Target localization method based on multi-transmission and multi-reception passive multistatic radar under interference environment

Abstract

This invention discloses a target localization method for multiple-transmitter, multiple-receiver passive multistatic radar under interference conditions. The method includes: acquiring reference channel signals and echo signals and performing signal characterization preprocessing to obtain reference channel signal matrices and echo signal matrices; estimating channel parameters based on the reference channel signal matrices and echo signal matrices using the generalized likelihood ratio principle to construct a DPI-GRLT detector; solving the DPI-GRLT detector and calculating the detection statistics at each grid point to obtain the radar target information estimation result. This invention can maintain high localization accuracy and achieve rapid estimation and resolution of multiple targets even under weak signal conditions. As a target localization method for multiple-transmitter, multiple-receiver passive multistatic radar under interference conditions, this invention can be widely applied in the field of radar target localization technology.

Description

Technical Field

[0001] This invention relates to the field of radar target localization technology, and in particular to a method for localizing targets using multi-transmitter, multi-receiver passive multistatic radar under interference conditions. Background Technology

[0002] With the rapid development of modern electronic countermeasures technology and the increasing scarcity of spectrum resources, passive multistatic radar (PMR) systems, with their unique "passive detection" characteristics, are becoming an important component of the next generation of intelligent sensing systems. These systems innovatively utilize existing non-cooperative radiation sources in the environment (such as digital television signals and navigation satellite signals) as detection carriers, achieving not only complete electromagnetic silence but also significantly improving spectrum utilization efficiency. Of particular note is that modern PMR systems, by introducing a MIMO (Multiple-Input Multiple-Output) architecture, enable the system to acquire richer spatial-temporal-frequency multidimensional signal features while maintaining stealth, providing a completely new information dimension for target detection and localization.

[0003] However, handling direct-path interference is a major challenge. Since the DPI (Direct Impact Point) is typically tens of decibels higher than the target echo power, neglecting the impact of DPI during the design phase will significantly degrade the performance of GLRT detectors. Currently, two main solutions have been developed for the DPI problem. The first is multi-domain filtering technology. While multi-domain filtering can achieve a certain degree of DPI suppression, noise pollution and multipath interference in the reference channel signal result in residual interference in the monitoring channel after clutter suppression. This residual clutter significantly reduces the system's target detection performance and affects positioning accuracy. The second is joint processing methods. While existing joint processing methods can simultaneously suppress interference and locate the target, they still have shortcomings: firstly, they ignore the target Doppler effect, affecting moving target detection performance; secondly, they do not consider the multi-input multi-output characteristics of MIMO-PMR systems, making it difficult to handle complex signal environments. Summary of the Invention

[0004] To address the aforementioned technical problems, the present invention aims to provide a target localization method for multiple-transmitter, multiple-receiver passive multistatic radar under interference conditions, which can maintain high localization accuracy and achieve rapid estimation and resolution of multiple targets even under weak signal conditions.

[0005] The first technical solution adopted in this invention is: a target localization method based on multi-transmitter, multi-receiver passive multistatic radar under interference conditions, comprising the following steps:

[0006] The reference channel signal and echo signal are acquired and preprocessed to obtain the reference channel signal matrix and echo signal matrix.

[0007] Channel parameters are estimated based on the reference channel signal matrix and the echo signal matrix combined with the generalized likelihood ratio principle, and a DPI-GRLT detector is constructed.

[0008] The DPI-GRLT detector is solved, and the detection statistics at each grid point are calculated to obtain the radar target information estimation results.

[0009] Furthermore, the step of acquiring the reference channel signal and echo signal and performing signal characterization preprocessing to obtain the reference channel signal matrix and echo signal matrix specifically includes:

[0010] The signals from the non-cooperative opportunity source received by the receiver's reference channel and detection channel are respectively denoted as the reference channel signal and the echo signal. The non-cooperative opportunity source signal includes the channel factor of the direct wave signal in the reference channel, the channel factor of the direct wave signal in the detection channel, and the channel factor of the target echo.

[0011] By using a uniform sampling rate to discretely sample the reference channel signal and the echo signal, a unified discrete reference channel signal sample and a unified discrete echo signal sample are constructed.

[0012] The unified discrete reference channel signal samples and the unified discrete echo signal samples are represented by signal matrix to obtain the reference channel signal matrix and the echo signal matrix.

[0013] Furthermore, the expression for the reference channel signal matrix is ​​as follows:

[0014]

[0015] In the above formula, r mn Represents the reference channel signal matrix, α mn μ represents the channel factor of the direct wave signal in the reference channel. m Denotes the complex envelope of the m-th non-cooperative opportunity source. The reference channel noise is represented by n, which represents the nth receiver. Represents the distance-Doppler matrix. The sampled value represents the direct wave delay;

[0016] The specific expression for the echo signal matrix is ​​as follows:

[0017]

[0018] In the above formula, e mn Represents the echo signal matrix, β mn γ represents the direct-wave channel factor of the detection channel. mn f represents the target echo channel factor. mn Indicates Doppler, This indicates the noise level in the detection channel.

[0019] Furthermore, the step of estimating channel parameters based on the reference channel signal matrix and the echo signal matrix using the generalized likelihood ratio principle, and constructing the DPI-GRLT detector, specifically includes:

[0020] Based on the reference channel signal matrix and the echo signal matrix combined with the generalized likelihood ratio principle, a detection statistic is constructed, and the conditional probability density of the target's existence and the conditional probability density of the target's non-existence are defined.

[0021] Channel parameters are estimated based on the conditional probability density of the target's presence and the conditional probability density of the target's absence, resulting in the maximum likelihood estimate of the signal factor under the condition that the target exists and the maximum likelihood estimate of the signal factor under the condition that the target does not exist.

[0022] The maximum likelihood estimates of the signal factors under the condition that the target exists and the maximum likelihood estimates of the signal factors under the condition that the target does not exist are substituted into the detection statistic and the logarithm of both sides of the equation is taken to construct the DPI-GRLT detector.

[0023] Furthermore, the expression for the detection statistic is as follows:

[0024]

[0025] In the above formula, Λ represents the detection statistic, and α mn β represents the channel factor of the direct wave signal in the reference channel. mn γ represents the direct-wave channel factor of the detection channel. mn μ represents the target echo channel factor. m Let f1 represent the conditional probability density when the target exists, f0 represent the conditional probability density when the target does not exist, H1 represent the target exists, H0 represent the target does not exist, θ represent the target parameter to be estimated, and N represent the target parameters to be estimated. T N represents the number of non-cooperative opportunity source sites. R Indicates the number of receiving stations, s mn denoted as the received signal vector, α as the estimated direct wave channel factor of the reference channel, β as the estimated direct wave channel factor of the monitoring channel, γ as the estimated target echo channel factor of the monitoring channel, and μ as the estimated transmitted waveform.

[0026] Furthermore, the expression for the DPI-GRLT detector is as follows:

[0027]

[0028] In the above formula, ln(Λ) represents the DPI-GRLT detector, u mDenotes the complex envelope of the m-th non-cooperative opportunity source. This represents the time delay-Doppler compensation matrix under the H1 assumption. Let N represent the time delay-Doppler compensation matrix under the H0 assumption. T σ represents the number of non-cooperative opportunity source sites, σ represents the noise variance, and m represents the non-cooperative opportunity source index.

[0029] Furthermore, the step of solving the DPI-GRLT detector, calculating the detection statistics at each grid point, and obtaining the radar target information estimation result specifically includes:

[0030] Based on the properties of the Rayleigh quotient, the signal from the non-cooperative opportunity source is estimated to obtain the maximum likelihood estimate of the transmitted waveform under the condition that the target exists and the maximum likelihood estimate of the transmitted waveform under the condition that the target does not exist.

[0031] The maximum likelihood estimate of the transmitted waveform under the condition that the target exists and the maximum likelihood estimate of the transmitted waveform under the condition that the target does not exist are substituted into the DPI-GRLT detector for solution to obtain the detection statistic;

[0032] The search space grid points are traversed, the detection statistics at each grid point are calculated, and the grid point with the largest detection statistics is selected to obtain the radar target information estimation result.

[0033] Furthermore, the specific expression for solving the DPI-GRLT detector is as follows:

[0034]

[0035] In the above formula, ln(Λ) represents the DPI-GRLT detector, λ 1,max Let λ be the largest eigenvalue of the matrix under the H1 hypothesis. 0,max Let m be the largest eigenvalue of the matrix under the H0 assumption, and m represent the index.

[0036] The beneficial effects of the method of this invention are as follows: This invention obtains the reference channel signal matrix and the echo signal matrix by acquiring the reference channel signal and the echo signal and performing signal characterization preprocessing. It also considers the amplitude and phase information of the echo signal, making it a fully coherent positioning method. Compared with traditional methods, this method can still maintain high positioning accuracy under weak signal conditions. Furthermore, based on the reference channel signal matrix and the echo signal matrix, channel parameters are estimated using the generalized likelihood ratio principle to construct a DPI-GRLT detector. This effectively utilizes the spatial diversity gain of the distributed array and is suitable for target positioning scenarios in complex electromagnetic environments. Finally, the DPI-GRLT detector is solved, and the detection statistics at each grid point are calculated to obtain the radar target information estimation results. Based on a preset detection threshold, the test statistics are filtered to achieve rapid estimation and resolution of multiple targets. Attached Figure Description

[0037] Figure 1 This is a flowchart of the steps of the present invention for a target localization method based on a multi-transmitter, multi-receiver passive multi-static radar under interference conditions;

[0038] Figure 2 This is a schematic diagram of a MIMO-PMR positioning scenario provided in a specific embodiment of the present invention;

[0039] Figure 3 This is a schematic diagram of the radar target localization process provided in a specific embodiment of the present invention;

[0040] Figure 4 This is a schematic diagram showing the comparison of the positioning performance of the algorithm provided in a specific embodiment of the present invention with that of a control case;

[0041] Figure 5 This is a schematic diagram of the positioning performance test results under high interference environment provided by a specific embodiment of the present invention. Detailed Implementation

[0042] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments. The step numbers in the following embodiments are only for ease of explanation and do not limit the order of the steps. The execution order of each step in the embodiments can be adapted according to the understanding of those skilled in the art.

[0043] In the research of localization methods, current technical approaches mainly fall into two branches: indirect localization based on parameter measurement and direct localization based on signal processing. The former extracts multi-dimensional observations such as time difference of arrival (TDOA) and frequency difference of arrival (FDOA) and obtains target position estimates through geometric analysis, possessing advantages such as mature algorithms and simple implementation. The latter breaks through the constraints of the traditional measurement-solution framework, directly constructing a localization optimization problem at the signal level and achieving target localization through joint estimation of multi-dimensional parameters. Theoretical research shows that direct localization methods, by avoiding information loss in intermediate measurement stages, can achieve localization accuracy close to the Cramer-Rao lower bound under low signal-to-noise ratio conditions. However, handling direct wave interference is a major challenge. Since the DPI is usually several tens of decibels higher than the target echo power, failing to consider the impact of DPI during the design phase will significantly reduce the performance of the GLRT detector.

[0044] Based on this, this invention proposes a direct target localization method for multiple-input multiple-receiver passive multistatic radar (MIMO-PMR) under direct-input interference (DPI) conditions. First, signal models for the reference and monitoring channels under DPI interference conditions are established, and the received signals are characterized using a matrix method. Then, a generalized likelihood ratio (GRLT) detector is constructed, and the test statistic for each grid point is calculated by traversing the possible spatial positions and velocities of the target. Finally, the grid point parameters that maximize the test statistic are selected as the final estimation results for the target's position and motion parameters, achieving accurate estimation of the target's position and velocity information.

[0045] Reference Figure 1 This invention provides a target localization method for multi-transmitter, multi-receiver passive multistatic radar under interference conditions, the method comprising the following steps:

[0046] S100: Acquire the reference channel signal and echo signal and perform signal characterization preprocessing to obtain the reference channel signal matrix and echo signal matrix;

[0047] S110. The signals of the non-cooperative opportunity source received by the reference channel and the detection channel of the receiver are respectively denoted as the reference channel signal and the echo signal. The signal of the non-cooperative opportunity source includes the channel factor of the direct wave signal in the reference channel, the channel factor of the direct wave in the detection channel, and the channel factor of the target echo.

[0048] In this embodiment, reference signal and echo signal models are established. The signals received by the nth receiver reference channel and detection channel from the mth non-cooperative opportunity source are defined as r, respectively. mn (t) and e mn (t), whose mathematical model is expressed as:

[0049]

[0050] Where T represents the accumulation time, α mn The channel factor and β of the direct wave signal in the reference channel are represented. mn and γ mn These represent the direct wave channel factor of the detection channel and the target echo channel factor, respectively. m (t) represents the complex envelope of the m-th non-cooperative opportunity source, where the emission sources are uncorrelated. and These are the reference channel noise and the detection channel noise, respectively. Since the receivers have similar performance, the noise in each monitoring channel is independent and identically distributed. It is assumed that the noise in each channel follows a law with a mean of zero and a variance of σ. 2 It follows a normal distribution. τ mn and f mn Let these represent the direct wave delay, target delay, and Doppler effect, respectively, calculated as follows:

[0051]

[0052] in, and Represent the positions of the nth receiver and the mth non-cooperative light source, respectively, P = [x, y, z] ∈ R 3 and These represent the target's position and velocity, respectively.

[0053] S120. Discretely sample the reference channel signal and the echo signal using a uniform sampling rate to construct a uniform discrete reference channel signal sample and a uniform discrete echo signal sample.

[0054] In this embodiment, the signal is discretized. Using a sampling rate f... s The signals from the reference channel and the monitoring channel are sampled, and the number of sampling points is set to N. s =f s The discretized signal, *T, is represented as follows:

[0055]

[0056] In the above formula, N s Indicates the number of sampling points.

[0057] S130. The unified discrete reference channel signal samples and the unified discrete echo signal samples are represented by signal matrix to obtain the reference channel signal matrix and the echo signal matrix.

[0058] In this embodiment, the sampled signal is represented as a matrix:

[0059]

[0060] in The time-delay Doppler matrix is ​​defined as follows:

[0061]

[0062] in It is the Fourier transform matrix, and the elements of this matrix are represented as... [·] g,h This represents the element in the g-th row and h-th column of the matrix. It is a complex diagonal matrix.

[0063] S200. Based on the reference channel signal matrix and the echo signal matrix combined with the generalized likelihood ratio principle, channel parameters are estimated, and a DPI-GRLT detector is constructed.

[0064] S210. Based on the reference channel signal matrix and the echo signal matrix combined with the generalized likelihood ratio principle, a detection statistic is constructed, and the conditional probability density of the target's existence and the conditional probability density of the target's non-existence are defined.

[0065] In this embodiment, based on the generalized likelihood ratio principle, the following detection statistic is constructed:

[0066]

[0067] in f1 and f0 represent the conditional probability densities when the target exists (H1) and does not exist (H0), respectively, and are defined as follows:

[0068]

[0069] in This is the normalization constant.

[0070] S220. Based on the conditional probability density of the target's existence and the conditional probability density of the target's non-existence, channel parameters are estimated to obtain the maximum likelihood estimate of the signal factor under the condition that the target exists and the maximum likelihood estimate of the signal factor under the condition that the target does not exist.

[0071] In this embodiment, channel parameter estimation is performed. Taking the logarithm of both sides of the expression for the conditional probability density when the target exists (H1) and does not exist (H0), we obtain:

[0072]

[0073] Under the H1 assumption, α1, β1, γ mn The maximum likelihood estimates are as follows:

[0074]

[0075] in diag(A) represents taking the elements on the diagonal of the matrix. This means concatenating matrices A and B into a diagonal matrix, with A at the top left corner and B at the bottom left corner, and the resulting matrix has a size of (m1+m2)×(n1+n2), and so on.

[0076] Under the assumption of H0, α mn β mn The maximum likelihood estimates are as follows:

[0077]

[0078] in

[0079] S230. Substitute the maximum likelihood estimates of the signal factors under the condition that the target exists and the maximum likelihood estimates of the signal factors under the condition that the target does not exist into the detection statistic and take the logarithm of both sides of the equation to construct the DPI-GRLT detector.

[0080] In this embodiment, the DPI-GRLT detector is derived. Substituting the maximum likelihood estimates of the signal factors under the condition that the target is present and under the condition that the target is absent into the detection statistic and taking the logarithm of both sides of the equation, we obtain:

[0081]

[0082] in:

[0083]

[0084] In the above formula, ln(Λ) represents the DPI-GRLT detector, u m Denotes the complex envelope of the m-th non-cooperative opportunity source. This represents the time delay-Doppler compensation matrix under the H1 assumption. Let σ represent the time delay-Doppler compensation matrix under the H0 assumption, σ represent the noise variance, and m represent the non-cooperative opportunity source index. This represents the transpose of the corresponding matrix.

[0085] S300: Solve the DPI-GRLT detector, calculate the detection statistics at each grid point, and obtain the radar target information estimation results.

[0086] S310. Based on the properties of Rayleigh quotient, the non-cooperative opportunity source signal is estimated to obtain the maximum likelihood estimate of the transmitted waveform under the condition that the target exists and the maximum likelihood estimate of the transmitted waveform under the condition that the target does not exist.

[0087] In this embodiment, under the H1 assumption, according to the property of Rayleigh quotient, the maximum value of the fractional terms after taking the logarithm of both sides is the matrix. The largest eigenvalue, u m The eigenvector corresponding to the largest eigenvalue is given by the equation, which is: The waveform of the non-cooperative opportunity source signal can be estimated using the following formula:

[0088]

[0089] Where v max Let represent the eigenvector corresponding to the largest eigenvalue of matrix A. Similarly, the estimate under the H0 assumption is:

[0090]

[0091] In the above formula, This represents the maximum likelihood estimate of the transmitted waveform given the presence of the target. This represents the maximum likelihood estimate of the transmitted waveform under the condition that the target does not exist.

[0092] S320. Substitute the maximum likelihood estimate of the transmitted waveform under the condition that the target exists and the maximum likelihood estimate of the transmitted waveform under the condition that the target does not exist into the DPI-GRLT detector to solve for the detection statistic.

[0093] In this embodiment, the DPI-GRLT detector is used for solving. Substituting the maximum likelihood estimates of the transmitted waveform under the condition of target presence and the maximum likelihood estimates of the transmitted waveform under the condition of target absence into the expression after taking the logarithm of both sides, we obtain:

[0094]

[0095] λ 1,max Let be the matrix representation of the largest eigenvalue of matrix A. Define the detection statistic: χ = ln(Λ).

[0096] S330. Traverse the grid points in the search space, calculate the detection statistics for each grid point, select the grid point with the largest detection statistics, and obtain the radar target information estimation result.

[0097] In this embodiment, target parameters are estimated. The search space grid points are traversed, and the test statistic for each grid point is calculated. The target position and velocity information can be estimated using the following expression:

[0098]

[0099] The spatial grid points include position grid points and velocity grid points.

[0100] Therefore, as Figure 2 as well as Figure 3 As shown in the figure, this invention proposes a direct target localization method for multiple-input multiple-receiver passive multistatic radar (MIMO-PMR) under direct-wave (DPI) interference conditions. First, signal models of the reference channel and monitoring channel under DPI interference conditions are established, and the received signals are characterized using a matrix method. Based on this, a generalized likelihood ratio (GRLT) detector is constructed. By traversing the grid points of possible target spatial positions and velocities, the test statistics of each grid point are calculated. The grid point parameters that maximize the test statistics are selected as the final estimation results of the target position and motion parameters, achieving accurate estimation of target position and velocity information. This method effectively solves the target localization problem under DPI interference conditions and improves the localization performance of passive multistatic radar systems.

[0101] In summary, the embodiments of the present invention have the following advantages over the prior art:

[0102] 1) The method proposed in this embodiment of the invention takes into account both the amplitude and phase information of the echo signal, and is a fully coherent positioning method. Compared with traditional methods, this method can still maintain high positioning accuracy under weak signal conditions.

[0103] 2) In this embodiment of the invention, a dedicated signal processing framework is designed for the characteristics of MIMO-PMR systems. It can effectively utilize the spatial diversity gain of the distributed array and is suitable for target positioning scenarios in complex electromagnetic environments.

[0104] 3) This embodiment of the invention employs a linear processing architecture, which is also suitable for multi-target localization scenarios. By filtering the test statistics based on a preset detection threshold, rapid estimation and differentiation of multiple targets can be achieved.

[0105] Finally, the embodiments of the present invention will be described in conjunction with the accompanying drawings:

[0106] Table 1 shows the key simulation parameters of this experiment. To verify the effectiveness of the invention, a receiver ignoring the DPI parameter was selected as a control case (i.e., the direct wave interference term r was ignored). mn Only considering ).

[0107] Table 1 Key simulation parameters of this experiment

[0108]

[0109]

[0110] The definitions of SNR, DNR, and ISR in the table are as follows:

[0111]

[0112] Figure 4 The results show a comparison of the positioning performance of the algorithm of this invention with those of a control case. Figure 4 (a) shows the complete localization result of the algorithm of the present invention in three-dimensional space; Figure 4 (b) in the middle is Figure 4 (a) is the two-dimensional sectional projection of the plane at height Z = 2 km; Figure 4 (c) shows the localization results of the control case with the DPI parameter ignored; its corresponding Z=2km section is as follows Figure 4 As shown in (d) in the figure, it can be clearly observed that the target position estimate (red marker) and the actual target position (black cross marker) in the localization result of the proposed algorithm are highly consistent, achieving accurate target localization.

[0113] While keeping the original simulation parameters of Experiment 1 unchanged, the interference signal ratio (ISR) was increased to 35dB to verify the robustness of the algorithm. Figure 5 The results of positioning performance tests in high-interference environments are presented. Figure 5 (a) in the figure represents the complete localization result of the algorithm of the present invention in three-dimensional space. Figure 5 (b) in the middle is Figure 5 (a) is the two-dimensional sectional projection on the Z = 2km height plane. Experimental results show that the proposed algorithm can still maintain high positioning accuracy under strong interference conditions of ISR = 35dB.

[0114] The above is a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the embodiments described. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of this application.

Claims

1. A target localization method based on multi-transmitter, multi-receiver passive multistatic radar under interference conditions, characterized in that, Includes the following steps: The reference channel signal and echo signal are acquired and preprocessed to obtain the reference channel signal matrix and echo signal matrix. Based on the reference channel signal matrix and the echo signal matrix combined with the generalized likelihood ratio principle, a detection statistic is constructed, and the conditional probability density of the target's existence and the conditional probability density of the target's non-existence are defined. Channel parameters are estimated based on the conditional probability density of the target's presence and the conditional probability density of the target's absence, resulting in the maximum likelihood estimate of the signal factor under the condition that the target exists and the maximum likelihood estimate of the signal factor under the condition that the target does not exist. Substitute the maximum likelihood estimates of the signal factors under the condition that the target exists and the maximum likelihood estimates of the signal factors under the condition that the target does not exist into the detection statistic and take the logarithm of both sides of the equation to construct the DPI-GRLT detector. The specific expression for the DPI-GRLT detector is as follows: ； In the above formula, This indicates a DPI-GRLT detector. Indicates the first A complex envelope of non-cooperative opportunity sources, express Assuming the time delay-Doppler compensation matrix, express Assuming the time delay-Doppler compensation matrix, Indicates the number of non-cooperative opportunity source sites. Indicates the noise variance. Indicates a source index for non-cooperative opportunities; The DPI-GRLT detector is solved, and the detection statistics at each grid point are calculated to obtain the radar target information estimation results.

2. The target localization method for multiple-transmitter, multiple-receiver passive multi-static radar under interference environment as described in claim 1, characterized in that, The step of acquiring the reference channel signal and echo signal and performing signal characterization preprocessing to obtain the reference channel signal matrix and echo signal matrix specifically includes: The signals from the non-cooperative opportunity source received by the receiver's reference channel and detection channel are respectively denoted as the reference channel signal and the echo signal. The non-cooperative opportunity source signal includes the channel factor of the direct wave signal in the reference channel, the channel factor of the direct wave signal in the detection channel, and the channel factor of the target echo. By using a uniform sampling rate to discretely sample the reference channel signal and the echo signal, a unified discrete reference channel signal sample and a unified discrete echo signal sample are constructed. The unified discrete reference channel signal samples and the unified discrete echo signal samples are represented by signal matrix to obtain the reference channel signal matrix and the echo signal matrix.

3. The target localization method for multiple-transmitter, multiple-receiver passive multi-static radar under interference environment according to claim 2, characterized in that, The specific expression for the reference channel signal matrix is ​​as follows: ； In the above formula, Represents the reference channel signal matrix. This represents the channel factor of the direct wave signal in the reference channel. Indicates the first A complex envelope of non-cooperative opportunity sources, Indicates the reference channel noise. Indicates the first One receiver, Represents the distance-Doppler matrix. The sampled value represents the direct wave delay; The specific expression for the echo signal matrix is ​​as follows: ； In the above formula, Represents the echo signal matrix. Indicates the direct-wave channel factor of the detection channel. Indicates the target echo channel factor. Indicates Doppler, This indicates the noise level in the detection channel.

4. The target localization method for multi-transmitter, multi-receiver passive multi-static radar under interference environment as described in claim 3, characterized in that, The specific expression for the detection statistic is as follows: ； In the above formula, This represents the detection statistics. This represents the channel factor of the direct wave signal in the reference channel. Indicates the direct-wave channel factor of the detection channel. Indicates the target echo channel factor. Indicates the first A complex envelope of non-cooperative opportunity sources, This represents the conditional probability density when the target exists. This represents the conditional probability density when the target does not exist. This indicates that the target exists. This indicates that the target does not exist. Indicates the target parameter to be estimated. Indicates the number of non-cooperative opportunity source sites. Indicates the number of receiving stations. Represents the received signal vector. This represents the direct wave channel factor to be estimated in the reference channel. This indicates the direct wave channel factor to be estimated in the monitoring channel. This indicates the target echo channel factor to be estimated in the monitoring channel. This indicates the transmitted waveform to be estimated.

5. The target localization method for multiple-transmitter, multiple-receiver passive multi-static radar under interference environment according to claim 4, characterized in that, The step of solving the DPI-GRLT detector, calculating the detection statistics at each grid point, and obtaining the radar target information estimation result specifically includes: Based on the properties of the Rayleigh quotient, the signal from the non-cooperative opportunity source is estimated to obtain the maximum likelihood estimate of the transmitted waveform under the condition that the target exists and the maximum likelihood estimate of the transmitted waveform under the condition that the target does not exist. The maximum likelihood estimate of the transmitted waveform under the condition that the target exists and the maximum likelihood estimate of the transmitted waveform under the condition that the target does not exist are substituted into the DPI-GRLT detector for solution to obtain the detection statistic; The search space grid points are traversed, the detection statistics at each grid point are calculated, and the grid point with the largest detection statistics is selected to obtain the radar target information estimation result.

6. The target localization method for multiple-transmitter, multiple-receiver passive multi-static radar under interference environment as described in claim 5, characterized in that, The specific expression for solving the DPI-GRLT detector is as follows: ； In the above formula, This indicates a DPI-GRLT detector. Let H1 be the largest eigenvalue of the matrix. for Assume the largest eigenvalue of the following matrix, Indicates an index.

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