A channel correction method and device for resolving ambiguity of dual-target joint guidance vector

Abstract

The present invention relates to a channel correction method and device for resolving the ambiguity of a dual-target joint steering vector. The method comprises: first, obtaining a joint MVDR spectrum of a current single information source and an auxiliary single information source, and retaining two groups of azimuth estimation results corresponding to the two highest spectrum peaks for each estimation. Secondly, calculating the Euclidean distances between multiple estimated azimuths of the single information source and candidate azimuths, and selecting the smallest half of the distance values ​​and taking the average thereof to obtain the half Euclidean average distance, and the candidate azimuth with the smallest average distance is the estimated azimuth of the single information source. Then, according to the estimated azimuth of the single information source, the inherent array steering vector of the estimated azimuth in the sampled data is deducted to obtain a channel correction value obtained by the single information source. Finally, for the correction values ​​obtained by multiple single information sources, the median of the amplitude is taken to obtain the amplitude correction value, and the median of the phase is taken to obtain the phase correction value. The present invention overcomes the ambiguity of the dual-target joint steering vector, and the channel correction result is more stable.

Description

Technical Field

[0001] The present invention relates to the technical field of radar array channel correction, and in particular to a channel correction method and device for resolving dual-target joint guidance vector ambiguity. Background Art

[0002] Array radar can solve the target's position by scanning the airspace, which is the basis of phased array radar angle measurement. However, in actual systems, the array channel has uncertain amplitude and phase errors, which seriously degrades the performance of radar array angle measurement or even completely fails. In order to compensate for the amplitude and phase errors of the array channel, there are two solutions: cooperative source and non-cooperative source.

[0003] The idea of ​​cooperative source is to correct the channel through a signal source with known position. According to different technical approaches, it can be divided into three categories: beacon, transponder and target echo with known position. Beacon is realized by emitting a signal synchronized with the radar. Liu Shuai (2018) adopted this idea. The channel correction value measured by this method has high accuracy, but it is necessary to set up a beacon in the far field of the radar. The complex system is not conducive to business operation. The basic working process of the transponder is to first receive the direct wave signal of the radar, and then forward it back after distance and speed offset. Fang Fan (2015) described the design of such a high-frequency radar transponder based on direct digital frequency synthesis (Direct Digital Synthesis, abbreviated as: DDS). The characteristics of this method are similar to the beacon method. Although the accuracy of the channel correction value is high, the complex system is not conducive to engineering implementation. The idea of ​​using target echo with known position requires obtaining the true position of the target in the radar echo through other means. For example, the Automatic Identification System (AIS) can provide the position information of the ship. Zhao Chen (2020) extracted the channel correction value of the array through the echo of the ship with AIS information, and further obtained the directional distortion factor of the array channel. In general, the channel correction methods based on cooperative sources require additional equipment, which complicates the system structure and is not conducive to commercial operation.

[0004] The non-cooperative source approach does not require additional equipment and can directly extract channel correction values ​​from radar echoes. Huang Chao (2022), Fu Wei (2021), Chen Zezong (2020), etc. obtain the correction values ​​of array channels by optimizing multiple single signal sources of radar, but this type of optimization method has low computational efficiency and is prone to converge to local optimal values. Zhang Lan (2023) disclosed a method based on a dual-target joint steering vector. First, the common channel correction value is eliminated by two single signal sources, and then the true azimuth of the non-cooperative source is estimated using the dual-target joint steering vector, and the channel correction value can be further calculated. However, the dual-target joint steering vector is ambiguous, and two sets of target estimation results will appear, one of which is an erroneous azimuth estimation result. The best way to eliminate this ambiguity is to constrain the radar's detection angle of view to less than 180 degrees, but this limits the use scenario of this method. Alternatively, the mode value of multiple sets of estimation results is used to reduce the impact of the ambiguous azimuth estimation results, but nearly half of the samples used to obtain the mode value will have erroneous data, which will lead to insufficient stability of the estimation results.

[0005] In view of this, how to overcome the defects of the prior art and solve the problem that when the prior art uses a non-cooperative source to perform channel correction through a dual-target joint guidance vector method, a set of fuzzy values ​​will appear in the non-cooperative source orientation estimation, which will lead to unstable channel correction results, is a difficult problem to be solved in this technical field. Summary of the invention

[0006] In view of the technical problems in the traditional solution: when a non-cooperative source is used to perform channel correction through a dual-target joint steering vector method, a set of fuzzy values ​​will appear in the non-cooperative source azimuth estimation, which leads to unstable channel correction results. The embodiment of the present invention provides a channel correction method and device for solving the ambiguity of the dual-target joint steering vector. First, the joint minimum variance distortionless response (Minimum Variance Distortionless Response, abbreviated as: MVDR) spectrum of the current single source and the auxiliary single source is obtained, and two sets of azimuth estimation results corresponding to the highest two spectrum peaks are retained for each estimation. Secondly, the Euclidean distances between multiple estimated azimuths of the single source and the candidate azimuths are calculated, and the minimum half of the distance values ​​are selected and averaged to obtain the half Euclidean average distance. The candidate azimuth with the minimum average distance is the estimated azimuth of the single source. Then, according to the estimated azimuth of the single source, the inherent array steering vector of the estimated azimuth in the sampled data is deducted to obtain the channel correction value obtained by the single source. Finally, the correction values ​​obtained by multiple single sources are obtained by taking the median of the amplitude to obtain the amplitude correction value, and the median of the phase to obtain the phase correction value.

[0007] The purpose of the embodiment of the present invention is achieved through the following technical solutions:

[0008] In order to solve the above technical problems, in a first aspect, an embodiment of the present invention provides a channel correction method for resolving the ambiguity of a dual-target joint steering vector, comprising:

[0009] The joint MVDR spectrum of the first single source and the n auxiliary single sources is obtained using the dual-target joint steering vector method:

[0010] ;

[0011] in, represents the conjugate transpose, represents matrix inversion; are the possible target directions of two single sources, and their ranges include all azimuth directions, that is, ; is the joint steering vector, The joint covariance matrix constructed for single source No. 1 and auxiliary single source No. n;

[0012] Pick Two groups of angle estimation results corresponding to the two highest spectral peaks and , we get two possible directions of single source No. 1 , , one of which is the correct value and the other is the fuzzy value; similarly, after the No. 1 single source and N-1 auxiliary single sources are jointly estimated, the No. 1 single source finally obtains possible position estimates, half of which are correct and half are ambiguous;

[0013] Calculate the number 1 single source Position estimation results and candidate positions The Euclidean distance of Sequence:

[0014]

[0015] Sort the sequence from low to high and get :

[0016] ;

[0017] The reliability index of each candidate position is obtained, that is, the half Euclidean mean distance:

[0018] ;

[0019] in, The smaller the value, the more likely the candidate position is the true target position of the No. 1 single signal source; When the minimum value is taken , which is the estimated direction of single source No. 1 ;

[0020] Calculate the channel correction value obtained based on single source No. 1. First, deduct the inherent steering vector of the sampled signal of single source No. 1 to obtain :

[0021] ;

[0022] in, represents a diagonal matrix constructed with its posterior vector as diagonal elements; represents taking the conjugate of the signal; for Direction of the steering vector;

[0023] use The first row of data is Normalized to get :

[0024] ;

[0025] in, for The first row of data; Calculate the modulus of each element, and then take the median of each row to obtain the amplitude correction value of the single source estimate No. 1 ; Calculate the phase of each element, and then take the median of each row to obtain the phase correction value estimated for single source No. 1 Similarly, for other single sources, obtain their corresponding estimated amplitude correction values Phase correction value ;

[0026] Arrange the amplitude correction values ​​of all single source estimates into a matrix , which is The matrix is ​​expressed as: ;right Take the median of each row to get the final amplitude correction value ;

[0027] Arrange the phase correction values ​​of all single source estimates into a matrix , which is The matrix is ​​expressed as: ;right Take the median of each row to get the final phase correction value .

[0028] In some embodiments, the and The calculation includes:

[0029] ;

[0030] ;

[0031] in, Indicates the wave number corresponding to the radar operating frequency, is the number of radar receiving antennas, Indicates the number of single information sources; is the coordinate of the array in the due east direction, is the coordinate of the array in the true north direction; are the sampling snapshot data of single signal source No. 1 and auxiliary single signal source No. n, respectively, which are A two-dimensional matrix, where M is the number of sampled snapshots.

[0032] In some embodiments, the The calculation includes:

[0033] .

[0034] In a second aspect, an embodiment of the present invention provides a channel correction device for resolving the ambiguity of a dual-target joint steering vector, comprising at least one processor and a memory, wherein the at least one processor and the memory are connected via a data bus, and the memory stores instructions that can be executed by the at least one processor, and after the instructions are executed by the processor, are used to complete the channel correction method for resolving the ambiguity of a dual-target joint steering vector as described in the first aspect.

[0035] In a third aspect, an embodiment of the present invention provides a non-volatile computer storage medium, wherein the computer storage medium stores computer executable instructions, which are executed by one or more processors to complete the channel correction method for resolving the ambiguity of the dual-target joint steering vector as described in the first aspect.

[0036] Compared with the prior art, the beneficial effects of the present invention are as follows: Different from the prior art, the embodiment of the present invention provides a channel correction method and device for resolving the ambiguity of the joint guidance vector of dual targets. First, the joint MVDR spectrum of the current single source and the auxiliary single source is obtained, and the two groups of azimuth estimation results corresponding to the two highest spectrum peaks are retained for each estimation. Secondly, the Euclidean distances between the multiple estimated azimuths of the single source and the candidate azimuths are calculated, and the smallest half of the distance values ​​are selected and averaged to obtain the half Euclidean average distance. The candidate azimuth with the smallest average distance is the estimated azimuth of the single source. Then, according to the estimated azimuth of the single source, the inherent array guidance vector of the estimated azimuth in the sampled data is deducted to obtain the channel correction value obtained by the single source. Finally, the correction values ​​obtained by multiple single sources are obtained by taking the median of the amplitude to obtain the amplitude correction value, and the median of the phase to obtain the phase correction value.

[0037] In general, the advantages of the technical solution provided by the embodiment of the present invention compared with the prior art are mainly reflected in that when using the dual-target joint steering vector for channel correction, there is no need to limit the radar detection viewing angle to less than 180 degrees, and the influence of ambiguous angle estimation results can also be avoided. The ambiguity of the dual-target joint steering vector is overcome, and the channel correction result is more stable. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] One or more embodiments are exemplarily described by pictures in the corresponding drawings, and these exemplified descriptions do not constitute limitations on the embodiments. Elements / modules and steps with the same reference numerals in the drawings are represented as similar elements / modules and steps. Unless otherwise specified, the figures in the drawings do not constitute proportional limitations.

[0039] Figure 1 It is a flow chart of a channel correction method for resolving the ambiguity of a dual-target joint guidance vector provided by an embodiment of the present invention;

[0040] Figure 2 It is a schematic diagram of the overall process provided by an embodiment of the present invention;

[0041] Figure 3 It is a schematic diagram of using a dual-target joint steering vector to perform arrival angle estimation to generate a fuzzy angle measurement result provided by an embodiment of the present invention;

[0042] Figure 4 It is a block diagram of a channel correction system for resolving dual-target joint guidance vector ambiguity provided by an embodiment of the present invention;

[0043] Figure 5 It is a schematic diagram of the structure of a channel correction device for resolving the ambiguity of a dual-target joint guidance vector provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0044] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several variations and improvements may be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0045] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0046] It should be noted that, if there is no conflict, the various features in the embodiments of the present invention can be combined with each other, and all are within the protection scope of the present invention. In addition, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in a different order than the module division in the device or the order in the flow chart.

[0047] Unless otherwise defined, all technical and scientific terms used in this specification have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in this specification and in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. In addition, the technical features involved in each embodiment of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0048] The present invention aims to solve the problem that when a non-cooperative source is used to perform channel correction through a dual-target joint steering vector method, a group of ambiguous values ​​will appear in the non-cooperative source azimuth estimation, which leads to unstable channel correction results; and provides a channel correction method and device for resolving the ambiguity of a dual-target joint steering vector to solve this problem.

[0049] First, the joint MVDR spectrum of the current single source and the auxiliary single source is obtained, and two groups of azimuth estimation results corresponding to the two highest spectrum peaks are retained for each estimation.

[0050] Secondly, the Euclidean distances between the multiple estimated positions of the single information source and the candidate positions are calculated, and the smallest half of the distance values ​​are selected and averaged to obtain the half Euclidean average distance. The candidate position with the smallest average distance is the estimated position of the single information source.

[0051] Then, according to the estimated azimuth of the single information source, the inherent array steering vector of the estimated azimuth in the sampled data is deducted to obtain the channel correction value obtained by the single information source.

[0052] Finally, the correction values ​​obtained by multiple single signal sources are obtained by taking the median of the amplitude to obtain the amplitude correction value, and taking the median of the phase to obtain the phase correction value.

[0053] Specifically, the embodiments of the present invention are further described below in conjunction with the accompanying drawings.

[0054] Example 1

[0055] Embodiment 1 of the present invention provides a channel correction method for resolving the ambiguity of a dual-target joint steering vector, which can be applied to the non-cooperative source channel correction of a high-frequency ground wave radar. The technical problem to be solved is the ambiguity of the dual-target joint steering vector when performing angle estimation. Figure 3 See Figure 1 and Figure 2As shown, the channel correction method for solving the ambiguity of the dual-target joint guidance vector includes but is not limited to the following steps:

[0056] Step S101: obtaining the joint MVDR spectrum of the current single information source and the auxiliary single information source, and retaining two groups of azimuth estimation results corresponding to the two highest spectrum peaks for each estimation.

[0057] Specifically, the method of dual-target joint steering vector is used to obtain the joint MVDR spectrum of the first single signal source and the nth auxiliary single signal source:

[0058] (1);

[0059] in, represents the conjugate transpose, Represents matrix inversion. are the possible target directions of two single sources, and their ranges include all azimuth directions, that is, . is the joint steering vector, The joint covariance matrix constructed for single source No. 1 and auxiliary single source No. n can be calculated by the following formula:

[0060] (2);

[0061] (3);

[0062] in, Indicates the wave number corresponding to the radar operating frequency, is the number of radar receiving antennas, Indicates the number of single signal sources. is the coordinate of the array in the due east direction, is the coordinate of the array's true north direction. are the sampling snapshot data of single signal source No. 1 and auxiliary single signal source No. n, respectively, which are A two-dimensional matrix, where M is the number of sampled snapshots.

[0063] Pick Two sets of angle estimation results corresponding to the two highest spectral peaks and . Then we can get two possible directions of single signal source No. 1 , , one of them is the true value and the other is the fuzzy value.

[0064] Similarly, single source No. 1 can be estimated jointly with N-1 auxiliary single sources, and single source No. 1 can finally get possible orientation estimates, half of which are correct and half are ambiguous.

[0065] Step S102: Calculate the Euclidean distances between the multiple estimated positions of the single information source and the candidate positions, and select the smallest half of the distance values ​​and take the average thereof to obtain the half Euclidean average distance. The candidate position with the smallest average distance is the estimated position of the single information source.

[0066] Specifically, calculate the number 1 single source Position estimation results and candidate positions The Euclidean distance is obtained as follows Sequence:

[0067] (4);

[0068] Sort the sequence from low to high and get :

[0069] (5);

[0070] The reliability of each candidate position is further measured by the half-Euclidean mean distance, which is the key to solving the ambiguity of the dual-target joint guidance vector. It is calculated by the following formula:

[0071] (6);

[0072] in, The smaller it is, the more likely the candidate position is the true target position of the No. 1 single signal source. When the minimum value is taken , which is the estimated direction of single source No. 1 .

[0073] Step S103: According to the estimated azimuth of the single information source, the inherent array steering vector of the estimated azimuth in the sampled data is deducted to obtain a channel correction value obtained by the single information source.

[0074] Specifically, the channel correction value obtained from the single signal source No. 1 is calculated by first deducting the inherent steering vector of the sampling signal of the single signal source No. 1 to obtain :

[0075] (7);

[0076] in, Represents a diagonal matrix constructed with its posterior vector as diagonal elements. represents taking the conjugate of the signal. for The steering vector of the direction can be calculated by the following formula:

[0077] (8);

[0078] use The first row of data is Normalized to get :

[0079] (9);

[0080] in, for The first row of data. Calculate the modulus of each element, and then take the median of each row to obtain the amplitude correction value of the single source estimate No. 1 ; Calculate the phase of each element, and then take the median of each row to obtain the phase correction value estimated for single source No. 1 .

[0081] Step S104: The correction values ​​obtained by multiple single signal sources are obtained by taking the median of the amplitude to obtain the amplitude correction value, and taking the median of the phase to obtain the phase correction value.

[0082] Specifically, repeat steps S101 to S103 for other single information sources to obtain their corresponding estimated amplitude correction values. Phase correction value Arrange the amplitude correction values ​​of all single source estimates into a matrix , which is The matrix is ​​expressed as:

[0083] (10);

[0084] right The final amplitude correction value can be obtained by taking the median of each row of .

[0085] Arrange the phase correction values ​​of all single source estimates into a matrix , which is The matrix is ​​expressed as:

[0086] (11);

[0087] right The final phase correction value can be obtained by taking the median of each row of .

[0088] In summary, an embodiment of the present invention provides a channel correction method for resolving the ambiguity of the joint guidance vector of dual targets. First, the joint MVDR spectrum of the current single source and the auxiliary single source is obtained, and two groups of azimuth estimation results corresponding to the two highest spectral peaks are retained for each estimation. Secondly, the Euclidean distances between multiple estimated azimuths of the single source and the candidate azimuths are calculated, and the smallest half of the distance values ​​are selected and averaged to obtain the half Euclidean average distance. The candidate azimuth with the smallest average distance is the estimated azimuth of the single source. Then, according to the estimated azimuth of the single source, the inherent array guidance vector of the estimated azimuth in the sampled data is deducted to obtain the channel correction value obtained by the single source. Finally, for the correction values ​​obtained by multiple single sources, the median of the amplitude is taken to obtain the amplitude correction value, and the median of the phase is taken to obtain the phase correction value.

[0089] In general, the advantages of the technical solution provided by the embodiment of the present invention compared with the prior art are mainly reflected in that when using the dual-target joint steering vector for channel correction, there is no need to limit the radar detection viewing angle to less than 180 degrees, and the influence of ambiguous angle estimation results can also be avoided. The ambiguity of the dual-target joint steering vector is overcome, and the channel correction result is more stable.

[0090] Example 2

[0091] Based on Example 1, the present invention also provides a channel correction system for resolving the ambiguity of the dual-target joint guidance vector. Figure 4 As shown, the system includes an azimuth estimation result acquisition module, a single source estimation azimuth acquisition module, a channel correction value acquisition module and a final correction value acquisition module, wherein: the azimuth estimation result acquisition module is used to obtain the joint MVDR spectrum of the current single source and the auxiliary single source, and retain two groups of azimuth estimation results corresponding to the two highest spectrum peaks for each estimation. The single source estimation azimuth acquisition module is used to calculate the Euclidean distances between multiple estimated azimuths of the single source and the candidate azimuths, and select the smallest half of the distance values ​​to take the average to obtain the half Euclidean average distance, and the candidate azimuth with the smallest average distance is the estimated azimuth of the single source. The channel correction value acquisition module is used to obtain the channel correction value obtained by the single source according to the estimated azimuth of the single source. The final correction value acquisition module is used to obtain the amplitude correction value by taking the median of the amplitude and the phase correction value by taking the median of the phase.

[0092] Each module described in the above system has a detailed introduction to its corresponding function in Example 1, which will not be repeated here.

[0093] Example 3

[0094] The embodiment of the present invention also provides a channel correction device for resolving the ambiguity of the dual-target joint guidance vector, see Figure 5 , which shows that it is possible to execute Figure 1 The hardware structure of the channel correction method for resolving the ambiguity of the dual-target joint steering vector.

[0095] The channel correction device for solving the dual-target joint steering vector ambiguity includes: at least one processor 11; and a memory 12 connected to the at least one processor 11 in communication. Figure 5 The memory 12 stores instructions that can be executed by the at least one processor 11, and the instructions are executed by the at least one processor 11 so that the at least one processor 11 can perform the above Figure 1 The processor 11 and the memory 12 can be connected via a bus or other means. Figure 5 The example of connecting through bus is taken in the following.

[0096] The memory 12, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer executable programs and modules, such as program instructions / modules corresponding to the channel correction method for solving the ambiguity of the dual-target joint steering vector in the embodiment of the present invention. The processor 11 executes various functional applications and data processing of the server by running the non-volatile software programs, instructions and modules stored in the memory 12, that is, the channel correction method for solving the ambiguity of the dual-target joint steering vector in the above method embodiment is realized.

[0097] The memory 12 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required by at least one function; the data storage area may store data created by the use of a channel correction system for solving dual-target joint steering vector ambiguity, etc. In addition, the memory 12 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 12 may optionally include a memory remotely arranged relative to the processor 11, and these remote memories may be connected to the channel correction system for solving dual-target joint steering vector ambiguity via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0098] The one or more modules are stored in the memory 12, and when executed by the one or more processors 11, perform the channel correction method for solving the dual-target joint steering vector ambiguity in any of the above method embodiments, for example, perform the above described Figure 1-Figure 2 method steps.

[0099] The above product can execute the method provided by the embodiment of the present invention, and has the functional modules and beneficial effects corresponding to the execution method. For technical details not described in detail in this embodiment, please refer to the method provided by the embodiment of the present invention.

[0100] The embodiment of the present invention further provides a non-volatile computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are executed by one or more processors, for example, to execute the above-described Figure 1-Figure 2 method steps.

[0101] The embodiment of the present invention further provides a computer program product, including a computer program stored on a non-volatile computer-readable storage medium, wherein the computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes the channel correction method for resolving the ambiguity of the dual-target joint steering vector in any of the above method embodiments, for example, executing the above described Figure 1-Figure 2 method steps.

[0102] It should be noted that the device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0103] Through the description of the above implementation methods, ordinary technicians in this field can clearly understand that each implementation method can be implemented by means of software plus a general hardware platform, and of course, it can also be implemented by hardware. Ordinary technicians in this field can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them. Under the concept of the present invention, the technical features in the above embodiments or different embodiments may also be combined, the steps may be implemented in any order, and there are many other changes in different aspects of the present invention as described above, which are not provided in detail for the sake of simplicity. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A channel correction method for resolving the ambiguity of a dual-target joint steering vector, characterized in that: include: The joint MVDR spectrum of the first single signal source and the n auxiliary single signal sources is obtained using the dual-target joint steering vector method: ； in, represents the conjugate transpose, represents matrix inversion; are the possible target directions of two single sources, and their ranges include all azimuth directions, that is, ; is the joint steering vector, The joint covariance matrix constructed for single source No. 1 and auxiliary single source No. n; Pick Two groups of angle estimation results corresponding to the two highest spectral peaks and , we get two possible directions of single source No. 1 , , one of which is the correct value and the other is the fuzzy value; similarly, after the No. 1 single source is jointly estimated with N-1 auxiliary single sources, the No. 1 single source finally obtains possible position estimates, half of which are correct and half are ambiguous; Calculate the number 1 single source Position estimation results and candidate positions The Euclidean distance of Sequence: Sort the sequence from low to high and get : ； The reliability index of each candidate position is obtained, that is, the half Euclidean mean distance: ； in, The smaller the value, the more likely the candidate position is the true target position of the No. 1 single signal source; When the minimum value is taken , which is the estimated direction of single source No. 1 ; Calculate the channel correction value obtained based on single source No.

1. First, deduct the inherent steering vector of the sampled signal of single source No. 1 to obtain : ； in, represents a diagonal matrix constructed with its posterior vector as diagonal elements; represents taking the conjugate of the signal; for Direction of the steering vector; use The first row of data is Normalized to get : ； in, for The first row of data; Calculate the modulus of each element, and then take the median of each row to obtain the amplitude correction value of the single source estimate No. 1 ; Calculate the phase of each element, and then take the median of each row to obtain the phase correction value estimated for single source No. 1 Similarly, for other single sources, obtain their corresponding estimated amplitude correction values Phase correction value ; Arrange the amplitude correction values ​​of all single source estimates into a matrix , which is The matrix is ​​expressed as: ;right Take the median of each row to get the final amplitude correction value ; Arrange the phase correction values ​​of all single source estimates into a matrix , which is The matrix is ​​expressed as: ;right Take the median of each row to get the final phase correction value .

2. The channel correction method for resolving the ambiguity of the dual-target joint steering vector according to claim 1 is characterized in that: Said and The calculation includes: ； ； in, Indicates the wave number corresponding to the radar operating frequency, is the number of radar receiving antennas, Indicates the number of single information sources; is the coordinate of the array in the due east direction, is the coordinate of the array in the true north direction; are the sampling snapshot data of single signal source No. 1 and auxiliary single signal source No. n, respectively, which are A two-dimensional matrix, where M is the number of sampled snapshots.

3. The channel correction method for resolving the ambiguity of the dual-target joint steering vector according to claim 1 is characterized in that: Said The calculation includes: 。 4. A channel correction device for resolving the ambiguity of a dual-target joint guidance vector, characterized in that: The method comprises at least one processor and a memory, wherein the at least one processor and the memory are connected via a data bus, and the memory stores instructions executable by the at least one processor, and the instructions, after being executed by the processor, are used to complete the channel correction method for resolving the ambiguity of the dual-target joint steering vector according to any one of claims 1 to 3.

5. A non-volatile computer storage medium, characterized in that: The computer storage medium stores computer executable instructions, which are executed by one or more processors to complete the channel correction method for resolving the ambiguity of the dual-target joint steering vector as described in any one of claims 1-3.

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