A distributed target detection method under a zero direct wave system

Abstract

The present invention relates to a distributed target detection method under a zero direct wave system, which includes: obtaining echo signals received by multiple receiving stations, sequentially performing cross-ambiguity processing on each slave station echo signal and the master station echo signal to obtain the cross-ambiguity function value corresponding to the slave station; comparing the cross-ambiguity function value with a preset first threshold value. If there is a cross-ambiguity function value exceeding the first threshold value, record the time delay corresponding to the cross-ambiguity function value, perform correction using the time delay, and perform target detection using the corrected signal. If not, construct a multi-channel time delay estimation scheme set, calculate the decision parameter corresponding to each estimation scheme, and select the estimation scheme corresponding to the maximum decision parameter as the final time delay scheme; perform correction according to the final time delay scheme, and perform target detection using the corrected signal. The present invention solves the problem that traditional target detection requires direct waves, and multiple receiving stations work together, improving the reliability.

Description

Technical Field

[0001] The present invention belongs to the technical field of radar target detection, and particularly relates to a distributed target detection method under a zero direct wave regime. Background Art

[0002] Currently, the research on target detection of external radiation source radars mainly focuses on the condition of having direct waves. However, a multi-base external radiation source radar system consists of a third-party illumination source and receiving base stations distributed at different geographical locations. Due to the earth's curvature, each receiving base station cannot receive direct waves and can only receive the echoes reflected from the target of interest respectively. Traditional target detection methods are no longer applicable.

[0003] GLRT (Generalized Likelihood Ratio Test) detection is a main method for parametric signal statistical testing. The essence of the GLRT principle is to search for the maximization of the likelihood ratio in the unknown parameter interval, that is, to use the maximum likelihood estimate of the unknown parameter to replace the unknown parameter, and then obtain the GLRT detection statistic, thus transforming the problem into a statistical test of a known signal.

[0004] J. Liu et al. proposed a generalized likelihood ratio test (GLRT) detector to handle passive detection problems in the literature "Two Target Detection Algorithms for Passive Multistatic Radar, in IEEE Transactions on Signal Processing, vol. 62, no. 22, pp. 5930 - 5939, Nov. 15, 2014". Zhao Hongyan proposed a target detection method in the literature "Research on Target Detection Algorithms for Passive Multi-Base Radars [D]. Xidian University, 2017", which independently configures a reference channel to receive the signal emitted by a third-party opportunistic source as a reference signal and conducts target detection according to the two-step GLRT principle.

[0005] The above target detection methods all require direct wave information, need an additional independent channel as a reference channel to collect the transmitted signal radiated by the opportunistic source as a reference for target detection, and have a low detection probability when the number of receiving stations is small. Summary of the Invention

[0006] In order to solve the above problems existing in the prior art, the present invention provides a distributed target detection method under a zero direct wave regime. The technical problems to be solved by the present invention are realized through the following technical solutions:

[0007] The present invention provides a distributed target detection method under a zero direct wave regime, including:

[0008] Step 1: Obtain the echo signals received by multiple receiving stations, where the multiple receiving stations include a master station and multiple slave stations;

[0009] Step 2: Perform cross-ambiguity processing on each slave station echo signal and the master station echo signal in sequence to obtain the cross-ambiguity function values corresponding to the slave stations;

[0010] Step 3: Compare the cross-ambiguity function values with a preset first threshold value. If there are cross-ambiguity function values exceeding the first threshold value, record the time delay corresponding to the cross-ambiguity function value, use the time delay to correct the corresponding slave station echo signal, and perform target detection according to the correction result. If there are no cross-ambiguity function values exceeding the first threshold value, execute Step 4;

[0011] Step 4: Set the time difference search range. According to the time difference search range, design multiple time delay schemes for each slave station, and construct a multi-channel time delay estimation scheme set according to the multiple time delay schemes of the slave stations;

[0012] Step 5: According to the multi-channel time delay estimation scheme set, obtain the receiving station echo data matrix corresponding to each estimation scheme, calculate the corresponding decision parameter according to the receiving station echo data matrix, and select the estimation scheme corresponding to the maximum decision parameter as the final time delay scheme;

[0013] Step 6: Correct the echo signal according to the final time delay scheme, and perform target detection according to the correction result.

[0014] In an embodiment of the present invention, Step 2 includes:

[0015] Perform cross-ambiguity processing on each slave station echo signal and the master station echo signal in sequence using the ambiguity function to obtain the cross-ambiguity function values corresponding to the slave stations, where the ambiguity function is:

[0016]

[0017] In the formula, r1(n) represents the master station echo signal, x i (n) represents the echo signal of the i-th slave station, L represents the length of the signal, n τ represents the time delay, n f represents the Doppler frequency shift, x i * represents the conjugate of x i and K represents the number of receiving stations.

[0018] In an embodiment of the present invention, in Step 3, using the time delay to correct the corresponding slave station echo signal and performing target detection according to the correction result includes:

[0019] Step a: Correct the corresponding slave - station echo signal by using the time delay to obtain the corrected slave - station echo signal;

[0020] Step b: Arrange the corrected slave - station echo signals in chronological order to obtain the corresponding slave - station echo data matrix;

[0021] Step c: Calculate the new matrix \(X'\) according to the slave - station echo data matrix, obtain the eigenvalue matrix of the new matrix \(X'\), and calculate the characteristic parameter according to the eigenvalue matrix;

[0022] where \(X' = X\) H \(X\), \(X\) represents the slave - station echo data matrix, \(X\) H represents the conjugate transpose of \(X\); \(A = p / sum\), \(A\) represents the characteristic parameter, \(p\) represents the maximum eigenvalue in the eigenvalue matrix, and \(sum\) represents the sum of all eigenvalues in the eigenvalue matrix;

[0023] Step d: Compare the characteristic parameter with a preset second threshold value. When the characteristic parameter is greater than the second threshold value, it is determined that there is a target. When the characteristic parameter is less than the second threshold value, it is determined that there is no target.

[0024] In an embodiment of the present invention, step 4 includes:

[0025] Step 4.1: Set the time - difference search range as \([-M,M]\) according to the inter - station distance;

[0026] Step 4.2: For each slave - station echo signal \(x\) i (n), where \(K - 1\geq i\geq1\), shift it to the right by \(T\) i \(\cdot b\) points to obtain multiple time - delay schemes for this slave - station. Here, \(T\) i takes integer values within the range of \([-M,M]\), and \(b\) is the time - shifting interval constant;

[0027] Step 4.3: Arrange and combine the multiple time - delay schemes of all slave - stations to construct a multi - channel time - delay estimation scheme set \(S\), \(K\) represents the number of receiving stations, \(S\) m \(=(x'_1,x'_2,\cdots x' i \cdots,x' K-1 )), \(x'\) i represents a time - delay scheme of the \(i\) - th slave - station echo signal.

[0028] In an embodiment of the present invention, step 5 includes:

[0029] Step 5.1: Arrange the slave - station echo signals in each estimation scheme in chronological order to obtain the echo data matrix corresponding to each estimation scheme;

[0030] Step 5.2: Combine the echo data matrix corresponding to each estimation scheme with the echo data matrix of the master station to obtain the echo data matrix of the receiving station corresponding to each estimation scheme;

[0031] Step 5.3: Calculate the corresponding decision matrix Y′ based on each of the receiving station echo data matrices, obtain the eigenvalue matrix of the decision matrix Y′, and calculate the decision parameter according to the eigenvalue matrix;

[0032] where Y′ = Y H Y, Y represents the receiving station echo data matrix, Y H represents the conjugate transpose of Y; a = p / sum, a represents the decision parameter, p represents the maximum eigenvalue in the eigenvalue matrix, and sum represents the sum of all eigenvalues in the eigenvalue matrix;

[0033] Step 5.4: Select the estimation scheme corresponding to the maximum value among all the decision parameters as the final time delay scheme.

[0034] In an embodiment of the present invention, the step 6 includes:

[0035] Compare the decision parameter corresponding to the final time delay scheme with a preset second threshold value. When the decision parameter is greater than the second threshold value, it is determined that there is a target. When the decision parameter is less than the second threshold value, it is determined that there is no target.

[0036] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0037] The distributed target detection method under the zero direct wave system of the present invention does not require direct wave information and can achieve target detection only relying on echo information. The receiving stations of the present invention are distributed, and multiple receiving stations work together, improving the reliability and laying a foundation for time difference positioning at the same time.

[0038] The above description is only an overview of the technical solution of the present invention. In order to be able to understand the technical means of the present invention more clearly, it can be implemented according to the content of the description. And in order to make the above and other purposes, features and advantages of the present invention more obvious and understandable, the following specific preferred embodiments are given and described in detail in conjunction with the accompanying drawings. Brief Description of the Drawings

[0039] Figure 1 is a scenario diagram provided by an embodiment of the present invention;

[0040] Figure 2 is a schematic diagram of a distributed target detection method under the zero direct wave system provided by an embodiment of the present invention;

[0041] Figure 3It is a flowchart of a distributed target detection method under a zero direct wave system provided by an embodiment of the present invention;

[0042] Figure 4 It is a time delay estimation diagram provided by an embodiment of the present invention;

[0043] Figure 5 It is a target detection diagram provided by an embodiment of the present invention. Detailed implementation manners

[0044] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following combines the accompanying drawings and specific implementation manners to elaborate in detail on a distributed target detection method under a zero direct wave system proposed according to the present invention.

[0045] The foregoing and other technical contents, features, and effects of the present invention can be clearly presented in the following detailed description in conjunction with the accompanying drawings. Through the description of the specific implementation manners, a more in-depth and specific understanding of the technical means and effects adopted by the present invention to achieve the predetermined purpose can be obtained. However, the attached drawings are only for reference and explanation, and are not used to limit the technical solutions of the present invention.

[0046] Embodiment 1

[0047] Please refer to Figure 1 , the application scenario of the distributed target detection method under the zero direct wave system of this embodiment is as Figure 1 shown, and multiple receiving stations cooperate, including a master station and multiple slave stations. Please refer to Figure 2 and Figure 3 , Figure 2 is a schematic diagram of a distributed target detection method under a zero direct wave system provided by an embodiment of the present invention; Figure 3 is a flowchart of a distributed target detection method under a zero direct wave system provided by an embodiment of the present invention. As shown in the figure, the distributed target detection method under the zero direct wave system of this embodiment includes:

[0048] Step 1: Obtain the echo signals received by multiple receiving stations, where the multiple receiving stations include a master station and multiple slave stations;

[0049] In an alternative implementation manner, the echo signals received by multiple receiving stations are simulated by setting the relevant parameters of the receiving stations, the targets, and the basic radiation source signals.

[0050] Assume that the number of receiving stations is K, where one receiving station is the master station and the remaining K - 1 receiving stations are slave stations. The radiation source signal is expressed as the product of the transmitted signal complex envelope and its phase change part:

[0051]

[0052] Among them, u(n) represents the complex envelope of the radiation source signal, and f c represents the carrier frequency of the transmitted signal, and represents the initial phase of the transmitted signal.

[0053] Set the time delay and frequency delay according to the speed, position of the target and the distance between the receiving stations, and add different noises according to the signal-to-noise ratio to generate the echo signal:

[0054] x k (n) = a k s(n - l k ) exp(jΩ k n) + w k (n) (2);

[0055] Among them, k = 1, 2,..., K, a k represents the loss coefficient of the echo received by the k-th receiving station, l k represents the time delay of the echo of the k-th receiving station relative to the master station, Ω k is the Doppler frequency difference of the k-th receiving station relative to the master station, w k (n) is a Gaussian white noise signal, w k (n) is noise that satisfies a circularly symmetric complex Gaussian distribution with a mean equal to 0 and a covariance equal to .

[0056] Step 2: Perform cross-ambiguity processing on each slave station echo signal and the master station echo signal in sequence to obtain the cross-ambiguity function values corresponding to the slave stations;

[0057] In an optionally implemented embodiment, Step 2 includes:

[0058] Use the ambiguity function to perform cross-ambiguity processing on each slave station echo signal and the master station echo signal in sequence to obtain the cross-ambiguity function values corresponding to the slave stations, where the ambiguity function is:

[0059]

[0060] In the formula, r1(n) represents the master station echo signal, x i (n) represents the echo signal of the i-th slave station, L represents the length of the signal, n τ represents the time delay, n f represents the Doppler frequency shift, x i * represents the conjugate of x i , and K represents the number of receiving stations.

[0061] Step 3: Compare the cross ambiguity function value with a preset first threshold value. If there is a cross ambiguity function value exceeding the first threshold value, record the time delay corresponding to this cross ambiguity function value, correct the echo signal of the corresponding slave station using the time delay, and perform target detection based on the correction result. If there is no cross ambiguity function value exceeding the first threshold value, execute Step 4;

[0062] Optionally, by setting the search ranges and step intervals of the time delay and frequency delay, perform a two-dimensional search on the cross ambiguity function values according to the time-frequency delay search ranges and step intervals, and compare with the preset first threshold value.

[0063] Among them, correcting the echo signal of the corresponding slave station using the time delay and performing target detection based on the correction result includes:

[0064] Step a: Correct the echo signal of the corresponding slave station using the time delay to obtain the corrected echo signal of the slave station;

[0065] Step b: Arrange the corrected echo signals of the slave station in chronological order to obtain the corresponding echo data matrix of the slave station;

[0066] Step c: Calculate to obtain a new matrix X′ according to the echo data matrix of the slave station, obtain the eigenvalue matrix of the new matrix X′, and calculate the characteristic parameter according to the eigenvalue matrix,

[0067] where X′ = X H X, X represents the echo data matrix of the slave station, X H represents the conjugate transpose of X; A = p / sum, A represents the characteristic parameter, p represents the largest eigenvalue in the eigenvalue matrix, and sum represents the sum of all eigenvalues in the eigenvalue matrix;

[0068] Step d: Compare the characteristic parameter with a preset second threshold value. When the characteristic parameter is greater than the second threshold value, it is determined that there is a target. When the characteristic parameter is less than the second threshold value, it is determined that there is no target.

[0069] Step 4: Set the time difference search range. According to the time difference search range, design multiple time delay schemes for each slave station, and construct a multi-channel time delay estimation scheme set according to the multiple time delay schemes of the slave stations;

[0070] In an optional implementation manner, Step 4 includes:

[0071] Step 4.1: Set the time difference search range to [-M, M] according to the inter-station distance;

[0072] Optionally, calculate the time delay estimation value according to the positions of the receiving station and the transmitting station, and determine the time difference search range according to this time delay estimation value. The time difference search range is slightly larger than the calculated time delay estimation value.

[0073] Step 4.2: For each slave echo signal x i (n), 1 ≤ i ≤ K - 1, shift it to the right by T i ·b points to obtain multiple time delay schemes for this slave station, where T i takes integer values within the range of [-M, M], and b is the time shift interval constant;

[0074] Step 4.3: Arrange and combine the multiple time delay schemes of all slave stations to construct a multi-channel time delay estimation scheme set S, that is, it includes a total of (2M + 1) K-1 schemes, K represents the number of receiving stations, and S m =(x′1, x′2, … x′ i …, x′ K-1 ), x′ i represents a time delay scheme of the echo signal of the i-th slave station.

[0075] Among them, the signal after delaying the echo signal of the i-th slave station according to the time delay scheme is expressed as:

[0076] x″ i (n)=a k s(n + T i ·b - l k )exp(jΩ k n)+w k (n), K - 1 ≥ i ≥ 1 (4).

[0077] Step 5: According to the multi-channel time delay estimation scheme set, obtain the echo data matrix of each receiving station corresponding to each estimation scheme, calculate the corresponding decision parameter according to the echo data matrix of the receiving station, and select the estimation scheme corresponding to the maximum decision parameter as the final time delay scheme;

[0078] In an optional implementation manner, Step 5 includes:

[0079] Step 5.1: Arrange the echo signals of each slave station in each estimation scheme in chronological order to obtain the echo data matrix corresponding to each estimation scheme;

[0080] Step 5.2: Combine the echo data matrix corresponding to each estimation scheme with the echo data matrix of the master station to obtain the echo data matrix of each receiving station corresponding to each estimation scheme;

[0081] Optionally, arrange the master station echo signal in chronological order to obtain the echo data matrix of the master station.

[0082] Step 5.3: Calculate the corresponding decision matrix Y′ based on the echo data matrix of each receiving station, obtain the eigenvalue matrix of the decision matrix Y′, and calculate the decision parameter according to the eigenvalue matrix;

[0083] where Y′ = Y H Y represents the echo data matrix of the receiving station, and Y H represents the conjugate transpose of Y; a = p / sum, where a represents the decision parameter, p represents the maximum eigenvalue in the eigenvalue matrix, and sum represents the sum of all eigenvalues in the eigenvalue matrix;

[0084] Step 5.4: Select the estimation scheme corresponding to the maximum value among all decision parameters as the final time delay scheme.

[0085] Optionally, a 1×(2M + 1) K-1 dimensional vector is set with all elements in G being 0. Each time a decision parameter a is calculated, it is stored in the corresponding position of the vector G, that is, let g i = a, 1 ≤ i ≤ (2M + 1) K-1 . By traversing the vector G to find the maximum value and recording the position of the maximum value in G, find the estimation scheme in the multi-channel time delay estimation scheme set S corresponding to the position of the maximum value in the vector G as the final time delay scheme, so as to determine the delay time.

[0086] In other alternative embodiments, a multi-dimensional matrix G can also be designed, which can store (2M + 1) K-1 data.

[0087] Step 6: Correct the echo signal according to the final time delay scheme, and perform target detection based on the correction result.

[0088] In an alternative embodiment, Step 6 includes:

[0089] Compare the decision parameter corresponding to the final time delay scheme with a preset second threshold. When the decision parameter is greater than the second threshold, it is determined that there is a target. When the decision parameter is less than the second threshold, it is determined that there is no target, that is, where Z represents the maximum value among all decision parameters, H1 represents the case of having a target, H0 represents the case of having no target, represents the second threshold.

[0090] The distributed target detection method under the zero direct wave system of the present invention does not require direct wave information and can achieve target detection only relying on echo information. The receiving stations of the present invention are distributed, and multiple receiving stations work together, improving the reliability and laying a foundation for time difference positioning at the same time.

[0091] Embodiment 2

[0092] In this embodiment, the effect of the distributed target detection method under the zero direct wave system of Embodiment 1 is illustrated through simulation experiments.

[0093] Taking 2 channels as an example, this embodiment is repeated 100 times for verification, and the detailed parameters of the experiment are shown in Table 1.

[0094] Table 1 Settings of simulation parameters for time delay estimation

[0095]

[0096]

[0097] As Figure 4 shown in the time delay estimation diagram, in the case of zero direct wave, using the time delay estimation method of the present invention, the time delay position can be correctly detected in the final experiment. The experimental results prove that the time delay estimation method proposed by the present invention can achieve time delay estimation in the case of zero direct wave.

[0098] To verify the target detection effect of the method of the present invention, the detailed parameters of the experiment are listed in Table 2. It should be noted that although the model parameters remain unchanged, in order to verify the accuracy and reliability of target detection, 100 Monte Carlo experiments are set for verification. Among them, the original signal "1" indicates the presence of a target, and "0" indicates the absence of a target.

[0099] Table 2 Settings of simulation parameters for target detection

[0100] Number of experiments 100 Probability of signal generation in the channel 0.5 Signal-to-noise ratio -40 dB Number of channels 2 Sampling frequency 100 MHz Integration time 0.1s Second threshold value 0.37

[0101] As Figure 5 shown in the target detection diagram, where Figure a is the original signal and Figure b is the detected signal. It can be seen that the accuracy of the final target detection of the distributed radar under the zero direct wave system can basically reach 100%.

[0102] It should be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant is intended to cover non-exclusive inclusion, so that an article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the article or device comprising the element. Words such as "connected" or "coupled" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The orientation or positional relationship indicated by "upper", "lower", "left", "right", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention.

[0103] The above content is a further detailed description of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is only limited to these descriptions. For those of ordinary skill in the technical field to which the present invention pertains, without departing from the concept of the present invention, several simple deductions or substitutions can be made, and all should be regarded as belonging to the protection scope of the present invention.

Claims

1. A distributed target detection method under a zero direct wave system, characterized in that Including: Step 1: Obtain the echo signals received by multiple receiving stations, where the multiple receiving stations include a master station and multiple slave stations; Step 2: Perform cross-ambiguity processing on each slave station echo signal and the master station echo signal in sequence to obtain the cross-ambiguity function values corresponding to the slave stations; Step 3: Compare the cross-ambiguity function values with a preset first threshold value. If there are cross-ambiguity function values exceeding the first threshold value, record the time delay corresponding to the cross-ambiguity function value, use the time delay to correct the corresponding slave station echo signal, and perform target detection based on the correction result. If there are no cross-ambiguity function values exceeding the first threshold value, execute Step 4; Step 4: Set the time difference search range, design multiple time delay schemes for each slave station according to the time difference search range, and construct a multi-channel time delay estimation scheme set according to the multiple time delay schemes of the slave stations; Step 5: According to the multi-channel time delay estimation scheme set, obtain the receiving station echo data matrix corresponding to each estimation scheme, calculate the corresponding decision parameter according to the receiving station echo data matrix, and select the estimation scheme corresponding to the maximum decision parameter as the final time delay scheme; Step 6: Correct the echo signal according to the final time delay scheme, and perform target detection based on the correction result.

2. The distributed target detection method under the zero direct wave system according to claim 1, characterized in that, The said Step 2 includes: Perform cross-ambiguity processing on each slave station echo signal and the master station echo signal in sequence using the ambiguity function to obtain the cross-ambiguity function values corresponding to the slave stations, where the ambiguity function is: where \(r_1(n)\) represents the master station echo signal, \(x\) i (n) represents the echo signal of the \(i\)-th slave station, \(L\) represents the length of the signal, \(n\) τ represents the time delay, \(n\) f represents the Doppler frequency shift, \(x\) i * represents the conjugate of \(x\) i and \(K\) represents the number of receiving stations.

3. The distributed target detection method under the zero direct wave system according to claim 1, characterized in that, In the said Step 3, using the time delay to correct the corresponding slave station echo signal and performing target detection based on the correction result includes: Step a: Use the time delay to correct the corresponding slave station echo signal to obtain the corrected slave station echo signal; Step b: Arrange the corrected slave station echo signals in chronological order to obtain the corresponding slave station echo data matrix; Step c: According to the slave station echo data matrix, calculate to obtain a new matrix X', obtain the eigenvalue matrix of the new matrix X', and calculate the characteristic parameter according to the eigenvalue matrix; where X' = X H X and X represent the slave echo data matrix, X H represents the conjugate transpose of X; A = p / sum, A represents the characteristic parameter, p represents the maximum eigenvalue in the eigenvalue matrix, and sum represents the sum of all eigenvalues in the eigenvalue matrix; Step d: Compare the characteristic parameter with a preset second threshold value. When the characteristic parameter is greater than the second threshold value, it is determined that there is a target. When the characteristic parameter is less than the second threshold value, it is determined that there is no target.

4. The distributed target detection method under the zero direct wave system according to claim 1, characterized in that The said Step 4 includes: Step 4.1: Set the time difference search range as [-M, M] according to the inter-station distance; Step 4.2: For each slave echo signal x i (n), where K - 1 ≥ i ≥ 1, shift it to the right by T i ·b points to obtain multiple time delay schemes for this slave station, where T i takes integer values within the range of [-M, M], and b is a time shift interval constant; Step 4.3: Arrange and combine multiple delay schemes of all slave stations to construct a multi-channel delay estimation scheme set S. K represents the number of receiving stations, and S m =(x′1,x'2,…x′ i …,x' K-1 ), where x′ i represents a delay scheme of the echo signal of the i-th slave station.

5. The distributed target detection method under the zero direct wave system according to claim 1, characterized in that, The said Step 5 includes: Step 5.1: Arrange each slave station echo signal in each estimation scheme in chronological order to obtain the echo data matrix corresponding to each estimation scheme; Step 5.2: Combine the echo data matrix corresponding to each estimation scheme with the echo data matrix of the master station to obtain the receiving station echo data matrix corresponding to each estimation scheme; Step 5.3: According to each receiving station echo data matrix, calculate to obtain the corresponding decision matrix Y', obtain the eigenvalue matrix of the decision matrix Y', and calculate the decision parameter according to the eigenvalue matrix; where Y' = Y H Y and Y represent the received station echo data matrix, H Y represents the conjugate transpose of Y; a = p / sum, where a represents the decision parameter, p represents the maximum eigenvalue in the eigenvalue matrix, and sum represents the sum of all eigenvalues in the eigenvalue matrix; Step 5.4: Select the estimation scheme corresponding to the maximum value among all decision parameters as the final time delay scheme.

6. The distributed target detection method under the zero direct wave system according to claim 5, characterized in that The said Step 6 includes: Compare the decision parameter corresponding to the final time delay scheme with a preset second threshold value. When the decision parameter is greater than the second threshold value, it is determined that there is a target. When the decision parameter is less than the second threshold value, it is determined that there is no target.

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