Airspace non-uniform distributed coherent array angle measurement method and device

Abstract

The invention discloses an airspace non-uniform distributed coherent array angle measurement method and device, and the method comprises the steps: carrying out the estimation of the receiving gain of a target distance unit, and obtaining the receiving gain; establishing an airspace sampling vector of the target distance unit according to the receiving gain; obtaining an adaptive directional diagram vector according to the main beam center angle, the main beam left boundary angle and the main beam right boundary angle; constructing a directional diagram matching matrix according to the adaptive directional diagram vector; obtaining a correlation coefficient spectrum according to a column vector of the directional diagram matching matrix and the spatial domain sampling vector; and obtaining a correlation angle corresponding to the maximum value in the correlation coefficient spectrum to obtain a target angle estimation value. The method can improve the angle measurement efficiency of the non-uniformly distributed coherent array, and can be widely applied to the technical field of signal processing.

Description

Technical Field

[0001] This invention relates to the field of signal processing technology, and in particular to a method and apparatus for angle measurement using a spatially non-uniform distributed coherent array. Background Technology

[0002] Non-uniform distributed arrays, due to their coherent synthetic aperture size being much larger than that of conventional single-node phased array antennas, suffer from a significantly narrower main lobe width in their antenna pattern, resulting in a marked reduction in the spatial coverage area. Within the same angular observation range, this property forces beam scanning schemes to densely discretize the angular space and perform target detection in each predefined fine beam direction, making the scanning search process of non-uniform distributed coherent arrays slow and inefficient. Two-stage scanning schemes designed to improve scanning efficiency—coarse scanning followed by fine estimation—are often affected by the distributed array grating lobes, failing to resolve angular ambiguity in the coarse scanning stage, leading to a higher false detection probability and directly impacting the initial values ​​for subsequent fine estimation. Therefore, beam scanning schemes applied to non-uniform distributed coherent arrays still rely on dense search operations involving finely dividing the angular space. Furthermore, node position optimization methods used to suppress grating lobe levels further increase the complexity of the system scheme. While sparse reconstruction algorithms based on compressed sensing theory effectively reduce the number of beam scans through dimensionality reduction observations, their reliance on the CVX toolkit for solving convex optimization problems results in high computation time due to their high complexity, thus failing to significantly improve the angle estimation efficiency of non-uniform distributed arrays. Summary of the Invention

[0003] In view of this, the main objective of the embodiments of the present invention is to provide a method and apparatus for angle measurement of a spatially non-uniform distributed coherent array, in order to solve at least one of the problems of the prior art. The present invention can improve the angle measurement efficiency of a non-uniform distributed coherent array.

[0004] To achieve the above objectives, one aspect of the present invention provides a method for angle measurement using a spatially non-uniform distributed coherent array, comprising the following steps:

[0005] The receiver gain is estimated for the target range cell to obtain the receiver gain;

[0006] Based on the received gain, establish the spatial sampling vector of the target range unit;

[0007] The adaptive radiation pattern vector is obtained based on the main beam center angle, the main beam left boundary angle, and the main beam right boundary angle.

[0008] Construct a pattern matching matrix based on the adaptive pattern vector;

[0009] The correlation coefficient spectrum is obtained based on the column vectors of the pattern matching matrix and the spatial sampling vector;

[0010] Obtain the correlation angle corresponding to the maximum value in the correlation coefficient spectrum to obtain the target angle estimate.

[0011] In some embodiments, estimating the receiver gain of the target range cell to obtain the receiver gain includes the following steps:

[0012] Based on each node of the non-uniform distributed coherent array, the inter-node steering vector and the intra-node steering vector are obtained to obtain the spatial steering vector;

[0013] Based on the spatial guidance vector, the guidance vector matrix is ​​obtained;

[0014] The first signal matrix is ​​obtained based on the target signal vector and interference signal vector received by the phase center of the first node;

[0015] Based on the steering vector matrix, the first signal matrix, and the noise signals received by each spatial channel, the source signal matrix received by the non-uniform distributed coherent array is obtained.

[0016] Based on the source incoming signal matrix, obtain the covariance matrix of the noise signal;

[0017] The matrix of the source echo signal is obtained from the distributed array data vector of the target range cell;

[0018] The receiving gain is obtained based on the distributed array data vector, the covariance matrix, the spatial steering vector, and the main beam center angle.

[0019] In some embodiments, the spatial steering vector is obtained by acquiring the inter-node steering vector and the intra-node steering vector based on each node of the non-uniformly distributed coherent array, including the following steps:

[0020] The first phase relationship of the received source echo signal at the phase center of each node of the non-uniform distributed coherent array is obtained to obtain the steering vector between the nodes;

[0021] The second phase relationship of the echo signal received by each array element in the node is obtained to obtain the steering vector in the node;

[0022] The spatial guidance vector is obtained based on the inter-node guidance vector and the intra-node guidance vector.

[0023] In some embodiments, obtaining the adaptive radiation pattern vector based on the main beam center angle, the main beam left boundary angle, and the main beam right boundary angle includes the following steps:

[0024] The single-node main lobe angle range is obtained based on the left boundary angle and the right boundary angle of the main beam.

[0025] According to a preset angle interval, sampling is performed within the angle range of the main lobe of the single node to obtain the sampling angle;

[0026] At the main beam center angle, obtain the gain value of the adaptive radiation pattern of the non-uniform distributed coherent array at the sampling angle;

[0027] The adaptive radiation pattern vector is obtained based on each of the aforementioned gain values.

[0028] In some embodiments, obtaining the correlation coefficient spectrum based on the column vectors of the pattern matching matrix and the spatial sampling vector includes the following steps:

[0029] The column vectors of the orientation pattern matching matrix are correlated with the spatial sampling vectors column by column to obtain the correlation coefficients;

[0030] The correlation coefficient spectrum is obtained based on each of the aforementioned correlation coefficients.

[0031] In some embodiments, the formula used to obtain the correlation coefficient by correlating the column vectors of the orientation pattern matching matrix with the spatial sampling vector column by column includes:

[0032]

[0033] In the formula, ρ d This represents the d-th correlation coefficient, where d = 1, 2, ..., N. Sample N Sample ζ represents the total number of samples; ζ represents the spatial sampling vector; ζ i v represents the i-th element of the spatial sampling vector; v represents the column vector of the pattern matching matrix; v i Represents the i-th element of the pattern matching matrix; E(·) represents the expected value; N Beam This indicates the total number of beam scans.

[0034] To achieve the above objectives, another aspect of the present invention provides a spatially non-uniform distributed coherent array angle measuring device, the device comprising:

[0035] The first module is used to estimate the receiving gain of the target range cell to obtain the receiving gain;

[0036] The second module is used to establish the spatial sampling vector of the target range unit based on the receiving gain;

[0037] The third module is used to obtain the adaptive radiation pattern vector based on the main beam center angle, the main beam left boundary angle, and the main beam right boundary angle;

[0038] The fourth module is used to construct a pattern matching matrix based on the adaptive pattern vector;

[0039] The fifth module is used to obtain the correlation coefficient spectrum based on the column vectors of the pattern matching matrix and the spatial sampling vector;

[0040] The sixth module is used to obtain the correlation angle corresponding to the maximum value in the correlation coefficient spectrum, and to obtain the target angle estimate.

[0041] To achieve the above objectives, another aspect of the present invention provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the aforementioned spatial non-uniform distributed coherent array angle measurement method.

[0042] To achieve the above objectives, another aspect of the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned spatial non-uniform distributed coherent array angle measurement method.

[0043] To achieve the above objectives, another aspect of the present invention provides a computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium and execute the computer instructions, causing the computer device to perform the aforementioned spatial non-uniform distributed coherent array angle measurement method.

[0044] The embodiments of the present invention include at least the following beneficial effects: The present invention provides a spatial non-uniform distributed coherent array angle measurement method and apparatus. This scheme obtains the receiving gain by estimating the receiving gain of the target range cell; establishes the spatial sampling vector of the target range cell based on the receiving gain; obtains an adaptive radiation pattern vector based on the main beam center angle, the main beam left boundary angle, and the main beam right boundary angle; constructs a radiation pattern matching matrix based on the adaptive radiation pattern vector; obtains a correlation coefficient spectrum based on the column vectors of the radiation pattern matching matrix and the spatial sampling vector; and obtains the correlation angle corresponding to the maximum value in the correlation coefficient spectrum as the target angle estimate after deblurring, effectively reducing the number of beam scans and improving the angle measurement efficiency of large aperture non-uniform distributed coherent arrays. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 This is a flowchart of the spatial non-uniform distributed coherent array angle measurement method provided in the embodiments of the present invention;

[0047] Figure 2 This is a diagram of a non-uniform distributed coherent array structure provided in an embodiment of the present invention;

[0048] Figure 3 This is a schematic diagram of the pattern matching matrix of the non-uniform distributed array pattern matching angle measurement algorithm provided in this embodiment of the invention under constraint 1;

[0049] Figure 4 This is a schematic diagram of the correlation coefficient spectrum of the non-uniform distributed array pattern matching angle measurement algorithm provided in this embodiment of the invention under constraint 1;

[0050] Figure 5 This is a schematic diagram of the pattern matching matrix of the non-uniform distributed array pattern matching angle measurement algorithm provided in this embodiment of the invention under constraint condition 2;

[0051] Figure 6 This is a schematic diagram of the correlation coefficient spectrum of the non-uniform distributed array pattern matching angle measurement algorithm provided in this embodiment of the invention under constraint condition 2;

[0052] Figure 7 This is a comparative diagram showing the unambiguity probabilities of different algorithms provided in this embodiment of the invention for a fixed target, under conditions of no interference, as the number of search beams changes;

[0053] Figure 8 This is a comparative diagram showing the defuzzification probabilities of different algorithms provided in this embodiment of the invention for a fixed target and in the presence of main lobe interference, as the number of search beams changes.

[0054] Figure 9 This is a comparative diagram showing the target angle estimation unambiguity probability of different algorithms provided in the embodiments of the present invention as the input signal-to-noise ratio changes;

[0055] Figure 10 This is a schematic diagram comparing the target angle estimation accuracy of different algorithms provided in the embodiments of the present invention as the input signal-to-noise ratio changes;

[0056] Figure 11This is a schematic diagram of the angle measurement process of the non-uniform distributed array pattern matching angle measurement algorithm provided in the embodiment of the present invention;

[0057] Figure 12 This is a schematic diagram of the hardware structure of the electronic device provided in an embodiment of the present invention. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this invention; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this invention as detailed in the appended claims.

[0059] It should be noted that although functional modules are divided in the system diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the system or the order in the flowchart. The terms "first / S100" and "second / S200" in the specification, claims, and the foregoing drawings may be used herein to describe various concepts, but unless specifically stated otherwise, these concepts are not limited by these terms. These terms are used only to distinguish one concept from another. For example, first information may also be referred to as second information without departing from the scope of the embodiments of the invention, and similarly, second information may also be referred to as first information. Depending on the context, the words "if" or "when" as used herein may be interpreted as "when," "in response to a determination," or "in the event of a determination."

[0060] The terms “at least one,” “multiple,” “each,” “any,” etc., used in this invention, “at least one” includes one, two, or more than two; “multiple” includes two or more than two; “each” refers to each of the corresponding multiple; and “any” refers to any one of the multiple.

[0061] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein is for the purpose of describing embodiments of the invention only and is not intended to limit the invention.

[0062] Before providing a detailed description of the embodiments of the present invention, some of the nouns and terms involved in the embodiments of the present invention will be explained first. The nouns and terms involved in the embodiments of the present invention are subject to the following interpretations.

[0063] Non-uniform distributed coherent arrays refer to array structures in which multiple phased array antennas operate as independent nodes, exhibiting a non-uniform spatial arrangement. The phase centers of the nodes satisfy a linear phase relationship to achieve coherent joint processing of signals received by multiple nodes. Non-uniform distributed coherent arrays offer the advantage of high-precision angle measurement due to their large synthetic aperture. Among the key characteristics of non-uniform distributed coherent arrays, "non-uniform distribution" refers to the unequal spacing between nodes, following a random spatial distribution layout; "coherence" refers to the definite phase relationship of the received source echo signals at each node, sharing a unified phase reference, typically using the phase center of the first node as the phase reference.

[0064] An antenna pattern is a spatial distribution function describing the radiation gain or reception gain of an array antenna. Based on the magnitude of the gain, it is classified into main lobes and side lobes, etc., and is obtained by weighted summation of weighted vectors over each array element. The process of weighting the array with weighted vectors possessing a specific beam center to synthesize the pattern is called beamforming. Conventional beamforming uses the array steering vector in the incoming direction as the weighting vector. Under the Fraunhofer zone far-field theoretical model, the normalized pattern of the antenna depends only on the incident angle of the received signal.

[0065] Adaptive beamforming is a technique that adjusts the radiation pattern of an array antenna in real time. By optimizing the element weights, it aligns the main lobe of the radiation pattern with the target while simultaneously creating nulls in the direction of interference. Optimization criteria include minimum variance distortion-free response criteria or linearly constrained minimum variance criteria. Adaptive beamforming technology offers electronic countermeasures advantages such as suppressing strong interference and improving the signal-to-interference-plus-noise ratio.

[0066] Single-node main lobe width: The main lobe of the beamform pattern formed by a single independent node in a distributed array is called the single-node main lobe. The beamwidth of the single-node main lobe is defined as the half-power beamwidth angle range within which the maximum gain of the main lobe decreases by 3dB.

[0067] Distributed array synthesized main lobe width: Multiple nodes in a distributed coherent array share the same phase reference. The distributed array steering vector is obtained based on the phase relationships between the nodes, and then a computable distributed array radiation pattern is formed through multi-node joint beamforming. The main lobe in the distributed array radiation pattern is the synthesized main lobe of the distributed array, and its beamwidth is defined as the angular range from the maximum gain of the main lobe to the half-power point, where the gain drops by 3dB. Compared to the main lobe width of a single node, the synthesized main lobe width of a distributed array is much narrower due to the larger aperture of the multi-node coherent array.

[0068] like Figure 1 As shown, this embodiment of the invention provides a method for angle measurement using a spatially non-uniform distributed coherent array, which may include, but is not limited to, steps S100 to S600:

[0069] Step S100: Estimate the receiving gain of the target range cell to obtain the receiving gain;

[0070] Step S200: Based on the received gain, establish the spatial sampling vector of the target range unit;

[0071] Step S300: Obtain the adaptive radiation pattern vector based on the main beam center angle, the main beam left boundary angle, and the main beam right boundary angle;

[0072] Step S400: Construct a pattern matching matrix based on the adaptive pattern vector;

[0073] Step S500: Obtain the correlation coefficient spectrum based on the column vectors of the pattern matching matrix and the spatial sampling vector;

[0074] Step S600: Obtain the correlation angle corresponding to the maximum value in the correlation coefficient spectrum to obtain the target angle estimate.

[0075] In steps S100 to S600 of some embodiments, during each beam scan, the receiving gain of the target range cell is estimated, and the adaptive radiation pattern of the non-uniform distributed coherent array is calculated. After multiple beam scans, the receiving gain data of the target range cell forms a spatial sampling vector, and the adaptive radiation patterns of the non-uniform distributed coherent array at different beam centers are arranged into a radiation pattern matching matrix. The correlation coefficient is calculated column by column of the spatial sampling vector and the radiation pattern matching matrix, so that the non-uniform grating lobe characteristics in the spatial range near the target are correlated and matched to obtain the correlation coefficient spectrum. The maximum angle index of the correlation coefficient spectrum, i.e., the maximum correlation angle, is used as the target angle estimate after deblurring. This utilizes the specificity of the radiation pattern grating lobe characteristics of the non-uniform distributed coherent array to achieve angle estimation deblurring. Compared with existing dense search schemes, the embodiments of the present invention replace the traditional method of using the maximum index angle of the single beam scan as the angle estimate, establishes a deblurring basis for spatial grating lobe characteristic correlation matching, effectively reduces the number of beam scans, and improves the beam scanning efficiency of large-aperture non-uniform distributed coherent arrays.

[0076] To provide a detailed description of the spatial non-uniform distributed coherent array angle measurement method according to embodiments of the present invention, a non-uniform distributed coherent array structural model and an echo signal model are established. For example, consider a non-uniform distributed coherent array composed of N nodes with uneven spacing, where each node contains M array elements, and the element spacing is... λ is the signal wavelength, therefore the number of spatial channels Q = NM. All nodes are linearly arranged along the x-axis, with the first element serving as its reference element, also called the phase center. The reference element (i.e., the phase center) of the first node is located at the origin, and the phase centers of the remaining nodes are located at x... n,mWhere n = 1, 2, ..., N; m = 1, 2, ..., M. The coherent synthesis aperture of N nodes is D = x N,M The structure of a non-uniformly distributed coherent array is as follows: Figure 2 As shown. The distance from the information source in space to each reference array element is r. n The angle between the source line of sight and the array axis is The distance from the far-field source to the non-uniformly distributed coherent array and the coherent synthesis aperture satisfy the Fraunhofer far-field assumption, expressed as:

[0077]

[0078] For far-field sources, the electromagnetic wave signals received by the distributed array are modeled as plane waves, where the angle between the incoming wave signal and each node is... Satisfying Relationships Then the spatial angle of the non-uniformly distributed coherent array receiving signal is: The source echo signal.

[0079] In some embodiments, step S100 may include, but is not limited to, steps S110 to S170:

[0080] Step S110: Based on each node of the non-uniform distributed coherent array, obtain the inter-node steering vector and the intra-node steering vector to obtain the spatial steering vector.

[0081] Step S120: Obtain the steering vector matrix based on the spatial steering vector;

[0082] Step S130: Obtain the first signal matrix based on the target signal vector and interference signal vector received by the phase center of the first node;

[0083] Step S140: Based on the steering vector matrix, the first signal matrix, and the noise signals received by each spatial channel, the source incoming signal matrix received by the non-uniform distributed coherent array is obtained.

[0084] Step S150: Obtain the covariance matrix of the noise signal based on the source incoming signal matrix;

[0085] Step S160: Obtain the matrix of the source echo signal in the distributed array data vector of the target range cell;

[0086] Step S170: Obtain the receiving gain based on the distributed array data vector, the covariance matrix, the spatial steering vector, and the main beam center angle.

[0087] In some embodiments, step S110 may include, but is not limited to, steps S111 to S113:

[0088] Step S111: Obtain the first phase relationship of the echo signal received by the phase center of each node of the non-uniform distributed coherent array, and obtain the steering vector between the nodes;

[0089] Step S112: Obtain the second phase relationship of the source echo signal received by each array element in the node, and obtain the steering vector in the node;

[0090] Step S113: Obtain the spatial guidance vector based on the inter-node guidance vector and the intra-node guidance vector.

[0091] In step S111 of some embodiments, for the echo signal of the target source or the echo signal of the interfering source, the phase relationship of the echo signal received by the phase center of each node is the inter-node steering vector a. a The expression is:

[0092]

[0093] In the formula, a a Represents the inter-node steering vector; x 1,1 ,…,x N-1,1 This indicates the position of the phase center of each node; denoted by λ, representing the spatial angle received by a non-uniformly distributed coherent array; e represents the base of the natural logarithm; j represents the imaginary unit; λ represents the signal wavelength; [·] T This indicates the transpose operation.

[0094] In step S112 of some embodiments, for the echo signal of the target source or the echo signal of the interfering source, the phase relationship of the echo signal received by each array element in the node from the source is, i.e., the steering vector a in the node. e The expression is:

[0095]

[0096] In the formula, a e This represents the guiding vector within the node.

[0097] In step S113 of some embodiments, based on the inter-node guiding vector a a and the intranode steering vector a e The spatial steering vector a of the non-uniform distributed coherent array can be obtained. s The expression is:

[0098]

[0099] In the formula, a s Represents the spatial guidance vector; It represents the Kronecker product.

[0100] In step S120 of some embodiments, when the information source is the target information source, the non-uniform distributed coherent array receiving spatial angle in equations (2) and (3) is... The corresponding spatial steering vector for the non-uniform distributed coherent array is a. s,T When the signal source is an interfering signal source, the non-uniform distributed coherent array receiving spatial angle in equations (2) and (3) is... The corresponding spatial steering vector for the non-uniform distributed coherent array is a. s,J The expression for the guiding vector matrix A is:

[0101] A = [a s,T a s,J (5)

[0102] In step S130 of some embodiments, the target signal vector and interference signal vector received by the phase center of the node at the origin of the non-uniform distributed coherent array, i.e., the phase center of the first node, are s and s respectively. T and s J Then the expression for the first signal matrix S is:

[0103]

[0104] In step S140 of some embodiments, the noise signal received by each independent spatial channel is N. Combining the steering vector matrix and the first signal matrix, the expression for the incoming signal matrix X of the non-uniform distributed coherent array receiving spatial source can be obtained as follows:

[0105] X = AS + N (7)

[0106] In step S150 of some embodiments, the covariance matrix R of the interference noise signal JN The expression is:

[0107]

[0108] In the formula, E[·] represents the expected value; (·) H Indicates the conjugate transpose operation; X JN This represents the interference noise signal matrix contained in the incoming signal matrix of the spatial information source.

[0109] To suppress interference and improve the target output signal-to-interference-plus-noise ratio (SNR), non-uniform distributed coherent arrays employ adaptive beamforming techniques to minimize the receiver gain in the interference angular direction. Based on the linearly constrained minimum variance criterion, the optimal weight vector w of the non-uniform distributed coherent array... opt The calculation formula is:

[0110]

[0111] In the formula, w opt Represents the optimal weight vector; Indicates the center angle of the main beam of a non-uniformly distributed coherent array; [·] -1 This indicates the inverse operation.

[0112] In steps S160 to S170 of some embodiments, during the b-th beam scan, after the non-uniform distributed coherent array received signal undergoes matched filtering and adaptive beamforming, constant false alarm rate (CFAR) detection and sidelobe concealment detection are also performed. The receiving gain is estimated for the effective target range cell l that passes CFAR detection and sidelobe concealment detection, and the following expression is given:

[0113]

[0114] in,

[0115]

[0116] In the formula, x l ξ represents the distributed array data vector of the source echo signal matrix in the target range cell; b This represents the receiver gain of the b-th beam scan, where b = 1, 2, ..., N. Beam N Beam E1 and E2 represent the total number of beam scans divided into sections; E1 and E2 are intermediate parameters.

[0117] Optionally, the receiver gain estimate is subject to the following constraints, expressed as follows:

[0118]

[0119] In the formula, G thre To measure the target receiver gain threshold within the grating lobe. During beam scanning, when the target angle is located in the grating lobe region with higher gain, and the estimated value ξ... b >G thre At this time, the target receiving gain estimate remains the result of equation (10). If the target signal is received from the sidelobe region of the distributed array, the gain in the target angular direction is low, and the target receiving gain estimate is used with a threshold G. thre Replacement. This step ensures the overall accuracy of the receiver gain estimation during beam scanning by retaining the target receiver gain estimation result of the grating lobe and replacing the target receiver gain estimation value of the side lobe. The output signal-to-noise ratio of the target signal after being received by the distributed array in the low gain angle region is low. Affected by noise, the target receiver gain estimation result is inaccurate. In addition, during the scanning process, the target angle changes relative to the main beam pointing of the distributed array. Therefore, constraint (13) specifically describes the characteristics of the grating lobe gain and grating lobe angle spacing in the spatial domain near the target.

[0120] In some embodiments, the left and right boundary angles of the main beam of a single node in a non-uniform distributed coherent array are respectively... and The range of main lobe angles at a single node is Within the single-node main lobe angle range, the main lobe width is synthesized using a non-uniformly distributed coherent array. Beam scanning is performed for the search interval, and the total number of beam scans is:

[0121]

[0122] In the formula, This indicates rounding down to the nearest integer.

[0123] The center angle of the b-th beam for:

[0124]

[0125] In the formula, b = 1, 2, ..., N Beam .

[0126] In step S200 of some embodiments, the receiving gain is estimated at different beam center angles, the gain change near the target direction is recorded, and the spatial sampling vector ζ of the target is obtained, expressed as:

[0127]

[0128] In some embodiments, step S300 may include, but is not limited to, steps S310 to S340:

[0129] Step S310: Based on the left boundary angle of the main beam and the right boundary angle of the main beam, obtain the single-node main lobe angle range;

[0130] Step S320: Sample the single-node main lobe angle within the preset angle interval to obtain the sampling angle;

[0131] Step S330: At the center angle of the main beam, obtain the gain value of the adaptive pattern of the non-uniform distributed coherent array at the sampling angle;

[0132] Step S340: Obtain the adaptive radiation pattern vector based on each of the gain values.

[0133] In some embodiments, steps S310 to S320 are performed based on the left boundary angle of the main beam. and the right boundary angle of the main beam The range of main lobe angles at a single node is obtained as follows: At preset angle intervals Sampling is performed within the main lobe angle range of a single node to obtain a sampled angle vector used to calculate the radiation pattern. The preset angle interval is smaller than the width of the synthesized main lobe of the non-uniform distributed coherent array. Then each sampling angle Represented as:

[0134]

[0135] In the formula, d = 1, 2, ..., N Sample N Sample This represents the total number of samples. The radiation pattern angle vector ψ is represented as:

[0136]

[0137] In steps S330 to S340 of some embodiments, during the b-th beam scan, at the main beam center angle Below, the adaptive radiation pattern of a non-uniform distributed coherent array is obtained at the sampling angle. Gain value Then we have the following expression:

[0138]

[0139] In the formula, Q represents the number of spatial channels in the distributed array, and its value is the spatial steering vector a. s The length.

[0140] Alternatively, corresponding to the constraints in equation (13), the adaptive pattern function has the following constraints, expressed as follows:

[0141]

[0142] During the b-th beam scan, the adaptive pattern vector p of the non-uniformly distributed coherent array b The expression is:

[0143]

[0144] In step S400 of some embodiments, the adaptive pattern vector p calculated for different beam centers is... b After arranging the patterns, the following pattern matching matrix M is obtained:

[0145]

[0146] In some embodiments, the adaptive pattern of the non-uniform distributed coherent array possesses the following grating lobe characteristics: irregular and non-uniform grating lobe gain, and unequal angular spacing between adjacent grating lobes. Features such as grating lobe gain and grating lobe spacing near the target angle differ from those near another ambiguous angle. In this embodiment, the non-uniform distributed coherent array uses the synthesized main lobe width as the scanning search interval, and the spatial sampling vector ζ completely records the grating lobe spacing and gain information near the target angle. The pattern matching matrix M is essentially also a representation of spatial gain, and each column of matrix M records the receiving gain of the adaptive pattern at the target angle for different beam centers, sharing the same essence as the spatial sampling vector ζ.

[0147] In some embodiments, step S500 may include, but is not limited to, steps S510 to S520:

[0148] Step S510: Correlate the column vectors of the pattern matching matrix with the spatial sampling vector column by column to obtain the correlation coefficient;

[0149] Step S520: Obtain the correlation coefficient spectrum based on each of the correlation coefficients.

[0150] In step S510 of some embodiments, the spatial sampling vector ζ is correlated with the column vector v of the pattern matching matrix M, and the correlation coefficient between the two vectors is calculated, resulting in the following expression:

[0151]

[0152] In the formula, ρ d This represents the d-th correlation coefficient, where d = 1, 2, ..., N. Sample N Sample ζ represents the total number of samples; ζ represents the spatial sampling vector; ζ i v represents the i-th element of the spatial sampling vector; v represents the column vector of the pattern matching matrix; v i Represents the i-th element of the pattern matching matrix; E(·) represents the expected value; N Beam This indicates the total number of beam scans.

[0153] In step S520 of some embodiments, based on the various correlation coefficients, the expression for the correlation coefficient spectrum ρ can be obtained as follows:

[0154]

[0155] In step S600 of some embodiments, the target angle estimate is taken as the angle corresponding to the maximum value in the correlation coefficient spectrum, i.e., the maximum correlation angle. Then we have the following expression:

[0156]

[0157] refer to Figure 3 The process of correlation matching using spatial sampling vectors and pattern matching matrices in this embodiment of the invention is as follows: Figure 3 As shown. The distributed array receives digital signals and performs beam scanning after matched filtering. During each scan, the echo signal undergoes adaptive beamforming, constant false alarm detection, and sidelobe concealment detection, and extracts multiple range cells that may be real targets or false alarms. According to equations (10) and (19), all detection cells can calculate spatial sampling data and radiation pattern vectors. According to equations (16) and (22), after beam scanning is completed, all detection cells generate a spatial sampling vector and a radiation pattern matching matrix. By statistically analyzing the range cells that pass detection in multiple scans, false alarms are eliminated, and real target range cells are retained. Finally, the sampling sequence of the target range cells and the radiation pattern matching matrix are traversed and correlated, and the target angle is deblurred by taking the maximum correlation angle.

[0158] To achieve the goal of outputting a deambiguous spectrum with the same angular range and accuracy, existing dense beam search methods for distributed arrays output signal-to-noise ratio or receiver gain estimates during successive scans and seek the angle index that produces the maximum value in a single output to achieve angle estimation. This invention establishes an angle deambiguity basis based on the correlation matching of spatial domain grating lobe characteristics near the target, significantly reducing the requirement for the number of beam scans compared to dense search methods. The angular range of the spectrum is used as the main lobe width of a single node. Angle accuracy is As a prerequisite, the beam scanning interval of dense search methods needs to be [value missing]. The beam scanning interval of the pattern matching method of the present invention is the main lobe width of the distributed array synthesis. When the beam scanning angle interval of the two methods satisfies the relationship

[0159]

[0160] In the formula, K scan >1. The beam scan number of the pattern matching angle measurement algorithm of this invention is reduced to that of a dense search method. Therefore, the method of the present invention improves the beam scanning rate, thereby improving the efficiency of angle measurement of non-uniform distributed coherent arrays.

[0161] To verify the effectiveness of the algorithm of this invention and evaluate its performance, an angle measurement performance experiment was conducted. The defuzzification probability and angle measurement performance of the algorithm were investigated and compared with dense search methods. The defuzzification probability is calculated as: the number of successful defuzzifications M... S With the number of Monte Carlo trials M C The ratio of M, where M S ≤MC The criterion for successful deblurring is that the deviation between the estimated angle and the true target angle is no greater than the width of the main lobe synthesized by the distributed array. Angle measurement performance is measured by the root mean square error (RMSE) of the angle estimates from all successful deblurring experiments, calculated as follows:

[0162]

[0163] In the formula, This is the sequence number of the i-th successful unfuzzy test.

[0164] The experimental setup is as follows: the signal frequency is 1 GHz. The node positions of the non-uniform distributed array are 0, 90λ, 160λ, and 200λ; the number of array element channels within a node is 4, and the element spacing is half a wavelength; the algorithm of this invention requires multiple beam scans, with the initial beam center at 90°. ° Target angle In single-node main lobe width The scanning beam spacing is equal to the main lobe width of the distributed array synthesis. The angular interval of the radiation pattern is This determines the accuracy of the correlation coefficient spectrum output by the method of this invention for deblurring. Additionally, considering that the scene includes a single-node main lobe interference, its angle... The input signal-to-noise ratio is 0dB, and the input interference-to-noise ratio is 20dB. The number of Monte Carlo trials is M. C =500.

[0165] The first part of the experiment demonstrates the basis for the angular de-ambiguity resolution achieved by the method of this invention. The number of beam scans, N... Beam When the threshold G is 50, thre When the value is -6dB, the pattern matching matrix and correlation coefficient spectrum calculated by the method of this invention are as follows: Figure 4 and Figure 5 As shown. When the threshold G thre When the value is -3dB, the pattern matching matrix and correlation coefficient spectrum are as follows: Figure 6 and Figure 7 As shown. The maximum correlation angle of the correlation coefficient spectrum effectively indicates the direction of target arrival. Extra peaks in the correlation spectrum do not affect the determination of the target angle, because different target angles will construct their own correlation spectra for estimation. Secondary peaks in the correlation spectrum affect the confidence level of the target angle estimation: when G... thre The larger the value of G, the higher the reliability of indicating the target direction. However, higher G values... thre It will filter out targets with lower gain, therefore G thre The value of should be determined by balancing reliability and practicality; based on this experiment, it is taken as -6dB to -3dB.

[0166] The second part analyzes the deambiguity performance of the proposed method under both interference-free and interference-containing conditions, and compares it with the dense beam scanning method that uses the receiver gain estimate as the output of a single scan. To ensure that the accuracy of the spectrum output by different methods remains consistent, the search interval of the dense search method is [insert value here]. The beam scanning angle shifts from the initial beam center to the target angle direction. Figure 8 and Figure 9 This demonstrates the unambiguity probabilities of different methods for a fixed target, varying with the number of scanning beams. For easier comparison of the number of beams scanned, the x-axis of the dense search method is shown on... Figure 8 and Figure 9 The following is shown below, while the x-axis of the method of this invention is in Figure 8 and Figure 9 The top of the display. Figure 8 The results show that, with a defuzzification probability of 95.2%, the dense search method requires 124 beam scans, while the method of this invention requires only 18 beam scans, resulting in a significant improvement in defuzzification rate. Figure 9 The results show that when main lobe interference is present and the radiation pattern is distorted due to grating lobe pointing interference, the number of beam scans in the method of the present invention increases to 30, but still greatly reduces the number of beam scans. Figure 10 The deblurring probability is shown as the signal-to-noise ratio (SNR) varies under different conditions. Under low SNR conditions, the method of this invention has a higher deblurring probability than the dense search method.

[0167] The third part analyzes the angle measurement performance of the method of the present invention under both interference-free and interference-containing conditions. Figure 11 The results demonstrate the angle measurement accuracy of different algorithms as the input signal-to-noise ratio (SNR) changes. The results show that, under interference-free conditions, the proposed method outperforms the dense search algorithm in angle measurement accuracy at low SNR. Furthermore, compared to the interference-free condition, the angle measurement performance of the proposed method is somewhat reduced by interference, but it still demonstrates its advantage in angle measurement accuracy compared to the traditional dense search algorithm.

[0168] This invention also provides a spatially non-uniform distributed coherent array angle measurement device, which can implement the above-described spatially non-uniform distributed coherent array angle measurement method. The device includes:

[0169] The first module is used to estimate the receiving gain of the target range cell to obtain the receiving gain;

[0170] The second module is used to establish the spatial sampling vector of the target range unit based on the receiving gain;

[0171] The third module is used to obtain the adaptive radiation pattern vector based on the main beam center angle, the main beam left boundary angle, and the main beam right boundary angle;

[0172] The fourth module is used to construct a pattern matching matrix based on the adaptive pattern vector;

[0173] The fifth module is used to obtain the correlation coefficient spectrum based on the column vectors of the pattern matching matrix and the spatial sampling vector;

[0174] The sixth module is used to obtain the correlation angle corresponding to the maximum value in the correlation coefficient spectrum, and to obtain the target angle estimate.

[0175] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0176] This invention also provides an electronic device, which includes a processor and a memory. The memory stores a computer program, and the processor executes the computer program to implement the aforementioned spatial non-uniform distributed coherent array angle measurement method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0177] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0178] refer to Figure 12 , Figure 12 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes:

[0179] The processor 701 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present invention.

[0180] The memory 702 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 702 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 702 and is called and executed by the processor 701 to execute the spatial non-uniform distributed coherent array angle measurement method of the embodiments of this invention.

[0181] The input / output interface 703 is used to implement information input and output;

[0182] The communication interface 704 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0183] Bus 705 transmits information between various components of the device (e.g., processor 701, memory 702, input / output interface 703, and communication interface 704);

[0184] The processor 701, memory 702, input / output interface 703, and communication interface 704 are connected to each other within the device via bus 705.

[0185] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described spatial non-uniform distributed coherent array angle measurement method.

[0186] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0187] This invention also provides a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium and execute the computer instructions, causing the computer device to perform the aforementioned spatial non-uniform distributed coherent array angle measurement method.

[0188] In summary, the spatial non-uniform distributed coherent array angle measurement method and apparatus of this invention is based on the characteristic that the grating lobe gain and spacing of the distributed array pattern are non-uniform. Utilizing the specificity of the non-uniform grating lobe characteristics in the spatial region near the target, correlation matching is performed on the grating lobe characteristics in the spatial region near the target to achieve unambiguous angle estimation. The key steps of the non-uniform distributed array correlation matching on the grating lobe characteristics in the spatial region near the target are as follows: the distributed array performs beam scanning within the main lobe width of a single node to estimate the receiving gain of the target element, forming a spatial sampling vector. The adaptive pattern of the distributed array with different beam centers is calculated and arranged into a pattern matching matrix, where the beam scanning interval is the width of the synthesized main lobe of the distributed array, and the pattern angle interval is much smaller than the beam scanning interval. The correlation coefficient spectrum is obtained by traversing the spatial sampling vector and the pattern matching matrix column by column, and the maximum correlation angle is sought to obtain the unambiguous angle estimate of the target.

[0189] This invention establishes a specific grating lobe characteristic correlation mechanism by combining the radiation pattern grating lobe characteristics of a non-uniform distributed array. The target angle is estimated by seeking the maximum correlation angle of the grating lobe characteristics after beam scanning, while saving the number of beam scans and improving search efficiency.

[0190] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order shown in the operation diagrams. For example, depending on the functions / operations involved, two consecutively shown blocks may actually be executed substantially simultaneously, or the blocks may sometimes be executed in reverse order. Furthermore, the embodiments presented and described in the flowcharts of this invention are provided by way of example to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is altered and sub-operations described as part of a larger operation are executed independently.

[0191] Furthermore, although the invention has been described in the context of functional modules, it should be understood that, unless otherwise stated, one or more of the described functions and / or features may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the invention. Rather, given the properties, functions, and internal relationships of the various functional modules in the apparatus disclosed herein, the actual implementation of the module will be understood within the scope of conventional skill of an engineer. Therefore, those skilled in the art can implement the invention as set forth in the claims using ordinary techniques without excessive experimentation. It is also understood that the specific concepts disclosed are merely illustrative and not intended to limit the scope of the invention, which is determined by the full scope of the appended claims and their equivalents.

[0192] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0193] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0194] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0195] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0196] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0197] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

[0198] The above is a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the embodiments described. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of the present invention.

Claims

1. A spatially non-uniform distributed coherent array angle measurement method, characterized in that, Includes the following steps: The receiver gain is estimated for the target range cell to obtain the receiver gain; Based on the received gain, establish the spatial sampling vector of the target range unit; The adaptive radiation pattern vector is obtained based on the main beam center angle, the main beam left boundary angle, and the main beam right boundary angle. Construct a pattern matching matrix based on the adaptive pattern vector; The correlation coefficient spectrum is obtained based on the column vectors of the pattern matching matrix and the spatial sampling vector; Obtain the correlation angle corresponding to the maximum value in the correlation coefficient spectrum to obtain the target angle estimate.

2. The spatial non-uniform distributed coherent array angle measurement method according to claim 1, characterized in that, The estimation of the receiving gain of the target range cell to obtain the receiving gain includes the following steps: Based on each node of the non-uniform distributed coherent array, the inter-node steering vector and the intra-node steering vector are obtained to obtain the spatial steering vector. Based on the spatial guidance vector, the guidance vector matrix is ​​obtained; The first signal matrix is ​​obtained based on the target signal vector and interference signal vector received by the phase center of the first node; Based on the steering vector matrix, the first signal matrix, and the noise signals received by each spatial channel, the source signal matrix received by the non-uniform distributed coherent array is obtained. Based on the source incoming signal matrix, obtain the covariance matrix of the noise signal; The matrix of the source echo signal is obtained from the distributed array data vector of the target range cell; The receiving gain is obtained based on the distributed array data vector, the covariance matrix, the spatial steering vector, and the main beam center angle.

3. The spatial non-uniform distributed coherent array angle measurement method according to claim 2, characterized in that, The step of obtaining the spatial steering vector by acquiring the inter-node steering vector and the intra-node steering vector based on each node of the non-uniformly distributed coherent array includes the following steps: The first phase relationship of the received source echo signal at the phase center of each node of the non-uniform distributed coherent array is obtained to obtain the steering vector between the nodes; The second phase relationship of the echo signal received by each array element in the node is obtained to obtain the steering vector in the node; The spatial guidance vector is obtained based on the inter-node guidance vector and the intra-node guidance vector.

4. The spatial non-uniform distributed coherent array angle measurement method according to claim 1, characterized in that, The process of obtaining the adaptive radiation pattern vector based on the main beam center angle, the main beam left boundary angle, and the main beam right boundary angle includes the following steps: The single-node main lobe angle range is obtained based on the left boundary angle and the right boundary angle of the main beam. According to a preset angle interval, sampling is performed within the angle range of the main lobe of the single node to obtain the sampling angle; At the main beam center angle, obtain the gain value of the adaptive radiation pattern of the non-uniform distributed coherent array at the sampling angle; The adaptive radiation pattern vector is obtained based on each of the aforementioned gain values.

5. The spatial non-uniform distributed coherent array angle measurement method according to claim 1, characterized in that, The step of obtaining the correlation coefficient spectrum based on the column vectors of the pattern matching matrix and the spatial sampling vector includes the following steps: The column vectors of the orientation pattern matching matrix are correlated with the spatial sampling vectors column by column to obtain the correlation coefficients; The correlation coefficient spectrum is obtained based on each of the aforementioned correlation coefficients.

6. The spatial non-uniform distributed coherent array angle measurement method according to claim 5, characterized in that, The method of correlating the column vectors of the orientation pattern matching matrix with the spatial sampling vector column by column to obtain the correlation coefficient uses the following formula: In the formula, ρ d This represents the d-th correlation coefficient, where d = 1, 2, ..., N. Sample N Sample ζ represents the total number of samples; ζ represents the spatial sampling vector; ζ i v represents the i-th element of the spatial sampling vector; v represents the column vector of the pattern matching matrix; v i Represents the i-th element of the pattern matching matrix; E(·) represents the expected value; N Beam This indicates the total number of beam scans.

7. A spatially non-uniform distributed coherent array angle measuring device, characterized in that, include: The first module is used to estimate the receiving gain of the target range cell to obtain the receiving gain; The second module is used to establish the spatial sampling vector of the target range unit based on the receiving gain; The third module is used to obtain the adaptive radiation pattern vector based on the main beam center angle, the main beam left boundary angle, and the main beam right boundary angle; The fourth module is used to construct a pattern matching matrix based on the adaptive pattern vector; The fifth module is used to obtain the correlation coefficient spectrum based on the column vectors of the pattern matching matrix and the spatial sampling vector; The sixth module is used to obtain the correlation angle corresponding to the maximum value in the correlation coefficient spectrum, and to obtain the target angle estimate.

8. An electronic device, characterized in that, Including the processor and memory; The memory is used to store programs; The processor executes the program to implement the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The storage medium stores a program that is executed by a processor to implement the method as described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 6.

Images