Conformal polarization sensitive array DOA estimation method based on virtual array extension technology

Abstract

The invention discloses a conformal polarization sensitive array DOA estimation method based on a virtual array extension technology, and the method comprises the steps: determining a sparse non-uniform linear array from a conformal polarization sensitive array, and constructing a first array flow pattern of the conformal polarization sensitive array and a second array flow pattern of the sparse non-uniform linear array; calculating a first covariance matrix according to the first array flow pattern and the spatial signal; calculating a second covariance matrix according to the second array flow pattern and the spatial signal; expanding the sparse non-uniform linear array by using a virtual array expansion technology to obtain a virtual uniform linear array, and constructing a third array flow pattern of the virtual uniform linear array; obtaining a virtual transformation matrix according to the second array flow pattern and the third array flow pattern; processing the second covariance matrix by using the virtual transformation matrix to obtain a third covariance matrix; dOA estimation is carried out according to the third covariance matrix and the first covariance matrix, the estimation precision is improved, a more accurate space signal angle measurement result is obtained, implementation is easy, and the cost is low.

Description

Technical Field

[0001] The present invention belongs to the technical field of signal processing, and in particular relates to a conformal polarization sensitive array DOA (Direction Of Arrival) estimation method based on virtual array extension technology. Background Art

[0002] The conformal array is attached to the surface of the carrier and fits the carrier structure. It is a layout method that is consistent with the shape of the object, which maintains the aerodynamic performance of the carrier to the greatest extent, improves the space utilization rate, and makes the carried equipment have better stealth performance. Conformal arrays are widely used in high-speed moving carriers such as aircraft, satellites and missiles.

[0003] Since the carrier structure cannot be destroyed, the conformal array structure is sparse and irregular, the number of array elements is limited, and it does not have the good performance of regular arrays such as uniform circular arrays. The two-dimensional conformal array with discontinuous azimuth layout has the problem of poor DOA estimation accuracy and cannot perform direction finding tasks normally.

[0004] For irregular conformal polarization sensitive arrays, the existing solutions to address the poor DOA estimation accuracy are divided into the following three types: offline calibration and storage of amplitude and phase errors, installation of real-time correction hardware modules in the device, and increasing the number of array elements.

[0005] Among them, the amplitude and phase errors are calibrated and stored offline. This method has a long implementation cycle, and the amplitude and phase inconsistencies of the receiving channel vary greatly with the increase of temperature. If all ambient temperatures of the carrier are to be covered, it will cause great pressure on the internal storage of the carrier and increase the hardware cost of the carrier. In the case of adding a real-time correction hardware module to the carrier, this method requires sufficient space inside the carrier. However, in actual engineering, the internal space of small aircraft is limited and the module cannot be installed. Increasing the number of array elements in an irregular conformal polarization-sensitive array, due to the discontinuous space on the carrier where the array elements can be placed, the final conformal array does not have good deambiguation capabilities, and adding array elements will also increase costs.

[0006] In summary, there is an urgent need for a conformal polarization-sensitive array DOA estimation method with high estimation accuracy, simple implementation and low cost. Summary of the invention

[0007] In order to solve the above problems existing in the prior art, the present invention provides a conformal polarization sensitive array DOA estimation method based on virtual array extension technology.

[0008] The technical problem to be solved by the present invention is achieved through the following technical solutions:

[0009] The present invention provides a conformal polarization sensitive array DOA estimation method based on virtual array extension technology, comprising:

[0010] Determining a sparse non-uniform linear array from a conformal polarization sensitive array, and constructing a first array flow pattern of the conformal polarization sensitive array and a second array flow pattern of the sparse non-uniform linear array;

[0011] Calculate a first covariance matrix of received data of the conformal polarization sensitive array according to the first array flow pattern and the spatial signal;

[0012] Calculate a second covariance matrix of the received data of the sparse non-uniform linear array according to the second array flow pattern and the spatial signal;

[0013] Expanding the sparse non-uniform linear array using a virtual array expansion technology to obtain a virtual uniform linear array, and constructing a third array flow pattern of the virtual uniform linear array;

[0014] Obtaining a virtual transformation matrix according to the second array flow pattern and the third array flow pattern;

[0015] Processing the second covariance matrix using the virtual transformation matrix to obtain a third covariance matrix of the received data of the virtual uniform linear array;

[0016] DOA estimation is performed according to the third covariance matrix and the first covariance matrix to obtain an angle measurement result of the spatial signal.

[0017] Optionally, determining a sparse non-uniform linear array from a conformal polarization sensitive array includes:

[0018] determining a horizontal axis of a conformal polarization sensitive array;

[0019] The array elements on the horizontal axis are formed into a sparse non-uniform linear array.

[0020] Optionally, performing DOA estimation according to the third covariance matrix and the first covariance matrix to obtain an angle measurement result of the spatial signal includes:

[0021] Performing eigenvalue decomposition on the third covariance matrix, and then calculating the first spatial spectrum to obtain the azimuth of the spatial signal;

[0022] Determine a second spatial spectrum of the conformal polarization sensitive array according to the first covariance matrix;

[0023] The elevation angle of the spatial signal is searched for in the second spatial spectrum according to the azimuth angle of the spatial signal.

[0024] Optionally, the first array flow pattern is:

[0025]

[0026] Wherein, a(·) represents the conformal polarization sensitive array steering vector; the azimuth angle of the nth spatial signal is θ n Indicated by; the elevation angle of the nth spatial signal is expressed by Indicated by; the polarization auxiliary angle of the nth spatial signal is γ n The polarization phase difference of the nth spatial signal is represented by η n Indicates; n=1,2...N.

[0027] Optionally, the second array flow pattern is:

[0028]

[0029] The distance between the mth array element and the m-1th array element in the sparse non-uniform linear array is d m Indicates that m = 2...M sub ;M sub represents the total number of array elements in the sparse non-uniform linear array; the azimuth angle of the nth spatial signal is θ n represents; n=1,2...N; j represents an imaginary unit; e represents a natural base; λ represents the wavelength of the spatial signal; π represents pi.

[0030] Optionally, the third array flow pattern is:

[0031]

[0032] Wherein, d represents the array element spacing in the virtual uniform linear array; the azimuth angle of the nth spatial signal is θ n represents; n = 1, 2 ... N; j represents an imaginary unit; e represents a natural base; λ represents the wavelength of the spatial signal; π represents the circumference ratio; M v represents the total number of array elements in the virtual uniform linear array.

[0033] Optionally, the virtual transformation matrix is ​​calculated as follows:

[0034] B=(T H T) -1 / 2 T H ;

[0035] Wherein, B represents the virtual transformation matrix; A sub represents the second array flow pattern; A represents the first array flow pattern; A visual A represents the third array flow pattern; sub (θ) represents the second array flow pattern of the spatial signal with an azimuth angle of θ; A(θ) represents the first array flow pattern of the spatial signal with an azimuth angle of θ; A visual(θ) represents the third array manifold with the azimuth angle of the spatial signal being θ; θ represents the azimuth angle of the spatial signal; and the superscript H represents the matrix conjugate transpose.

[0036] Optionally, the second covariance matrix is ​​processed by using the virtual transformation matrix to obtain a third covariance matrix of the received data of the virtual uniform linear array, including:

[0037]

[0038] Among them, R visual represents the third covariance matrix; R sub represents the second covariance matrix; σ n Represents the noise power corresponding to the nth spatial signal; n=1,2...N.

[0039] The present invention provides a conformal polarization sensitive array DOA estimation method based on virtual array expansion technology, which expands a sparse non-uniform linear array by using the virtual array expansion technology to obtain a virtual uniform linear array. Then, DOA estimation is performed using the third covariance matrix of the received data of the virtual uniform linear array and the first covariance matrix of the received data of the conformal polarization sensitive array, thereby improving the array degree of freedom and the estimation accuracy of the azimuth angle, thereby improving the accuracy of DOA estimation and obtaining a more accurate angle measurement result of the spatial signal.

[0040] In addition, the conformal polarization sensitive array DOA estimation method based on virtual array extension technology provided by the present invention does not increase hardware cost or damage the device structure, and is simple to implement and low in cost.

[0041] The present invention will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a flow chart of a conformal polarization sensitive array DOA estimation method based on virtual array extension technology provided by an embodiment of the present invention;

[0043] Figure 2 is a schematic structural diagram of a conformal polarization sensitive array provided by an embodiment of the present invention;

[0044] Figure 3 is a schematic diagram of the structure of a virtual uniform linear array provided by an embodiment of the present invention;

[0045] Figure 4 This is a schematic diagram of the placement angle of a single dipole antenna;

[0046] Figure 5 It is a schematic diagram of the MUSIC spatial spectrum of the conformal polarization sensitive array;

[0047] Figure 6 It is a schematic diagram of the MUSIC spatial spectrum of a virtual uniform linear array;

[0048] Figure 7 is a schematic diagram of the direction finding error of the conformal polarization sensitive array;

[0049] Figure 8 This is a schematic diagram of the direction finding error of the conformal polarization sensitive array after expansion based on the virtual array expansion technology. DETAILED DESCRIPTION

[0050] The present invention is further described in detail below with reference to specific embodiments, but the embodiments of the present invention are not limited thereto.

[0051] In order to solve the problems of low estimation accuracy, high cost and high implementation difficulty in the existing conformal polarization sensitive array DOA estimation method, the embodiment of the present invention provides a conformal polarization sensitive array DOA estimation method based on virtual array extension technology, see Figure 1 , Figure 1 1 is a flow chart of a conformal polarization sensitive array DOA estimation method based on virtual array extension technology provided by an embodiment of the present invention, which specifically includes the following steps:

[0052] Step S101 : determining a sparse non-uniform linear array from a conformal polarization sensitive array, and constructing a first array flow pattern of the conformal polarization sensitive array and a second array flow pattern of the sparse non-uniform linear array.

[0053] The structure of the conformal polarization sensitive array depends on the aerodynamic shape of the device it carries. The elements of the conformal polarization sensitive array are sparsely arranged at the position where the device can carry the elements. Figure 2 , Figure 2 Schematic diagram of the structure of a conformal polarization sensitive array provided by an embodiment of the present invention. Figure 2 The conformal polarization sensitive array is divided into two sub-arrays, where sub-array 1 is a sparse non-uniform linear array, and the other array elements except sub-array 1 constitute sub-array 2, which is an irregular sparse array.

[0054] The array flow pattern is a set of steering vectors, which is related to the array shape and the direction of the spatial signal. Therefore, the first array flow pattern of the conformal polarization sensitive array can be constructed based on the spatial signal and the conformal polarization sensitive array. The second array flow pattern of the sparse non-uniform linear array can be constructed based on the spatial signal and the sparse non-uniform linear array.

[0055] Step S102: Calculate a first covariance matrix of received data of the conformal polarization sensitive array according to the first array flow pattern and the spatial signal.

[0056] In the embodiment of the present invention, the position, quantity and polarization direction of the array elements in the conformal polarization sensitive array can be known according to the first array flow type, and then the first covariance matrix of the received data of the conformal polarization sensitive array can be calculated through the spatial signal.

[0057] The covariance matrix is ​​a Hermitian matrix, in which each element represents the covariance between a pair of variables. The first covariance matrix can be used to represent the covariance between the received data of each array element of the conformal polarization sensitive array, indicating the correlation between the received data of each array element.

[0058] Step S103: Calculate a second covariance matrix of the received data of the sparse non-uniform linear array according to the second array flow pattern and the spatial signal.

[0059] Similarly, the position, quantity and polarization direction of the array elements in the sparse non-uniform linear array can be known according to the second array flow pattern, and then the second covariance matrix of the received data of the sparse non-uniform linear array can be calculated through the spatial signal.

[0060] The second covariance matrix can be used to represent the covariance between the data received by each array element of the sparse non-uniform linear array, indicating the correlation between the data received by each array element.

[0061] Step S104: using a virtual array expansion technique to expand the sparse non-uniform linear array to obtain a virtual uniform linear array, and constructing a third array flow pattern of the virtual uniform linear array.

[0062] Virtual array extension technology refers to the use of certain technical means, including constructing a specific array structure model, using mathematical methods to process the received signal source, and performing virtual transformation on the array, in order to achieve the purpose of expanding the original array aperture or increasing the number of array elements. The application of different virtual array technologies, such as increasing the number of virtual array elements, widening the aperture of the array, and transforming the array, can greatly improve the accuracy of the estimation, enhance the robustness of the array, and achieve decoherence. Virtual array extension technology can be used for the layout of large array antennas and the placement of irregular array antennas. The main methods of virtual array extension technology include the fourth-order cumulant method, the extrapolation method, and the interpolation method.

[0063] See also Figure 3 , Figure 3 is a schematic diagram of the structure of a virtual uniform linear array provided by an embodiment of the present invention. Along the horizontal axis, the sparse non-uniform linear array is expanded by interpolation to obtain a virtual uniform linear array. In the virtual uniform linear array, the spacing between array elements is equal, which is d, and the azimuth angle of the spatial signal is θ.

[0064] A third array flow pattern of a virtual uniform linear array can be constructed according to the spatial signal and the virtual uniform linear array.

[0065] Step S105, obtaining a virtual transformation matrix according to the second array flow type and the third array flow type.

[0066] In the embodiment of the present invention, the second array flow pattern is an array flow pattern of a sparse non-uniform linear array, and the third array flow pattern is an array flow pattern of a virtual uniform linear array obtained by expanding the sparse non-uniform linear array. Therefore, according to the relationship between the second array flow pattern and the third array flow pattern, the virtual transformation matrix can be obtained.

[0067] Step S106: Process the second covariance matrix using the virtual transformation matrix to obtain a third covariance matrix of the received data of the virtual uniform linear array.

[0068] In the embodiment of the present invention, the second covariance matrix is ​​the covariance matrix of the received data of the sparse non-uniform linear array. Therefore, by processing the second covariance matrix according to the virtual transformation matrix obtained in step S105, the third covariance matrix of the received data of the virtual uniform linear array can be obtained.

[0069] The third covariance matrix of the received data of the virtual uniform linear array indicates the correlation between the received data of each array element in the virtual uniform linear array.

[0070] Step S107: performing DOA estimation according to the third covariance matrix and the first covariance matrix to obtain an angle measurement result of the spatial signal.

[0071] In the embodiment of the present invention, after obtaining the third covariance matrix and the first covariance matrix, the DOA estimation may be performed using a MUSIC (Multiple Signal Classification) algorithm to obtain an angle measurement result of the spatial signal.

[0072] The MUSIC algorithm is an algorithm based on subspace decomposition. It uses the eigenvalues ​​of the third covariance matrix and the first covariance matrix to obtain the noise subspace, and uses the orthogonality of the signal subspace and the noise subspace to construct the spatial spectrum. By searching the spectrum peak, it estimates the incoming direction of the spatial signal, including the azimuth and elevation angle.

[0073] In the embodiment of the present invention, a virtual uniform linear array is obtained by expanding a sparse non-uniform linear array using a virtual array expansion technology. Then, DOA estimation is performed using the third covariance matrix of the received data of the virtual uniform linear array and the first covariance matrix of the received data of the conformal polarization sensitive array, thereby improving the array degree of freedom and the estimation accuracy of the azimuth angle, thereby improving the accuracy of DOA estimation, and obtaining a more accurate angle measurement result of the spatial signal.

[0074] In addition, the conformal polarization sensitive array DOA estimation method based on virtual array extension technology provided by the embodiment of the present invention does not increase hardware cost or damage the device structure, and is simple to implement and low in cost.

[0075] In DOA estimation, the biggest difference from the conventional DOA estimation algorithm is that the application of virtual array technology can improve the utilization efficiency of array element antennas and greatly improve the degree of freedom of the entire array.

[0076] In one implementation, determining a sparse non-uniform linear array from a conformal polarization sensitive array includes: determining a horizontal axis of the conformal polarization sensitive array; and composing array elements on the horizontal axis into a sparse non-uniform linear array.

[0077] See also Figure 2 , the x-axis in the xoy coordinate system is the horizontal axis of the conformal polarization sensitive array, and the four array elements on the horizontal axis point in the same direction, forming a one-dimensional non-uniform linear array, recorded as sub-array 1, that is, a sparse non-uniform linear array is obtained. The remaining four array elements are recorded as sub-array 2, that is, an irregular sparse array is obtained.

[0078] Assume that there are N signal sources in space, i.e., spatial signals, incident on the conformal polarization sensitive array, and their two-dimensional wave arrival direction is θ n is the azimuth of the nth spatial signal, is the elevation angle of the nth spatial signal, and the coordinates of the array element in the conformal polarization sensitive array are (x m ,y m ,z m ),m=1,..,M, then the receiving signal models of the conformal polarization sensitive array and the sparse non-uniform linear array are:

[0079] X(t)=AS(t)+n(t);

[0080] X sub (t) = A sub S(t)+n(t);

[0081] Wherein, X(t) represents the receiving signal model of the conformal polarization sensitive array; A represents the array flow type of the conformal polarization sensitive array, that is, the first array flow type; S(t) represents the spatial signal matrix; n(t) represents Gaussian white noise; X sub (t) represents the received signal model of the sparse non-uniform linear array; A sub represents the array flow pattern of the sparse non-uniform linear array, that is, the second array flow pattern; t represents time.

[0082] For a conformal polarization sensitive array, the spatial phase factor caused by the nth spatial signal incident on the mth array element is:

[0083] u (m,n)=exp(-λ / 2πτ m );

[0084] Among them, u (m,n) represents the spatial phase factor caused by the nth spatial signal incident on the mth array element; λ represents the wavelength of the spatial signal; and π represents pi. The conformal polarization sensitive array is G = [g 1 ,g 2 ,...,g m ] T , represents the polarization receiving characteristics of the array element, which is determined by the placement angle of the antenna. The superscript T represents the transpose of the matrix.

[0085] In the embodiment of the present invention, the array elements of the conformal polarization sensitive array may all be incomplete electromagnetic vector sensors, which are only sensitive to the electric field component of the spatial signal, that is:

[0086] g m =[sinβ m cosα m ,sinβ m sinα m ,cosβ m ,0,0,0] T ;

[0087] Among them, g m represents the polarization receiving characteristic of the mth array element; β m Represents the angle between the single dipole antenna and the z-axis; α m represents the projection of a single dipole antenna on the xoy plane and the angle between the x-axis; Figure 4 As shown, Figure 4 This is a schematic diagram of the placement angle of a single dipole antenna.

[0088] Since the conformal polarization sensitive array is distributed in the same plane, the angle between each array element and the z-axis is Right now Then m =[cosα n ,sinα n ,0,0,0,0] T .

[0089] The spatial-polarization factor is:

[0090]

[0091] Among them, S ps represents the spatial-polarization factor; j represents the imaginary unit; e represents the natural base; h is a function with γ and η as variables; γ n represents the polarization auxiliary angle of the nth spatial signal; η nrepresents the polarization phase difference of the nth spatial signal; η∈[-π,π] represents the polarization state of the signal. Finally, the steering vector of the conformal polarization sensitive array is Has the following form:

[0092]

[0093] in, It represents the spatial phase factor caused by the nth spatial signal incident on the mth array element.

[0094] The array flow pattern of the conformal polarization sensitive array, that is, the first array flow pattern is:

[0095]

[0096] Where a(·) represents the steering vector of the conformal polarization sensitive array; the azimuth angle of the nth spatial signal is θ n Indicated by; the elevation angle of the nth spatial signal is expressed by Indicated by; the polarization auxiliary angle of the nth spatial signal is γ n The polarization phase difference of the nth spatial signal is represented by η n Indicates; n=1,2...N.

[0097] Assume that the number of array elements of the sparse non-uniform linear array is M sub , then the second array flow pattern is:

[0098]

[0099] The distance between the mth array element and the m-1th array element in the sparse non-uniform linear array is d m Indicates that m = 2...M sub ;M sub represents the total number of array elements in the sparse non-uniform linear array; θ n represents the azimuth of the nth spatial signal; n = 1, 2...N; j represents an imaginary unit; e represents a natural base; λ represents the wavelength of the spatial signal; π represents pi.

[0100] In the embodiment of the present invention, the sparse non-uniform linear array is expanded by using the virtual array expansion technology, ignoring the part of the carrier that cannot place the array element, measuring the length of the carrier that can carry the array element, and determining the position of the virtual array element. The virtual uniform linear array is a scalar uniform linear array with an array element spacing of d. The third array flow type is:

[0101]

[0102] Where d represents the element spacing in the virtual uniform linear array; θ nrepresents the azimuth of the nth spatial signal; n=1,2...N; j represents the imaginary unit; e represents the natural base; λ represents the wavelength of the spatial signal; π represents the circumference ratio; M v Represents the total number of array elements in the virtual uniform linear array.

[0103] At this time, the virtual transformation matrix T directly obtained is:

[0104]

[0105] A sub represents the second array flow pattern; A represents the first array flow pattern; A visual Represents the third array flow pattern; A sub (θ) represents the second array flow pattern when the azimuth angle of the spatial signal is θ; A(θ) represents the first array flow pattern when the azimuth angle of the spatial signal is θ; A visual (θ) represents the third array manifold with the azimuth angle of the spatial signal being θ; θ represents the azimuth angle of the spatial signal.

[0106] According to the principle of virtual transformation technology, there is a transformation relationship between the received data of the virtual uniform linear array and the real space signal, namely:

[0107] x visual =T H x sub (t);

[0108] Among them, x visual represents the real space signal; x sub (t) represents the received data of the virtual uniform linear array.

[0109] Based on this, the second covariance matrix is ​​processed using a virtual transformation matrix, and the covariance matrix of the received data of the virtual uniform linear array can be obtained as follows:

[0110]

[0111] However, due to T H T≠I, so directly using the virtual transformation matrix T to find the covariance matrix of the virtual transformed data will turn white noise into color noise, which will seriously affect the performance of azimuth estimation. Where I represents the unit matrix.

[0112] Therefore, in the embodiment of the present invention, by whitening the noise, T is converted into:

[0113] B=(T H T) -1 / 2 T H ;

[0114] Wherein, B represents the virtual transformation matrix in the embodiment of the present invention.

[0115] Through the virtual transformation matrix B, the third covariance matrix is ​​obtained as:

[0116]

[0117] Among them, R visual represents the third covariance matrix; R sub represents the second covariance matrix; σ n Represents the noise power corresponding to the nth spatial signal; n=1,2...N.

[0118] In one implementation, performing DOA estimation according to the third covariance matrix and the first covariance matrix to obtain an angle measurement result of the spatial signal includes:

[0119] Performing eigenvalue decomposition on the third covariance matrix, and then calculating the first spatial spectrum to obtain the azimuth of the spatial signal;

[0120] Determine a second spatial spectrum of the conformal polarization sensitive array according to the first covariance matrix;

[0121] The elevation angle of the spatial signal is searched for in the second spatial spectrum according to the azimuth angle of the spatial signal.

[0122] In the embodiment of the present invention, a spatial spectrum estimation algorithm, such as a MUSIC algorithm, may be used to perform DOA estimation according to the third covariance matrix and the first covariance matrix to obtain an angle measurement result of the spatial signal.

[0123] Specifically, the third covariance matrix is ​​subjected to eigenvalue decomposition, and the noise subspace is obtained by using the MUSIC algorithm. The first spatial spectrum is calculated and the azimuth is obtained by spectrum peak search. Then, the second spatial spectrum of the conformal polarization sensitive array is determined from the first covariance matrix. Then, the column where the azimuth is located in the second spatial spectrum of the conformal polarization sensitive array is searched for the elevation angle to obtain a two-dimensional DOA estimation value.

[0124] The number of virtual array elements that can be carried is determined according to the carrier length, the virtual uniform linear array that needs virtual transformation is determined by adding virtual array elements, and the array flow pattern of the virtual uniform linear array is constructed, wherein the array element spacing of the virtual uniform linear array is λ / 2, and λ is the wavelength of the spatial signal.

[0125] In the embodiment of the present invention, any irregular conformal polarization sensitive array that meets the conditions for being split can use the method provided by the embodiment of the present invention to achieve the purpose of improving the DOA estimation accuracy. In addition, if the hardware storage space allows, offline storage of amplitude and phase errors can also improve the DOA estimation accuracy. For non-polarization sensitive arrays, the method provided by the embodiment of the present invention can also be used to process the irregular array, thereby achieving the purpose of improving the DOA estimation accuracy.

[0126] In addition, the virtual array expansion technology is used locally on the array. The expanded virtual array is not limited to a uniform array, and the virtual array can be adjusted according to actual needs.

[0127] A simulation experiment is conducted based on the conformal polarization sensitive array DOA estimation method based on the virtual array extension technology provided by the embodiment of the present invention. The structure of the conformal polarization sensitive array used in the simulation experiment is shown in Figure 2 The conformal polarization sensitive array is arranged in a bilaterally symmetrical triangular structure. Due to the shape of the carrier, the array element cannot be placed in the middle. The subarray on the x-axis is virtually expanded. The number of array elements after expansion is 30. The simulation simulates a source wave arrival direction of (30°, 35°) and the signal frequency is 9GHz. The amplitude and phase errors are added to simulate the channel amplitude and phase inconsistency under high temperature conditions.

[0128] See also Figure 5 and Figure 6 , Figure 5 This is a schematic diagram of the MUSIC spatial spectrum of the conformal polarization sensitive array. Figure 6 It is a schematic diagram of the MUSIC spatial spectrum of the virtual uniform linear array. From the simulation results, it can be seen that the peak value of the spatial spectrum pseudo-peak formed by the original array is relatively high, which affects the direction finding accuracy. After combining the azimuth direction finding results of the one-dimensional virtual linear array to search for the spectrum peak, the correct DOA estimation result is obtained. Among them, peak / power represents the peak value of the spatial spectrum; yaw angle represents the azimuth angle; pitch angle represents the pitch angle.

[0129] Under the above simulation conditions, 100 Monte Carlo simulations were performed to statistically analyze the direction finding errors of the conformal polarization sensitive array before and after expansion using the virtual array expansion technology. Figure 7 and Figure 8 As shown in Figure 2, the direction finding error includes the azimuth error and the elevation error. Figure 7 is a schematic diagram of the direction finding error of the conformal polarization sensitive array. Figure 8 This is a schematic diagram of the direction finding error of the conformal polarization sensitive array after expansion based on the virtual array expansion technology.

[0130] It should be noted that the terms "first", "second", etc. are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of devices and methods consistent with some aspects of the present invention.

[0131] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification.

[0132] Although the present invention is described herein in conjunction with various embodiments, in the process of implementing the claimed invention, those skilled in the art can understand and implement other changes to the disclosed embodiments by viewing the drawings and the disclosed content. In the description of the present invention, the term "comprising" does not exclude other components or steps, "one" or "an" does not exclude multiple situations, and "multiple" means two or more, unless otherwise clearly and specifically limited. In addition, certain measures are recorded in different embodiments, but this does not mean that these measures cannot be combined to produce good results.

[0133] The above contents are further detailed descriptions of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the protection scope of the present invention.

Claims

1. A conformal polarization sensitive array DOA estimation method based on virtual array extension technology, characterized in that: include: Determining a sparse non-uniform linear array from a conformal polarization sensitive array, and constructing a first array flow pattern of the conformal polarization sensitive array and a second array flow pattern of the sparse non-uniform linear array; Calculate a first covariance matrix of received data of the conformal polarization sensitive array according to the first array flow pattern and the spatial signal; Calculate a second covariance matrix of the received data of the sparse non-uniform linear array according to the second array flow pattern and the spatial signal; Expanding the sparse non-uniform linear array using a virtual array expansion technology to obtain a virtual uniform linear array, and constructing a third array flow pattern of the virtual uniform linear array; Obtaining a virtual transformation matrix according to the second array flow pattern and the third array flow pattern; Processing the second covariance matrix using the virtual transformation matrix to obtain a third covariance matrix of the received data of the virtual uniform linear array; DOA estimation is performed according to the third covariance matrix and the first covariance matrix to obtain an angle measurement result of the spatial signal.

2. The conformal polarization sensitive array DOA estimation method according to claim 1, characterized in that: Determine sparse non-uniform linear arrays from conformal polarization sensitive arrays, including: determining a horizontal axis of a conformal polarization sensitive array; The array elements on the horizontal axis are formed into a sparse non-uniform linear array.

3. The conformal polarization sensitive array DOA estimation method according to claim 1, characterized in that: Performing DOA estimation according to the third covariance matrix and the first covariance matrix to obtain an angle measurement result of the spatial signal includes: Performing eigenvalue decomposition on the third covariance matrix, and then calculating the first spatial spectrum to obtain the azimuth of the spatial signal; Determine a second spatial spectrum of the conformal polarization sensitive array according to the first covariance matrix; The elevation angle of the spatial signal is searched for in the second spatial spectrum according to the azimuth angle of the spatial signal.

4. The conformal polarization sensitive array DOA estimation method according to claim 1, characterized in that: The first array flow pattern is: Wherein, a(·) represents the steering vector of the conformal polarization sensitive array; the azimuth angle of the nth spatial signal is θ n Indicated by; the elevation angle of the nth spatial signal is expressed by Indicated by; the polarization auxiliary angle of the nth spatial signal is γ n The polarization phase difference of the nth spatial signal is represented by η n Indicates; n=1,2...N.

5. The conformal polarization sensitive array DOA estimation method according to claim 1, characterized in that: The second array flow pattern is: The distance between the mth array element and the m-1th array element in the sparse non-uniform linear array is d m Indicates that m = 2...M sub ;M sub represents the total number of array elements in the sparse non-uniform linear array; the azimuth angle of the nth spatial signal is θ n represents; n=1,2...N; j represents an imaginary unit; e represents a natural base; λ represents the wavelength of the spatial signal; π represents pi.

6. The conformal polarization sensitive array DOA estimation method according to claim 1, characterized in that: The third array flow pattern is: Wherein, d represents the array element spacing in the virtual uniform linear array; the azimuth angle of the nth spatial signal is θ n represents; n = 1, 2 ... N; j represents an imaginary unit; e represents a natural base; λ represents the wavelength of the spatial signal; π represents the circumference ratio; M v represents the total number of array elements in the virtual uniform linear array.

7. The conformal polarization sensitive array DOA estimation method according to claim 1, characterized in that: The virtual transformation matrix is ​​calculated as follows: B=(T H T) -1 / 2 T H ; Wherein, B represents the virtual transformation matrix; A sub represents the second array flow pattern; A represents the first array flow pattern; A visual A represents the third array flow pattern; sub (θ) represents the second array flow pattern of the spatial signal with an azimuth angle of θ; A(θ) represents the first array flow pattern of the spatial signal with an azimuth angle of θ; A visual (θ) represents the third array manifold with the azimuth angle of the spatial signal being θ; θ represents the azimuth angle of the spatial signal; and the superscript H represents the matrix conjugate transpose.

8. The conformal polarization sensitive array DOA estimation method according to claim 7, characterized in that: The second covariance matrix is ​​processed by using the virtual transformation matrix to obtain a third covariance matrix of the received data of the virtual uniform linear array, including: Among them, R sub represents the second covariance matrix; σ n Represents the noise power corresponding to the nth spatial signal; n=1,2...N.

Images