched filtering processing on a received signal to obtain a signal under the L (L ═ 1, 2., L) th pulse, which is expressed as:
in the formula,in order to receive the steering vector(s),for transmitting steering vectors, aP(v, l) is the target complex scattering coefficient and doppler shift, w (l) is the noise vector;
step 202: the received signal under L pulses is represented as: x ═ X (1), X (2),.., X (l), which is vectorized to obtain a signal:
then the signal covariance matrix is expressed as: rY＝E(YYH) Wherein ⊙ is a Khatri-Rao product, BL×P(v) Is Doppler vector, h is target scattering coefficient;
step 203: the signal is subjected to spatial smoothing processing, and an (l, n) th smoothing matrix is designed as follows:
then, the smoothed signal covariance matrix is:
whereinis the product of Kronecker, l0＝L-pv+1，n0＝N-pr+1, wherein pvAnd prDenotes the number of times of smoothing for spatially smoothing the received steering vector and doppler vector, respectively, H ═ diag (H) ΛT，C0＝Z11C1When p isvprNot less than P and l0n0When the content is more than or equal to P,i.e. a full rank signal covariance matrix, where P is the total number of targets.
As described above, step 3 specifically includes the following contents:
step 301: performing characteristic decomposition on the signal covariance matrix to obtain a signal subspaceDue to span { Es}＝span{C0Is then EsSatisfies Es＝C0T-1；
Step 302: will EsDivided into two subspaces Es1And Es2To obtainWherein, UsAnd T are allThe characteristic vector of,A diagonal matrix containing DOD and speed information;
step 303: computing a joint steering vector of
As mentioned above, the step 4 specifically includes the following contents:
step 401: and estimating DOA and speed by using the joint steering vector, wherein the specific formula is as follows:
step 402: the DOD and the distance are decoupled by using the characteristics of the transmitting signal, and the specific formula is as follows:
step 403: calculating DOD and distance by using a formula, wherein the specific calculation formula is as follows:
as mentioned above, the step 5 specifically includes the following contents: the true distance measured by the radar pulse isIn the formula, kpIs an integer, rut＝c/fPRFThe maximum unambiguous distance is represented and,representing a measured distance; true distance measured using FDA-MIMO radar isIn the formula, qpIs an integer, ruΔfC/4 af denotes the maximum unambiguous distance,representing an estimated distance; then the unambiguous distance can be estimated by:
as described above, step 6 specifically includes the following contents: solving the unambiguous velocity, L, from the relationship between the velocity and the frequency increment at a large number of pulsesaThe received signals under the pulse are:
in the formula, a steering vector is transmitted:
assuming a true velocity ofd is an integer, vu＝c/2f0And T is velocity ambiguity, and a MUSIC algorithm is utilized to solve d:
in the formula, Cv1(La) And Cv2(La) Is a joint steering vector based on two transmit sub-arrays.
The invention has the beneficial effects that:
1. the invention adopts a space smoothing method to ensure the full rank of the signal covariance matrix, and simultaneously carries out space smoothing on the Doppler vector and the receiving guide vector, thereby solving the problem that the velocity estimation and the distance estimation are easy to generate fuzziness under a single pulse repetition period in the prior art and improving the parameter estimation performance.
2. The invention fully utilizes the waveform diversity characteristic of the MIMO radar, combines the MIMO radar with the frequency control array FDA, and enables the emission waveform of the MIMO radar to not only have DOD information but also contain distance information or even speed information, thereby realizing the joint estimation of DOD, DOA, distance and speed, solving the contradiction of speed estimation and distance estimation without fuzzy estimation caused by pulse repetition Period (PRF) in the traditional phased array radar, and improving the performance of parameter estimation; the decoupling of DOD and distance information is realized, so that the joint estimation of the angle and the distance becomes possible, and the problem of fuzzy distance estimation under a single PRF is solved; by utilizing the relation between Doppler frequency shift and carrier frequency, the ambiguity resolution of the speed estimation is realized by utilizing an MUSIC algorithm when the number of pulse time delays is large, so that the effective estimation of 4 parameters of target DOD, DOA, distance and speed is realized, and the three-dimensional coordinate of the target is determined; and the Doppler vector and the receiving guide vector are subjected to smoothing treatment simultaneously by using a space smoothing algorithm, so that the problem of the combination of coherent signals and angles is solved, and the full rank condition of the covariance matrix is ensured.
Description of the drawings:
FIG. 1 is a schematic diagram of a bistatic FDA-MIMO radar system;
FIG. 2 is a schematic flow chart of the present invention;
FIG. 3 is a plot of phase of transmit steering vectors as a function of SNR for the present invention;
FIG. 4 is a graph of RMS error versus SNR for the next 4 parameters of the present invention;
FIG. 5 is a graph showing the variation of the root mean square error of 4 parameters with sampling points according to the present invention;
FIG. 6 is a graph of RMS error versus SNR for 4 parameters under both angle and angle conditions.
The specific implementation mode is as follows:
the present invention will be described in further detail below with reference to the accompanying drawings and technical solutions, and embodiments of the present invention will be described in detail by way of preferred examples, but the embodiments of the present invention are not limited thereto.
In an embodiment, referring to fig. 1 to 2, a method for multi-parameter joint estimation based on bistatic FDA-MIMO radar includes the following steps:
step 1, designing a transmitting signal by utilizing a waveform diversity characteristic, obtaining a transmitting waveform related to DOD and distance information according to a frequency increment delta f of a carrier wave of the transmitting signal, and ensuring that the DOD and the distance information can be decoupled in a parameter estimation process;
step 2, performing matched filtering, vectorization and spatial smoothing on the received transmitting waveform signal to obtain a full-rank signal covariance matrix;
step 3, estimating a joint steering vector by utilizing an ESPRIT algorithm based on the signal covariance matrix;
step 4, estimating DOA and speed parameters by using the joint steering vector, and performing decoupling and parameter estimation on DOD and distance information;
step 5, combining pulse delay estimation to perform deblurring processing on the distance information estimation result;
step 6, combining high pulse number LaAnd the lower signal characteristic carries out deblurring processing on the speed parameter estimation result through a MUSIC algorithm.
The invention adopts a space smoothing method to ensure the full rank of the signal covariance matrix, and simultaneously carries out space smoothing on the Doppler vector and the receiving guide vector, thereby solving the problem that the velocity estimation and the distance estimation are easy to generate fuzziness under a single pulse repetition period in the prior art and improving the parameter estimation performance.
In a second embodiment, referring to fig. 1 to 6, a bistatic FDA-MIMO radar-based multi-parameter joint estimation method includes the following steps:
step 1, designing a transmitting signal based on a bistatic MIMO radar formed by M transmitting array elements and N receiving array elements by using a waveform diversity characteristic, obtaining a transmitting waveform related to DOD and distance information according to a frequency increment delta f of a transmitting signal carrier, equally dividing a radar transmitting array into two sub-arrays by taking an array center as a reference point for solving the problem of DOD and distance information coupling, designing the frequency increment of the sub-array 1 to be delta f and the sub-array 2 to be delta f for calculation convenience, and obtaining a transmitting guide vector as follows:
wherein, thetapAnd RpRespectively target DOD and DOA, dtFor transmitting the spacing of the antennas, drFor the spacing of the receiving antennas, λ is the signal wavelength, c is the speed of light, v is the target speed, RpThe sum of the distances from the target to the transmitting end and the receiving end ensures that the DOD and the distance information can be decoupled in the parameter estimation process.
Step 2, performing matched filtering, vectorization and spatial smoothing on the received transmitting waveform signal to obtain a full-rank signal covariance matrix, which specifically comprises the following contents:
step 201: performing matched filtering processing on a received signal to obtain a signal under the L (L ═ 1, 2., L) th pulse, which is expressed as:
in the formula,in order to receive the steering vector(s),for transmitting steering vectors, aP(v, l) is the target complex scattering coefficient and doppler shift, w (l) is the noise vector;
step 202: the received signal under L pulses is represented as: x ═ X (1), X (2),.., X (l), which is vectorized to obtain a signal:
then the signal covariance matrix is expressed as: rY＝E(YYH) Wherein ⊙ is a Khatri-Rao product, BL×P(v) Is DuolipuA lux vector, h is a target scattering coefficient;
step 203: the signal is subjected to spatial smoothing processing, and in order to avoid the situation of angle coincidence, the (l, n) th smoothing matrix is designed as follows:
then, the smoothed signal covariance matrix is:
whereinis the product of Kronecker, l0＝L-pv+1，n0＝N-pr+1, wherein pvAnd prDenotes the number of times of smoothing for spatially smoothing the received steering vector and doppler vector, respectively, H ═ diag (H) ΛT，C0＝Z11C1When p isvprNot less than P and l0n0When the content is more than or equal to P,i.e. the signal covariance matrix of full rank.
And 3, estimating a joint steering vector by utilizing an ESPRIT algorithm based on the signal covariance matrix according to the rotation non-deformation of the FDA-MIMO radar signal, wherein the method specifically comprises the following contents:
step 301: performing characteristic decomposition on the signal covariance matrix to obtain a signal subspaceSatisfies Es＝C0T-1Wherein, due to span { E }s}＝span{C0Is then EsSatisfies Es＝C0T-1；
Step 302: will EsDivided into two subspaces Es1And Es2To obtainWherein, UsAnd T are allThe characteristic vector of,A diagonal matrix containing DOD and speed information;
step 303: computing a joint steering vector of
And 4, estimating DOA and speed parameters by using the joint steering vector, and performing decoupling and parameter estimation on DOD and distance information, wherein the method specifically comprises the following contents:
step 401: and estimating DOA and speed by using the joint steering vector, wherein the specific formula is as follows:
step 402: the DOD and the distance are decoupled by using the characteristics of the transmitting signal, and the specific formula is as follows:
step 403: calculating DOD and distance by using a formula, wherein the specific calculation formula is as follows:
step 5, combining pulse time delay estimation to carry out deblurring processing on the estimation result of the distance information, and utilizing the real distance measured by the radar pulse asIn the formula, kpIs an integer, rut＝c/fPRFThe maximum unambiguous distance is represented and,representing a measured distance; true distance measured using FDA-MIMO radar isIn the formula, qpIs an integer, ruΔfC/4 af denotes the maximum unambiguous distance,representing an estimated distance; then the unambiguous distance can be estimated by:
step 6, combining high pulse number LaThe lower signal characteristic is used for carrying out fuzzy resolving on the speed parameter estimation result through a MUSIC algorithm, and the non-fuzzy speed, L, is solved according to the relation between the speed and the frequency increment under the large pulse numberaUnder pulse connectionThe received signals are:
in the formula, a steering vector is transmitted:
assuming a true velocity ofd is an integer, vu＝c/2f0And T is velocity ambiguity, and a MUSIC algorithm is utilized to solve d:
in the formula, Cv1(La) And Cv2(La) Is a joint steering vector based on two transmit sub-arrays.
The Cramer-Rao Bound (CRB) for DOA estimation is the lower Bound of unbiased estimation variance theory. According to the signal model of bistatic FDA-MIMO radar, the Cramer-Rao bound CRB of 4 parameters is
Wherein SNR is (E | ξ -2)/(Mσ2) L, M, N denotes the number of pulse delays, the number of transmit antennas and the number of receive antennas, k, respectivelyv＝2πf0T/c，kθ＝2πdtcos(θ)/λ，κR＝2πΔf/c，K represents the number of sampling points.
The effects of the present invention can be further illustrated by the following simulation experiments.
1) Simulation conditions are as follows:
the bistatic FDA-MIMO radar transmitting and receiving array is a uniform linear array, and the parameters are set as follows:
TABLE 1 parameter settings for bistatic FDA-MIMO radars
2) Simulation experiment:
(1) influence of frequency increment on transmission steering vector
The simulation was mainly investigating the effect of frequency increments on the transmit steering vector. The DOD of the target was 20 deg., the distance 1.5km, and the speed 450 m/s. Figure 3 shows the frequency increment versus phase of the transmit steering vector as a function of pulse, and the DOD and distance as a function of the number of pulse delays. From simulation results, it can be found that since the speed is related to both the carrier frequency and the number of pulse delays, but since the magnitude thereof is relatively small, the influence on the transmission steering vector is not large when the number of pulses is small, and the influence is not negligible when the number of pulse delays is large. This can be used to deblur the velocity estimate.
(2) Parameter estimation performance of FDA-MIMO radar
The simulation mainly studies the parameter estimation performance of the FDA-MIMO radar. The first is the estimation performance, i.e. the estimated mean square error versus SNR curve. The number of sampling points is 256, DOD is 30 °, DOA is 35 °, distance is 150km, and speed is 450m/s, where both distance and speed produce estimation ambiguity. From the simulation result of fig. 4, it can be found that, compared with the conventional phased array radar and MIMO radar, the FDA-MIMO radar can achieve joint estimation of 4 parameters, and the distance and speed estimation is unambiguous. Meanwhile, due to the MIMO radar virtual aperture, the estimation precision is improved compared with that of the phased array radar.
Then the variation curve of the mean square error with the number of sampling points. SNR is 0dB, and the target coordinates are unchanged. From the simulation result of fig. 5, it can be found that the estimation accuracy of the radar is continuously improved as the number of sampling points increases.
(3) Angle-resolving and combining performance of FDA-MIMO radar
To verify the performance of the method of the present invention in terms of angle-doubling, we compared the method of the present invention with a method that does not employ spatial smoothing. There were set 2 targets with a combination of angles, DOD of 30 ° and 45 °, DOA of 35 ° and 36 °, distances of 150km and 250km, and speeds of 450m/s and 350 m/s. From the simulation results of fig. 6, it can be found that the method of the present invention can effectively estimate the target with both angle and signal-to-noise ratio even under the condition of low signal-to-noise ratio.
The present invention is not limited to the above-described embodiments, and various changes may be made therein by those skilled in the art, but any changes equivalent or similar to the present invention are intended to be included within the scope of the claims of the present invention.
Claims (3)
1. A multi-parameter joint estimation method based on bistatic FDA-MIMO radar is characterized by comprising the following steps: comprises the following steps:
step 1, designing a transmitting signal by utilizing a waveform diversity characteristic, and obtaining a transmitting waveform related to DOD and distance information according to a frequency increment delta f of a carrier wave of the transmitting signal, wherein the transmitting waveform specifically comprises the following contents: equally dividing the radar transmitting array into two sub-arrays by taking the center of the array as a reference point, designing the frequency increment of the sub-array 1 to be-delta f, designing the sub-array 2 to be delta f, and obtaining the transmitting guide vector of the pth target as follows:wherein, thetapAnd RpRespectively target DOD and DOA, dtFor transmitting the spacing of the antennas, drFor the spacing of the receiving antennas, λ is the signal wavelength, c is the speed of light, v is the target speed, RpThe sum of the distances from the target to the transmitting end and the receiving end;
step 2, performing matched filtering, vectorization and spatial smoothing on the received transmitting waveform signal to obtain a full-rank signal covariance matrix, which specifically comprises the following contents:
step 201: performing matched filtering processing on a received signal to obtain a signal under the L (L ═ 1, 2., L) th pulse, which is expressed as:
in the formula,in order to receive the steering vector(s),for transmitting steering vectors, aP(v, l) is the target complex scattering coefficient and doppler shift, w (l) is the noise vector;
step 202: the received signal under L pulses is represented as: x ═ X (1), X (2),.., X (l), which is vectorized to obtain a signal:
the signal covariance matrix is then expressed as: rY＝E(YYH) Wherein ⊙ is a Khatri-Rao product, BL×P(v) Is Doppler vector, h is target scattering coefficient;
step 203: the signal is subjected to spatial smoothing processing, and an (l, n) th smoothing matrix is designed as follows:
the smoothed signal covariance matrix is then:
wherein,is the product of Kronecker, l0＝L-pv+1，n0＝N-pr+1, wherein pvAnd prDenotes the number of times of smoothing for spatially smoothing the received steering vector and doppler vector, respectively, H ═ diag (H) ΛT，C0＝Z11C1When p isvprNot less than P and l0n0When the content is more than or equal to P,the signal covariance matrix of the full rank is obtained, wherein P is the total number of the targets;
and 3, estimating a joint steering vector by utilizing an ESPRIT algorithm based on the signal covariance matrix, wherein the joint steering vector specifically comprises the following contents:
step 301: performing characteristic decomposition on the signal covariance matrix to obtain a signal subspaceDue to span { Es}＝span{C0Is then EsSatisfies Es＝C0T-1；
Step 302: will EsDivided into two subspaces Es1And Es2To obtainWherein, UsAnd T are allThe characteristic vector of,A diagonal matrix containing DOD and speed information;
step 303: computing a joint steering vector of
And 4, estimating DOA and speed parameters by using the joint steering vector, and performing decoupling and parameter estimation on DOD and distance information, wherein the method specifically comprises the following contents:
step 401: and estimating DOA and speed by using the joint steering vector, wherein the specific formula is as follows:
step 402: the DOD and the distance are decoupled by using the characteristics of the transmitting signal, and the specific formula is as follows:
step 403: calculating DOD and distance by using a formula, wherein the specific calculation formula is as follows:
step 5, combining pulse delay estimation to perform deblurring processing on the distance information estimation result;
step 6, combining high pulse number LaAnd the lower signal characteristic carries out deblurring processing on the speed parameter estimation result through a MUSIC algorithm.
2. The bistatic FDA-MIMO radar-based multi-parameter joint estimation method according to claim 1, wherein: the step 5 specifically comprises the following contents: the true distance measured by the radar pulse isIn the formula, kpIs an integer, rut＝c/fPRFThe maximum unambiguous distance is represented and,representing a measured distance; true distance measured using FDA-MIMO radar isIn the formula, qpIs an integer, ruΔfC/4 af denotes the maximum unambiguous distance,representing an estimated distance; then the unambiguous distance can be estimated by:
3. the bistatic FDA-MIMO radar-based multi-parameter joint estimation method according to claim 2, wherein: the step 6 specifically comprises the following contents: solving the unambiguous velocity, L, from the relationship between the velocity and the frequency increment at a large number of pulsesaThe received signals under the pulse are:
in the formula, a steering vector is transmitted:
assuming a true velocity ofd is an integer, vu＝c/2f0And T is velocity ambiguity, and a MUSIC algorithm is utilized to solve d:
in the formula, Cv1(La) And Cv2(La) Is a joint steering vector based on two transmit sub-arrays.
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| CN106950550B (en) * | 2017-03-31 | 2020-03-03 | 中国人民解放军海军航空大学 | High dynamic deviation on-line estimation method based on cross-fuzzy interval judgment under condition of range finding and speed measuring ambiguity |
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| CN108732545A (en) * | 2018-03-06 | 2018-11-02 | 电子信息系统复杂电磁环境效应国家重点实验室 | The frequency control battle array signal acceptance method and structure of matched filtering are mixed based on multichannel |
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| CN108594233B (en) * | 2018-04-24 | 2020-07-14 | 森思泰克河北科技有限公司 | Speed ambiguity resolving method based on MIMO automobile radar |
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| CN109375213B (en) * | 2018-08-08 | 2023-03-21 | 西安电子科技大学 | Frequency diversity array signal processing method based on subarray division |
| CN109085541B (en) * | 2018-09-07 | 2021-02-02 | 杭州捍鹰科技有限公司 | MIMO radar array antenna and signal processing method thereof |
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| CN110146871B (en) * | 2019-05-21 | 2022-11-04 | 西安电子科技大学 | Target parameter estimation method based on double-frequency offset FDA-MIMO radar |
| CN110320489B (en) * | 2019-06-26 | 2022-02-08 | 中国电子科技集团公司第三十八研究所 | Measurement method and system for distributed isomorphic area array joint angle estimation precision |
| CN110346764B (en) * | 2019-08-21 | 2022-03-29 | 上海无线电设备研究所 | MIMO radar target distance angle decoupling method |
| CN110554361B (en) * | 2019-09-04 | 2023-11-03 | 南京慧尔视智能科技有限公司 | Method for designing transmitting waveform parameters under MIMO system |
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| CN105717496B (en) * | 2016-01-30 | 2017-11-10 | 湖北工业大学 | A kind of implementation method of the frequency control battle array MIMO radar system based on matrix fill-in |
| CN105699945B (en) * | 2016-01-30 | 2017-12-26 | 湖北工业大学 | Waveform optimization design method in frequency control battle array MIMO radar system |
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