Non-circular signal positioning method based on distributed processing

Abstract

The invention discloses a non-circular signal positioning method based on distributed processing. The method comprises the following steps: constructing a distributed signal receiving platform to obtain a received signal, and obtaining the extended output of the distributed signal receiving platform according to the received signal and the non-circular characteristic of the received signal; on the basis of the extended output of the distributed signal receiving platform, calculating a feature vector of an extended covariance matrix of the received signal by using a distributed average consensus iterative solution mode; and calculating a non-circular signal positioning spatial spectrum function under the distributed operation based on the feature vector of the extended covariance matrix of the received signal, and obtaining a non-circular signal positioning result according to the non-circular signal positioning spatial spectrum function under the distributed operation. According to the method, data transmission can be reduced, the calculation efficiency is improved, the real-time requirement is met, and the positioning precision of the non-circular signal is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of array signal processing, and in particular to a non-circular signal positioning method based on distributed processing. Background Art

[0002] Non-circular signals are signals whose probability density function is not circularly symmetric in the complex plane. These signals have unique statistical characteristics and rotational moment properties, which give them significant advantages in signal processing.

[0003] In the non-circular signal positioning technology, the existing method 1 estimates the arrival direction of the signal through the orthogonality of the signal subspace and the noise subspace. This algorithm requires the data of all sensors to be concentrated into a central processor for covariance matrix calculation and eigenvalue decomposition, and then the arrival direction of the signal is determined by spectral peak search. This process requires a large amount of data transmission, resulting in high communication costs and high computational complexity, and is not suitable for large-scale arrays or distributed sensor networks. The existing method 2 also uses centralized processing to improve positioning accuracy by using the second-order and fourth-order cumulants of non-circular signals. However, when processing large-scale arrays, the communication and computing costs increase significantly because the data needs to be centrally transmitted and processed, which affects the real-time and robustness of the system. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the present invention provides a non-circular signal positioning method based on distributed processing.

[0005] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is:

[0006] A non-circular signal positioning method based on distributed processing comprises the following steps:

[0007] S1. constructing a distributed signal receiving platform to obtain a received signal, and obtaining an extended output of the distributed signal receiving platform according to the received signal and the non-circular characteristics of the received signal;

[0008] S2. Based on the extended output of the distributed signal receiving platform, the eigenvector of the extended covariance matrix of the received signal is calculated using a distributed average consensus iterative solution method;

[0009] S3. Calculate the non-circular signal positioning spatial spectrum function under distributed computing based on the eigenvector of the extended covariance matrix of the received signal, and obtain the non-circular signal positioning result according to the non-circular signal positioning spatial spectrum function under distributed computing.

[0010] Furthermore, in step S1, a distributed signal receiving platform is constructed, and the specific process is: determine the wavelength of the signal source, and set the spacing of the array elements according to the wavelength of the signal source; construct multiple array elements into a sub-array including a local processor, set the sub-array as a node, set the communication link between the sub-arrays as an edge, and construct an undirected graph including nodes and edges to construct a distributed signal receiving platform.

[0011] Furthermore, in step S1, the expression of the received signal is:

[0012]

[0013] x p (t) = [x p1 (t),x p2 (t),...,x ph (t)],

[0014]

[0015] Where: x(t) is the received signal of the distributed signal receiving platform at time t, x0(t), x1(t), x P-1 (t) and x p (t) are the received signals of the subarrays numbered 0, 1, P-1 and p in the distributed signal receiving platform at time t, respectively, (·) T To perform matrix transposition, P is the number of sub-arrays in the distributed signal receiving platform, x p1 (t), x p2 (t), x ph (t) and x pg (t) are the received signals of the 1st, 2nd, hth and gth array elements in the subarray labeled p at time t, h is the number of array elements in the subarray, K is the number of signal sources, s k (t) is the signal emitted by the kth signal source at time t, r pg,k is the distance between the gth array element and the kth signal source in the subarray labeled p, r 0,k is the distance between the reference point and the kth signal source in the distributed signal receiving platform, j is an imaginary unit, λ is the wavelength of the signal source, and n pg (t) is the additive noise of the g-th element in the sub-matrix labeled p at time t, is the non-circular phase of the kth signal source.

[0016] Further, in step S1, the expression for obtaining the extended output of the distributed signal receiving platform according to the received signal and the non-circular characteristic of the received signal is:

[0017]

[0018] Where: z p (t) is the extended output of the subarray labeled p in the distributed signal receiving platform at time t, x p (t) is the received signal of the subarray labeled p in the distributed signal receiving platform at time t, (·) * To obtain the conjugate operation, A p is the array manifold matrix of the subarray labeled p in the distributed signal receiving platform, Φ p is the non-circular phase shift matrix of the subarray labeled p in the distributed signal receiving platform, diag is a vector-to-diagonal-matrix operator. are the non-circular phases of the received signals of the 1st, 2nd, and Qth array elements in the subarray labeled p, respectively. R,p (t) is s R The receiving part of the subarray labeled p in (t), s R (t) is the real part of the signal emitted by the signal source at time t, n p (t) is the additive noise of the submatrix labeled p at time t.

[0019] Further, step S2 includes the following steps:

[0020] S21, based on the extended output of the distributed signal receiving platform, calculating the first eigenvector of the extended covariance matrix of the received signal by using an iterative solution method;

[0021] S22. Based on the first eigenvector of the extended covariance matrix of the received signal, the eigenvector of the extended covariance matrix of the received signal is calculated using a distributed average consensus iterative solution method.

[0022] Further, in step S21, based on the extended output of the distributed signal receiving platform, the expression of the first eigenvector of the extended covariance matrix of the received signal is calculated by an iterative solution method as follows:

[0023]

[0024] Where: u1(n+1) is the n+1th iteration result of the first eigenvector, P is the number of subarrays in the distributed signal receiving platform, L is the number of snapshots, z[l] is the lth snapshot reception data of the extended output of the distributed signal receiving platform, b[l] is a shorthand symbol, For The exact average value, z p [l] is the lth snapshot received data of the extended output of the subarray labeled p in the distributed signal receiving platform, (·) H To obtain the conjugate transpose operation, u 1,p(n) is the nth iteration result of the first eigenvector on the submatrix labeled p.

[0025] Further, in step S22, based on the first eigenvector of the extended covariance matrix of the received signal, the expression of the eigenvector of the extended covariance matrix of the received signal is calculated by using the distributed average consensus iterative solution method:

[0026]

[0027] Where: u q (n+1) is the n+1th iteration result of the qth eigenvector, is the nth iteration result equivalent to the qth eigenvector, P is the number of subarrays in the distributed signal receiving platform, is the i-th eigenvector of the extended covariance matrix of the received signal, For The exact average value of for The l-th snapshot of the sub-vector corresponding to the sub-matrix labeled p in (·) H To find the conjugate transpose operation, for The sub-vector corresponding to the sub-matrix labeled p, u q (n) is the nth iteration result of the qth eigenvector, is the extended covariance matrix obtained by using L snapshots for the subarray labeled p in the distributed signal receiving platform, where L is the number of snapshots, z p [l] is the lth snapshot received data of the extended output of the subarray labeled p in the distributed signal receiving platform.

[0028] Further, in step S3, the expression of the non-circular signal positioning space spectrum function under distributed computing based on the eigenvector of the extended covariance matrix of the received signal is:

[0029]

[0030] in: is the spatial spectrum function for positioning non-circular signals, (x, y) is the coordinates of the signal source, is the non-circular phase of the signal source, N is the number of array elements in the distributed signal receiving platform, P is the number of sub-arrays in the distributed signal receiving platform, K is the number of signal sources, For The exact average value of for The subvector corresponding to the submatrix labeled p in , is the i-th eigenvector of the extended covariance matrix of the received signal, (·)H To obtain the conjugate transpose operation, a k,p (x,y) is the spectrum peak search vector, and Φ is the non-circular phase shift matrix.

[0031] Furthermore, in step S3, the non-circular signal positioning result is obtained according to the non-circular signal positioning spatial spectrum function under distributed computing. The specific process is: the horizontal and vertical coordinates of the non-circular signal positioning spatial spectrum function under distributed computing are traversed and changed respectively, and then a two-dimensional spectrum peak search is performed on the angle and distance to obtain an estimated spatial spectrum, and the coordinate value corresponding to the peak value in the estimated spatial spectrum is determined as the non-circular signal positioning result.

[0032] The present invention has the following beneficial effects:

[0033] (1) The present invention aims to solve the problem of high data transmission and computation costs in large-scale arrays by constructing a distributed signal receiving platform to obtain received signals, and obtaining the extended output of the distributed signal receiving platform based on the received signals and the non-circular characteristics of the received signals, and then using the distributed average consensus iterative solution method to calculate the eigenvector of the extended covariance matrix of the received signal. This process can reduce data transmission, improve computational efficiency, and meet real-time requirements;

[0034] (2) The present invention makes full use of the statistical characteristics of non-circular signals and improves the positioning accuracy of non-circular signals by constructing a distributed signal receiving platform to perform distributed processing on the received signals. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a flowchart of a non-circular signal positioning method based on distributed processing;

[0036] Figure 2 This is a schematic diagram of a distributed signal receiving platform;

[0037] Figure 3 The spatial spectrum obtained by the traditional centralized MUSIC algorithm;

[0038] Figure 4 This is a magnified view of the spatial spectrum obtained by the traditional centralized MUSIC algorithm;

[0039] Figure 5 The spatial spectrum obtained by the method proposed by the present invention;

[0040] Figure 6 This is an enlarged view of the spatial spectrum obtained by the method proposed in the present invention. DETAILED DESCRIPTION

[0041] The specific implementation modes of the present invention are described below so that those skilled in the art can understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept of the present invention are protected.

[0042] like Figure 1 As shown, a non-circular signal positioning method based on distributed processing includes steps S1-S3, which are specifically as follows:

[0043] S1. Construct a distributed signal receiving platform to obtain a received signal, and obtain an extended output of the distributed signal receiving platform according to the received signal and the non-circular characteristics of the received signal.

[0044] In an optional embodiment of the present invention, the present invention constructs a distributed signal receiving platform, and the specific process is: determine the wavelength of the signal source, and set the spacing of the array elements according to the wavelength of the signal source; construct multiple array elements into a sub-array including a local processor, set the sub-array as a node, set the communication link between the sub-arrays as an edge, and construct an undirected graph including nodes and edges to construct a distributed signal receiving platform, such as Figure 2 shown.

[0045] The expression of the received signal in the present invention is:

[0046]

[0047] x p (t) = [x p1 (t),x p2 (t),...,x ph (t)],

[0048]

[0049] Where: x(t) is the received signal of the distributed signal receiving platform at time t, x0(t), x1(t), x P-1 (t) and x p (t) are the received signals of the subarrays numbered 0, 1, P-1 and p in the distributed signal receiving platform at time t, respectively, (·) T To perform matrix transposition, P is the number of sub-arrays in the distributed signal receiving platform, x p1 (t), x p2 (t), x ph (t) and x pg (t) are the received signals of the 1st, 2nd, hth and gth array elements in the subarray labeled p at time t, h is the number of array elements in the subarray, K is the number of signal sources, sk (t) is the signal emitted by the kth signal source at time t, r pg,k is the distance between the gth array element and the kth signal source in the subarray labeled p, r 0,k is the distance between the reference point and the kth signal source in the distributed signal receiving platform, j is an imaginary unit, λ is the wavelength of the signal source, and n pg (t) is the additive noise of the g-th element in the sub-matrix labeled p at time t, is the non-circular phase of the kth signal source.

[0050] The expression for obtaining the extended output of the distributed signal receiving platform according to the received signal and the non-circular characteristics of the received signal is:

[0051]

[0052] Where: z p (t) is the extended output of the subarray labeled p in the distributed signal receiving platform at time t, x p (t) is the received signal of the subarray labeled p in the distributed signal receiving platform at time t, (·) * To obtain the conjugate operation, A p is the array manifold matrix of the subarray labeled p in the distributed signal receiving platform, Φ p is the non-circular phase shift matrix of the subarray labeled p in the distributed signal receiving platform, diag is a vector-to-diagonal-matrix operator. are the non-circular phases of the received signals of the 1st, 2nd, and Qth array elements in the subarray labeled p, respectively. R,p (t) is s R The receiving part of the subarray labeled p in (t), s R (t) is the real part of the signal emitted by the signal source at time t, n p (t) is the additive noise of the submatrix labeled p at time t.

[0053] S2. Based on the extended output of the distributed signal receiving platform, the eigenvector of the extended covariance matrix of the received signal is calculated using the distributed average consensus iterative solution method.

[0054] In an optional embodiment of the present invention, step S2 includes the following steps:

[0055] S21. Based on the extended output of the distributed signal receiving platform, the first eigenvector of the extended covariance matrix of the received signal is calculated by an iterative solution method. The expression is:

[0056]

[0057] Where: u1(n+1) is the n+1th iteration result of the first eigenvector, P is the number of subarrays in the distributed signal receiving platform, L is the number of snapshots, a snapshot refers to a sampling of the signal, and the number of snapshots indicates the number of samplings, z[l] is the lth snapshot reception data of the extended output of the distributed signal receiving platform, b[l] is a shorthand symbol, For The exact average value, z p [l] is the lth snapshot received data of the extended output of the subarray labeled p in the distributed signal receiving platform, (·) H To obtain the conjugate transpose operation, u 1,p (n) is the nth iteration result of the first eigenvector on the submatrix labeled p.

[0058] S22. Based on the first eigenvector of the extended covariance matrix of the received signal, the eigenvector of the extended covariance matrix of the received signal is calculated using a distributed average consensus iterative solution method, and the expression is:

[0059]

[0060] Where: u q (n+1) is the n+1th iteration result of the qth eigenvector, is the nth iteration result equivalent to the qth eigenvector, P is the number of subarrays in the distributed signal receiving platform, is the i-th eigenvector of the extended covariance matrix of the received signal, For The exact average value of for The l-th snapshot of the sub-vector corresponding to the sub-matrix labeled p in (·) H To find the conjugate transpose operation, for The sub-vector corresponding to the sub-matrix labeled p, u q (n) is the nth iteration result of the qth eigenvector, is the extended covariance matrix obtained by using L snapshots for the subarray labeled p in the distributed signal receiving platform, where L is the number of snapshots, z p [l] is the lth snapshot received data of the extended output of the subarray labeled p in the distributed signal receiving platform.

[0061] S3. Calculate the non-circular signal positioning spatial spectrum function under distributed computing based on the eigenvector of the extended covariance matrix of the received signal, and obtain the non-circular signal positioning result according to the non-circular signal positioning spatial spectrum function under distributed computing.

[0062] In an optional embodiment of the present invention, the expression of the non-circular signal positioning space spectrum function under distributed computing based on the eigenvector of the extended covariance matrix of the received signal is:

[0063]

[0064] in: is the spatial spectrum function for positioning non-circular signals, (x, y) is the coordinates of the signal source, is the non-circular phase of the signal source, N is the number of array elements in the distributed signal receiving platform, P is the number of sub-arrays in the distributed signal receiving platform, K is the number of signal sources, For The exact average value of for The subvector corresponding to the submatrix labeled p in , is the i-th eigenvector of the extended covariance matrix of the received signal, (·) H To obtain the conjugate transpose operation, a k,p (x,y) is the spectrum peak search vector, and Φ is the non-circular phase shift matrix.

[0065] The present invention obtains the non-circular signal positioning result according to the non-circular signal positioning spatial spectrum function under distributed computing. The specific process is: the horizontal and vertical coordinates of the non-circular signal positioning spatial spectrum function under distributed computing are traversed and changed respectively, and then a two-dimensional spectrum peak search is performed on the angle and distance to obtain an estimated spatial spectrum, and the coordinate value corresponding to the peak value in the estimated spatial spectrum is determined as the non-circular signal positioning result.

[0066] Simulation experiment:

[0067] The method proposed in the present invention is simulated and compared with the traditional centralized MUSIC positioning algorithm, and the simulation scenario is shown in Table 1:

[0068] Table 1 Simulation scenario settings for non-circular signal positioning method

[0069]

[0070]

[0071] When the covariance matrix is ​​directly constructed using the array received signal, the simulation results of the traditional centralized MUSIC positioning algorithm are as follows: Figure 3 As shown, the enlarged picture with an accuracy of 0.5m is as follows Figure 4 When the extended matrix of the array receiving signal is used to construct the extended covariance matrix, the simulation results of the method proposed in the present invention are as follows: Figure 5 As shown, the enlarged picture with an accuracy of 0.5m is as follows Figure 6As shown. By comparing the spectral peak intensities output by the two methods, the power spectrum peak of the traditional method does not exceed 5dB, while the power spectrum peak of the method proposed in the present invention significantly exceeds 20dB. This significant improvement in the power spectrum peak indicates that the present invention can achieve higher accuracy under the same environment and is more suitable for the needs of spacecraft miniaturization development (i.e., high-precision positioning and fast signal processing of satellite-borne distributed phased arrays). In summary, the method proposed in the present invention is significantly superior to the traditional method in terms of positioning estimation spectral peak intensity, and exhibits more superior positioning estimation performance.

[0072] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0073] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0074] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0075] The present invention uses specific embodiments to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

[0076] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific variations and combinations that do not deviate from the essence of the present invention based on the technical revelations disclosed by the present invention, and these variations and combinations are still within the protection scope of the present invention.

Claims

1. A non-circular signal positioning method based on distributed processing, characterized in that: Includes steps: S1. constructing a distributed signal receiving platform to obtain a received signal, and obtaining an extended output of the distributed signal receiving platform according to the received signal and the non-circular characteristics of the received signal; S2. Based on the extended output of the distributed signal receiving platform, the eigenvector of the extended covariance matrix of the received signal is calculated using a distributed average consensus iterative solution method; S3. Calculate the non-circular signal positioning spatial spectrum function under distributed computing based on the eigenvector of the extended covariance matrix of the received signal, and obtain the non-circular signal positioning result according to the non-circular signal positioning spatial spectrum function under distributed computing.

2. The non-circular signal positioning method based on distributed processing according to claim 1, characterized in that: In step S1, the specific process of constructing a distributed signal receiving platform is as follows: determine the wavelength of the signal source, and set the spacing of the array elements according to the wavelength of the signal source; construct multiple array elements into a sub-array containing a local processor, set the sub-array as a node, set the communication link between the sub-arrays as an edge, and construct an undirected graph containing nodes and edges to construct a distributed signal receiving platform.

3. The non-circular signal positioning method based on distributed processing according to claim 1, characterized in that: In step S1, the expression of the received signal is: x p (t)=[x p1 (t),x p2 (t),...,x ph (t)], Where: x(t) is the received signal of the distributed signal receiving platform at time t, x0(t), x1(t), x P-1 (t) and x p (t) are the received signals of the subarrays numbered 0, 1, P-1 and p in the distributed signal receiving platform at time t, respectively, (·) T To perform matrix transposition, P is the number of sub-arrays in the distributed signal receiving platform, x p1 (t), x p2 (t), x ph (t) and x pg (t) are the received signals of the 1st, 2nd, hth and gth array elements in the subarray labeled p at time t, h is the number of array elements in the subarray, K is the number of signal sources, s k (t) is the signal emitted by the kth signal source at time t, r pg,k is the distance between the gth array element and the kth signal source in the subarray labeled p, r 0,k is the distance between the reference point and the kth signal source in the distributed signal receiving platform, j is an imaginary unit, λ is the wavelength of the signal source, and n pg (t) is the additive noise of the g-th element in the sub-matrix labeled p at time t, is the non-circular phase of the kth signal source.

4. The non-circular signal positioning method based on distributed processing according to claim 1, characterized in that: In step S1, the expression for obtaining the extended output of the distributed signal receiving platform according to the received signal and the non-circular characteristics of the received signal is: Where: z p (t) is the extended output of the subarray labeled p in the distributed signal receiving platform at time t, x p (t) is the received signal of the subarray labeled p in the distributed signal receiving platform at time t, (·) * To obtain the conjugate operation, A p is the array manifold matrix of the subarray labeled p in the distributed signal receiving platform, Φ p is the non-circular phase shift matrix of the subarray labeled p in the distributed signal receiving platform, diag is a vector-to-diagonal-matrix operator. are the non-circular phases of the received signals of the 1st, 2nd, and Qth array elements in the subarray labeled p, respectively. R,p (t) is s R The receiving part of the subarray labeled p in (t), s R (t) is the real part of the signal emitted by the signal source at time t, n p (t) is the additive noise of the submatrix labeled p at time t.

5. The non-circular signal positioning method based on distributed processing according to claim 1, characterized in that: Step S2 includes the following steps: S21, based on the extended output of the distributed signal receiving platform, calculating the first eigenvector of the extended covariance matrix of the received signal by using an iterative solution method; S22. Based on the first eigenvector of the extended covariance matrix of the received signal, the eigenvector of the extended covariance matrix of the received signal is calculated using a distributed average consensus iterative solution method.

6. The non-circular signal positioning method based on distributed processing according to claim 5, characterized in that: In step S21, based on the extended output of the distributed signal receiving platform, the expression of the first eigenvector of the extended covariance matrix of the received signal is calculated by an iterative solution method as follows: Where: u1(n+1) is the n+1th iteration result of the first eigenvector, P is the number of subarrays in the distributed signal receiving platform, L is the number of snapshots, z[l] is the lth snapshot reception data of the extended output of the distributed signal receiving platform, b[l] is a shorthand symbol, For The exact average value, z p [l] is the lth snapshot received data of the extended output of the subarray labeled p in the distributed signal receiving platform, (·) H To obtain the conjugate transpose operation, u 1,p (n) is the nth iteration result of the first eigenvector on the submatrix labeled p.

7. The non-circular signal positioning method based on distributed processing according to claim 5, characterized in that: In step S22, based on the first eigenvector of the extended covariance matrix of the received signal, the expression of the eigenvector of the extended covariance matrix of the received signal is calculated by using the distributed average consensus iterative solution method: Where: u q (n+1) is the n+1th iteration result of the qth eigenvector, is the nth iteration result equivalent to the qth eigenvector, P is the number of subarrays in the distributed signal receiving platform, is the i-th eigenvector of the extended covariance matrix of the received signal, For The exact average value of for The l-th snapshot of the sub-vector corresponding to the sub-matrix labeled p in (·) H To find the conjugate transpose operation, for The sub-vector corresponding to the sub-matrix labeled p, u q (n) is the nth iteration result of the qth eigenvector, is the extended covariance matrix obtained by using L snapshots for the subarray labeled p in the distributed signal receiving platform, where L is the number of snapshots, z p [l] is the lth snapshot received data of the extended output of the subarray labeled p in the distributed signal receiving platform.

8. The non-circular signal positioning method based on distributed processing according to claim 1, characterized in that: In step S3, the expression of the non-circular signal positioning space spectrum function under distributed computing based on the eigenvector of the extended covariance matrix of the received signal is: in: is the spatial spectrum function for positioning non-circular signals, (x, y) is the coordinates of the signal source, is the non-circular phase of the signal source, N is the number of array elements in the distributed signal receiving platform, P is the number of sub-arrays in the distributed signal receiving platform, K is the number of signal sources, For The exact average value of for The subvector corresponding to the submatrix labeled p in , is the i-th eigenvector of the extended covariance matrix of the received signal, (·) H To obtain the conjugate transpose operation, a k,p (x,y) is the spectrum peak search vector, and Φ is the non-circular phase shift matrix.

9. The non-circular signal positioning method based on distributed processing according to claim 1, characterized in that: In step S3, the specific process of obtaining the non-circular signal positioning result according to the non-circular signal positioning spatial spectrum function under distributed computing is as follows: the horizontal and vertical coordinates of the non-circular signal positioning spatial spectrum function under distributed computing are traversed and changed respectively, and then a two-dimensional spectrum peak search is performed on the angle and distance to obtain an estimated spatial spectrum, and the coordinate value corresponding to the peak value in the estimated spatial spectrum is determined as the non-circular signal positioning result.

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