Non-circular signal DOA estimation method and system based on fourth-order sum-difference joint cooperative array
By constructing a non-circular signal DOA estimation method of fourth-order and differential joint coordinated array, the problem of limited freedom in traditional DOA estimation methods is solved, and higher detection capability and processing efficiency are achieved. It is suitable for uniform linear arrays and sparse arrays, with good applicability and computing performance.
Patent Information
- Application Number
- CN202111293388.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2021-11-03
- Publication Date
- 2025-08-22
- Estimated Expiration
- 2041-11-03
AI Technical Summary
In the prior art, the traditional DOA estimation method is limited in the degree of freedom when detecting non-circular signals, and the uniform linear array model cannot be effectively expanded, and the traditional non-circular DOA estimation algorithm is limited to the uniform linear array model, which limits the algorithm's degree of freedom expansion ability.
Using the non-circular signal DOA estimation method based on the fourth-order synergistic joint coordinated array, the fourth-order synergistic joint coordinated array is constructed by constructing an augmented fourth-order cumulative quantity matrix and applying vectorization technology, and using the non-circular properties of the signal and the concept of the coordinated array are used to improve detection freedom.
It achieves higher detection freedom, facilitates modular processing and GPU parallel computing, is suitable for uniform linear arrays and sparse arrays, has good transplantability and universality, and improves the processing efficiency of DOA estimation.
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Figure CN114185036B_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of array signal processing technology, and more specifically, to a non-circular signal DOA estimation method and system based on a fourth-order sum-difference joint cooperative array. Background Art
[0002] Estimating the Direction of Arrival (DOA) of multiple signals collected by sensor arrays is a research hotspot in array signal processing. Traditional DOA estimation methods use a uniform linear array as the array model. However, their DOA estimation performance is limited by the physical array aperture. For a uniform linear array with N elements, traditional estimation methods can only estimate a maximum of N-1 signal sources. To enable detection of signal sources exceeding the number of array elements, the concept of cooperative arrays has emerged.
[0003] Coarray is a new type of virtual array. The most widely studied coarray is the differential coarray (see reference 1: Liu, C. and Vaidyanathan, P., “Robustness of difference coarrays of sparsearrays to sensor failures—Part I: A theory motivated by coarray MUSIC”. IEEE Transactions on Signal Processing, 2019. 67(12), pp. 3213-3226). The differential coarray is constructed by using the characteristic that the phase of any element in the signal covariance matrix presents the position difference of the array element. It has a high degree of freedom. Applying the concept of coarray to the N-element sparse array model can detect up to O(N) 2 ) order of magnitude. However, the signal model of the estimation method based on the differential covariance matrix is limited to circular signals, and circular signals can only use the information of the signal covariance, which is not conducive to fully mining the signal statistical information.
[0004] Non-circular signals (see reference 2: Abeida, H. and Delmas, J., “MUSIC-like estimation of direction of arrival for noncircular sources”. IEEE Transactions on Signal Processing, 2006. 54(7), pp. 2678-2690) are another signal model widely used in various application scenarios compared to circular signals. They can not only utilize signal covariance information, but also signal elliptical covariance information. This non-circular property is conducive to improving the degree of freedom of detection. The traditional non-circular DOA estimation algorithm uses this non-circular property to construct a classic non-circular virtual array. The virtual array consists of a physical array and a corresponding flip array. Using N physical array elements, it can detect up to 2 (N-1) targets. The traditional non-circular DOA estimation algorithm is limited to the uniform linear array model, which greatly limits the degree of freedom expansion capability of the algorithm. Summary of the Invention
[0005] The purpose of the present invention is to provide a non-circular signal DOA estimation method and system based on a fourth-order sum-difference joint cooperative array, which has good portability and universality, a higher degree of freedom, facilitates modular processing, is suitable for GPU parallel computing in signal processors, and improves processing efficiency.
[0006] In order to achieve at least one of the above objectives, the present application adopts the following technical solutions:
[0007] In a first aspect, the present application provides a non-circular signal DOA estimation method based on a fourth-order sum-difference joint cooperative array, comprising:
[0008] S1. The far-field detection scene module locates the far-field tag target to be tracked, including Q far-field narrow-band non-circular non-Gaussian signal sources, and the azimuth angles of the Q far-field narrow-band non-circular non-Gaussian signal sources are {θ1,...,θ Q};
[0009] S2. The linear radar array system receives the far-field narrowband non-circular non-Gaussian signal source to obtain a received signal;
[0010] S3. constructing an augmented fourth-order cumulant matrix using the received signal;
[0011] S4, applying vectorization technology to the augmented cumulant matrix to obtain a fourth-order sum-difference joint cooperative matrix;
[0012] S5. Use non-circular phase separation and cooperative array spectrum estimation technology to complete DOA estimation.
[0013] In a specific embodiment, the received signal is:
[0014]
[0015] The array model of the linear radar array system is a linear array composed of N array elements.
[0016] The array model is represented as D={d1,...,d N};
[0017] in,
[0018] A=[a(θ1),...,a(θ Q )] represents the array manifold matrix, represents the steering vector, s(t)=[s1(t),…,s Q (t)] T represents a non-circular non-Gaussian signal vector, n(t)=[n1(t),…,n N (t)] T represents a zero-mean Gaussian white noise vector.
[0019] In a specific embodiment, the S2 further includes:
[0020] Any qth non-circular non-Gaussian signal s q (t) has the following relationship:
[0021]
[0022] Where q = 1, 2, ... Q, α q is a non-circular phase, s′ q (t) is a zero-phase real-valued signal.
[0023] In a specific embodiment, the S3 includes:
[0024] S31, according to the relationship get:
[0025] The fourth-order cumulant calculation result is:
[0026]
[0027] The fourth-order cumulant calculation result is:
[0028]
[0029] The fourth-order cumulant calculation result is:
[0030]
[0031] The fourth-order cumulant calculation result is:
[0032]
[0033] {s q (t),s q (t),s q (t),s q The fourth-order cumulant calculation result of (t)} is:
[0034]
[0035] S32, combining the above formulas (3) to (7) to construct the augmented fourth-order cumulant matrix C four :
[0036]
[0037] Among them, any matrix element C i_j (1≤i,j≤3) is expressed as:
[0038]
[0039] Among them, CUMmatrix is the fourth-order cumulant matrix operator, represents the left Kronecker product, (·) H represents the conjugate transpose, Indicates a dimension of N 2 ×N 2 The fourth-order cumulant matrix of Rank Column elements are fourth-order cumulants
[0040] S33. According to the above formula (9), the augmented fourth-order cumulant matrix is rewritten as an equivalent covariance matrix:
[0041]
[0042] in, represents a diagonal matrix, whose qth (q=1,2,…,Q) diagonal element is: A four =[a four (θ1),...,a four (θ Q )] represents the augmented array manifold matrix,
[0043] The augmented array popularity matrix A four =[a four (θ1),…,a four (θQ )] is:
[0044]
[0045] According to formula (11), the virtual element position of the equivalent covariance matrix is expressed as:
[0046]
[0047] In a specific embodiment, the S4 includes:
[0048] S41. Perform a vectorization operation on the equivalent covariance matrix to obtain a vector:
[0049]
[0050] Where ⊙ represents the Khatri-Rao product, represents the augmented vectorized non-circular array manifold matrix,
[0051] The qth steering vector of the augmented vectorized non-circular array manifold matrix is:
[0052]
[0053] S42, remove the vector C vec The redundant and discontinuous discrete virtual elements are obtained:
[0054]
[0055] in, It is from The non-redundant continuous array manifold extracted from ;
[0056] S43, constructing a fourth-order sum-difference joint cooperative matrix according to the above formulas (12) and (13);
[0057] The virtual array element set of the fourth-order sum-difference joint cooperative array can be expressed as follows: 4ds
[0058] D 4ds =D ds -D ds (15);
[0059] in,
[0060]
[0061] D diff =DD represents the difference result of the physical array element set D, and Indicates positive and negative and result, D ds Represents the sum-difference cooperative matrix, the fourth-order sum-difference joint cooperative matrix D 4ds It is the sum-difference cooperative matrix D ds The result of the difference operation.
[0062] In a specific embodiment, the far-field detection scenario is a non-cooperative scenario for locating an unknown far-field target or a cooperative scenario controlled by one party.
[0063] In a specific embodiment, the linear array is a uniform linear array or a sparse array.
[0064] A second aspect of the present application provides a non-circular signal DOA estimation system based on a fourth-order sum-difference joint cooperative array, comprising:
[0065] Far-field detection scene module: used to locate the far-field tag target to be tracked, including Q far-field narrow-band non-circular non-Gaussian signal sources, the azimuth angles of the Q far-field narrow-band non-circular non-Gaussian signal sources are {θ1,…,θ Q};
[0066] A linear radar array system is configured to receive the far-field narrowband non-circular non-Gaussian signal to obtain a received signal;
[0067] DOA estimation signal processor: used to construct an augmented cumulant matrix and apply vectorization technology to the augmented cumulant matrix to obtain a fourth-order sum-difference joint cooperative array, and use non-circular phase separation and cooperative array spectrum estimation technology to complete DOA estimation.
[0068] In a third aspect, the present application provides a non-circular signal DOA estimation device based on a fourth-order sum-difference joint cooperative array, comprising: a memory, one or more processors; the memory and the processor are connected via a communication bus; the processor is configured to execute instructions in the memory; and the storage medium stores instructions for executing each step of the above method.
[0069] A fourth aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the above method when executed by a processor.
[0070] The beneficial effects of this application are as follows:
[0071] In response to the problems existing in the current existing technology, the present application provides a non-circular signal DOA estimation method and system, device and computer-readable storage medium based on a fourth-order sum-difference joint cooperative array. The method of the present application facilitates modular processing and is suitable for GPU parallel computing in the signal processor, thereby improving processing efficiency. The present application also proposes an augmented cumulant matrix construction technology, and provides a strategy for constructing a sum-difference cooperative array using cumulant technology. The augmented cumulant matrix vectorization technology is proposed to construct a new fourth-order sum-difference joint cooperative array with higher degrees of freedom. In addition, the array system model of the present application can be either a uniform linear array or a sparse array, and has good portability and universality. BRIEF DESCRIPTION OF THE DRAWINGS
[0072] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.
[0073] Figure 1 A step diagram of a non-circular signal DOA estimation method based on a fourth-order sum-difference joint cooperative array in one embodiment of the present application is shown.
[0074] Figure 2 A non-circular signal DOA estimation method based on a fourth-order sum-difference joint cooperative array and a flowchart of system functional module division in one embodiment of the present application are shown.
[0075] Figure 3 A schematic diagram of a far-field multi-target orientation estimation scenario and a linear antenna array in one embodiment of the present application is shown.
[0076] Figure 4 A comparison chart showing the theoretical maximum degrees of freedom of four virtual arrays in an embodiment of the present application is shown. DETAILED DESCRIPTION
[0077] In the following description, for the purpose of explanation, numerous specific details are set forth in order to provide a thorough understanding of one or more embodiments. However, it will be apparent that these embodiments may be practiced without these specific details.
[0078] In the description of this application, it should be noted that the terms "upper" and "lower" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on this application. Unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or an indirect connection through an intermediate medium, or it can be internal communication between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to the specific circumstances.
[0079] It should also be noted that, in the description of the present application, relational terms such as first and second, etc. are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply the existence of any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element.
[0080] In order to improve the degree of freedom of DOA estimation for multiple signals collected by the sensor array and solve the problems existing in the prior art, an embodiment of the present application provides a non-circular signal DOA estimation method based on a fourth-order sum-difference joint cooperative array. The method steps are as follows: Figure 1 As shown,
[0081] In a specific embodiment, the method includes:
[0082] S1. The far-field detection scene module locates the far-field tag target to be tracked, which includes Q far-field narrow-band non-circular non-Gaussian signal sources. The non-circularity rate of the signal is 1, and the azimuth angles of the Q far-field narrow-band non-circular non-Gaussian signal sources are {θ1,…,θ Q},like Figure 3 As shown;
[0083] The non-circular non-Gaussian signal source satisfies the plane wave propagation characteristics because it is a far-field signal model;
[0084] In a specific embodiment, the far-field detection scenario is a non-cooperative system scenario for locating unknown far-field targets or a cooperative system scenario controlled by one's own party, such as Figure 2 shown.
[0085] S2. The linear radar array system receives the far-field narrowband non-circular non-Gaussian signal source to obtain a received signal:
[0086]
[0087] in,
[0088] A=[a(θ1),…,a(θ Q )] represents the array manifold matrix, represents the steering vector, s(t)=[s1(t),…,s Q (t)] T represents a non-circular non-Gaussian signal vector, n(t)=[n1(t),…,n N (t)] T represents a zero-mean Gaussian white noise vector;
[0089] The array model of the linear radar array system is a linear array composed of N array elements, and the sensor array element position set is D = {d1,…,d N};
[0090] According to the characteristics of non-circular signals, any q-th non-circular non-Gaussian signal s q (t) has the following relationship:
[0091]
[0092] Where q = 1, 2, ... Q, α q is a non-circular phase, s′ q (t) is a zero-phase real-valued signal;
[0093] The physical array structure of the linear radar array system can be a uniform linear array or a sparse array, such as Figure 2 As shown, when a sparse array is used, the array element consumption can be reduced and the virtual aperture can be increased. When a uniform linear array is used, the beam sidelobes can be reduced. Therefore, the present application has good universality and portability.
[0094] S3. Constructing an augmented fourth-order cumulant matrix according to the received signal, including:
[0095] S31, according to the above relationship get:
[0096] The fourth-order cumulant calculation result is:
[0097]
[0098] The fourth-order cumulant calculation result is:
[0099]
[0100] The fourth-order cumulant calculation result is:
[0101]
[0102] The fourth-order cumulant calculation result is:
[0103]
[0104] {s q (t),s q (t),s q (t),s q The fourth-order cumulant calculation result of (t)} is:
[0105]
[0106] S32. For the convenience of expression, this application defines a fourth-order cumulant matrix operator CUMmatrix, which is used to calculate the received signal x(t)=[x1(t),x2(t),...,x N (t)] T The fourth-order cumulant matrix. Let p1,p2,p3,p4∈{1,2,...,N}, the matrix ( represents the left Kronecker product) Rank Column elements are represented by composition. Then, Indicates a dimension of N 2 ×N 2 The fourth-order cumulant matrix of Rank Column elements are fourth-order cumulants
[0107] In order to jointly utilize the non-circular property, the concept of cooperative array and the cumulant operation to improve the detection freedom, the augmented fourth-order cumulant matrix C is constructed by combining the above formulas (3) to (7): four :
[0108]
[0109] Among them, any matrix element C i_j(1≤i,j≤3) is expressed as:
[0110]
[0111] Among them, CUMmatrix is the fourth-order cumulant matrix operator, represents the left Kronecker product, (·) H represents the conjugate transpose, Indicates a dimension of N 2 ×N 2 The fourth-order cumulant matrix of Rank Column elements are fourth-order cumulants
[0112] According to the augmented fourth-order cumulant matrix C four The matrix structure of is known to be easily divided into multiple basic fourth-order cumulant matrices C i_j (1≤i,j≤3) module, therefore, GPU parallel computing technology can be used for parallel processing to improve algorithm efficiency.
[0113] S33. According to the above formula (9), the augmented fourth-order cumulant matrix is rewritten as an equivalent covariance matrix:
[0114]
[0115] in, represents a diagonal matrix, whose qth (q=1,2,…,Q) diagonal element is: A four =[a four (θ1),...,a four (θ Q )] represents the augmented array manifold matrix,
[0116] The augmented array popularity matrix A four =[a four (θ1),...,a four (θ Q )] is:
[0117]
[0118] According to formula (10), the augmented fourth-order cumulant matrix C four It can be regarded as a steering vector four The augmented covariance matrix corresponding to the synergy matrix of (θ);
[0119] According to formula (11), the virtual element position of the equivalent covariance matrix is expressed as:
[0120] That is, it is composed of the difference operation result and the sum operation result.
[0121] Since the phase of the steering vector (Formula (11)) contains the difference and positive and negative sum calculation results of the physical array element positions, the augmented cumulant matrix construction technology successfully constructs the sum-difference cooperative array;
[0122] The expression of the virtual element position of the sum-difference cooperative array is:
[0123]
[0124] Among them, D ds Denotes the sum-difference coordinator matrix, D diff =DD represents the difference result of the physical array element set D, and Indicates positive, negative and results;
[0125] Compared with the differential cooperative array that is currently the main application, the sum-difference cooperative array has a higher degree of freedom.
[0126] S4. Applying vectorization technology to the augmented cumulant matrix to obtain a fourth-order sum-difference joint cooperative matrix; including:
[0127] S41. Perform a vectorization operation on the equivalent covariance matrix to obtain a vector:
[0128]
[0129] Where ⊙ represents the Khatri-Rao product, represents the augmented vectorized non-circular array manifold matrix,
[0130] The qth steering vector of the augmented vectorized non-circular array manifold matrix is:
[0131]
[0132] Obviously, the vector C constructed by vectorization technology vec It has an expression form similar to the received signal vector in formula (1), which can be regarded as the array manifold: The received signal of the corresponding cooperative array. Formula (13) shows that the augmented cumulant matrix is expanded from the original sum-difference cooperative array to the differential result of the sum-difference cooperative array. This application names the virtual array corresponding to Formula (13) as the fourth-order sum-difference joint cooperative array, which is a new type of cooperative array. Obviously, compared with the sum-difference cooperative array, the fourth-order sum-difference joint cooperative array after differential expansion has higher degrees of freedom and can detect more signal targets.
[0133] According to the structure of the steering vector of the augmented vectorized non-circular array manifold matrix, it can be well modularized and is therefore also suitable for using GPU parallel computing technology to improve processing efficiency.
[0134] S42, remove the vector C vec The redundant and discontinuous discrete virtual elements are obtained:
[0135]
[0136] in, It is from The non-redundant continuous array manifold extracted from ;
[0137] S43, constructing a fourth-order sum-difference joint cooperative matrix according to the above formulas (12) and (13);
[0138] The virtual array element set of the fourth-order sum-difference joint cooperative array can be expressed as follows: 4ds
[0139] D 4ds =D ds -D ds (15);
[0140] in,
[0141]
[0142] D diff =DD represents the difference result of the physical array element set D, and Indicates positive and negative and result, D ds Represents the sum-difference cooperative matrix, the fourth-order sum-difference joint cooperative matrix D 4ds It is the sum-difference cooperative matrix D ds The result of the difference operation.
[0143] S5. Use non-circular phase separation and cooperative array spectrum estimation technology to complete DOA estimation.
[0144] For the DOA estimation signal processor, such as Figure 2 The figure shows the computational core of this application, which primarily addresses the DOA estimation method for non-circular signals based on a fourth-order sum-difference joint cooperative array. This method includes two phases: augmented cumulant matrix construction for constructing the sum-difference joint cooperative array, and augmented cumulant matrix vectorization for constructing the fourth-order sum-difference joint cooperative array. This application facilitates modularization, facilitating the use of GPU parallel acceleration technology to improve computational efficiency.
[0145] A second aspect of the present application further provides a non-circular signal DOA estimation system based on a fourth-order sum-difference joint cooperative array, comprising:
[0146] Far-field detection scene module: used to locate the far-field tag target to be tracked, including Q far-field narrow-band non-circular non-Gaussian signal sources, the azimuth angles of the Q far-field narrow-band non-circular non-Gaussian signal sources are {θ1,...,θ Q};
[0147] A linear radar array system is configured to receive the far-field narrowband non-circular non-Gaussian signal to obtain a received signal;
[0148] DOA estimation signal processor: used to construct an augmented cumulant matrix and apply vectorization technology to the augmented cumulant matrix to obtain a fourth-order sum-difference joint cooperative array, and use non-circular phase separation and cooperative array spectrum estimation technology to complete DOA estimation.
[0149] In a third aspect, the present application further provides a non-circular signal DOA estimation device based on a fourth-order sum-difference joint cooperative array, comprising: a memory, one or more processors; the memory and the processor are connected via a communication bus; the processor is configured to execute instructions in the memory; and the storage medium stores instructions for executing each step of the above method.
[0150] The fourth aspect of the present application further provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the above method when executed by a processor.
[0151] Through combinatorial mathematics theory, this application can easily deduce the highest degree of freedom of the four virtual arrays in theory: the classical non-circular virtual array, the differential cooperative array, the sum-difference cooperative array, and the fourth-order sum-difference combined cooperative array. Figure 4 As shown in the figure, when the number of physical array elements is N, the theoretical maximum degrees of freedom of the classical non-circular virtual array and the differential cooperative array are 2(N-1) and N(N-1)+1, respectively. In comparison, the theoretical maximum degree of freedom of the sum-difference cooperative array can reach 2N(N-1)+1, which is much greater than the degrees of freedom of the classical non-circular virtual array and the differential cooperative array. This is because the sum-difference cooperative array is obtained by fully combining the non-circular properties, the concept of cooperative arrays, and the cumulative operation, so the amount of available information mined is greater. Furthermore, the theoretical maximum degree of freedom of the fourth-order sum-difference joint cooperative array constructed by the present invention can reach 4N 2 (N-1) 2 +2N(N-1)+1, a further improvement over the sum-difference cooperative array. This is because the method of the present invention fully utilizes the high-order statistical information of the cumulants through vectorization operations, thereby fully expanding the virtual aperture. Therefore, compared with the other three virtual array systems, the method and system of the present invention can detect more signal targets and has better estimation performance.
[0152] Cumulant technology is a method for constructing sum-difference co-ordination arrays. Because cumulants contain more information than second-order statistical methods, they can theoretically fully exploit the statistical information of the signal, constructing higher-order sum-difference co-ordination arrays to achieve larger virtual apertures.
[0153] In summary, the method and system of the present invention have the following advantages: the array system model can be either a uniform linear array or a sparse array, with good portability and universality; it facilitates modular processing and is suitable for GPU parallel computing in signal processors, thereby improving processing efficiency; an augmented cumulant matrix construction technology is proposed, providing a strategy for constructing sum-difference cooperative arrays using cumulant technology; an augmented cumulant matrix vectorization technology is proposed, constructing a new fourth-order sum-difference joint cooperative array with higher degrees of freedom.
[0154] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not limitations on the implementation methods of the present invention. For ordinary technicians in the relevant field, other different forms of changes or modifications can be made based on the above description. It is impossible to list all the implementation methods here. All obvious changes or modifications derived from the technical solution of the present invention are still within the scope of protection of the present invention.
Claims
1. A non-circular signal DOA estimation method based on a fourth-order sum-difference joint cooperative array, characterized in that: include: S1. The far-field detection scene module locates the far-field tag target to be tracked, which includes Q far-field narrow-band non-circular non-Gaussian signal sources. The azimuth angles of the Q far-field narrow-band non-circular non-Gaussian signal sources are ; S2. The linear radar array system receives the far-field narrowband non-circular non-Gaussian signal source to obtain a received signal; S3. constructing an augmented fourth-order cumulant matrix using the received signal; S4. Apply vectorization technology to the augmented cumulant matrix to obtain a fourth-order sum-difference joint synergy matrix; The S4 includes S41. Perform vectorization on the equivalent covariance matrix to obtain a vector: ， in, represents the Khatri-Rao product, , represents the augmented vectorized non-circular array manifold matrix, The qth steering vector of the augmented vectorized non-circular array manifold matrix is: ， S42, remove the vector The redundant and discontinuous discrete virtual elements are obtained: ， in, is from ( ) extracted from the non-redundant continuous array manifold; S43, constructing a fourth-order sum-difference joint cooperative matrix according to the above formula; The virtual array element set of the fourth-order sum-difference joint cooperative array is expressed as follows ， in, ， Represents a set of physical array elements The difference result of and Indicates positive and negative and results, Represents the sum-difference cooperative matrix, the fourth-order sum-difference joint cooperative matrix It is a sum-difference synergistic matrix The result of the difference operation; S5. Use non-circular phase separation and cooperative array spectrum estimation technology to complete DOA estimation.
2. The method according to claim 1, characterized in that The received signal is: ， The array model of the linear radar array system is a linear array composed of N array elements. The array model is represented as ; in, represents the array manifold matrix, represents the steering vector, represents a non-circular non-Gaussian signal vector, represents a zero-mean Gaussian white noise vector.
3. The method according to claim 2, characterized in that Said S2 further comprises: Any qth non-circular non-Gaussian signal Has the following relationship: ， Where, q=1,2,……,Q, is a non-circular phase, is a zero-phase real-valued signal.
4. The method according to claim 3, characterized in that The S3 includes: S31, according to the relationship get: The fourth-order cumulant calculation result is: ， The fourth-order cumulant calculation result is: ， The fourth-order cumulant calculation result is: ， The fourth-order cumulant calculation result is: ， The fourth-order cumulant calculation result is: ， S32. Combine the above formula to construct an augmented fourth-order cumulant matrix : ， Among them, any matrix element ( ) is expressed as: ， Among them, CUMmatrix is the fourth-order cumulant matrix operator, represents the left Kronecker product, , represents the conjugate transpose, Represents a dimension The fourth-order cumulant matrix of Rank Column elements are fourth-order cumulants , ; S33. Rewrite the augmented fourth-order cumulant matrix into an equivalent covariance matrix according to the above formula: ， in, represents a diagonal matrix whose qth (q=1,2,…,Q) diagonal element is: , represents the augmented array manifold matrix, The augmented array popularity matrix The qth steering vector in is: ， The virtual element position of the equivalent covariance matrix is expressed as: 。 5. The method according to claim 1, wherein The far-field detection scenario is a non-cooperative system scenario for locating an unknown target in the far field or a cooperative system scenario controlled by one party.
6. The method according to claim 1, characterized in that The linear array is a uniform linear array or a sparse array.
7. A non-circular signal DOA estimation system based on a fourth-order sum-difference joint cooperative array, characterized in that: include: Far-field detection scene module: used to locate the far-field tag target to be tracked, including Q far-field narrow-band non-circular non-Gaussian signal sources, the azimuth angles of the Q far-field narrow-band non-circular non-Gaussian signal sources are ; A linear radar array system is configured to receive the far-field narrowband non-circular non-Gaussian signal to obtain a received signal; DOA estimation signal processor: used to construct an augmented cumulant matrix and apply vectorization technology to the augmented cumulant matrix to obtain a fourth-order sum-difference joint cooperative array, perform vectorization operation on the equivalent covariance matrix to obtain a vector, remove redundant and non-continuous discrete virtual elements in the vector, and construct a fourth-order sum-difference joint cooperative array. The fourth-order sum-difference joint cooperative array is the difference operation result of the sum-difference cooperative array, and uses non-circular phase separation and cooperative array spectrum estimation technology to complete DOA estimation.
8. A non-circular signal DOA estimation device based on a fourth-order sum-difference joint cooperative array is characterized by: include: memory, one or more processors; The memory is connected to the processor via a communication bus; the processor is configured to execute instructions in the memory; The memory stores instructions for executing each step of the method according to any one of claims 1 to 6.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.