Radar imaging method, device, equipment and medium based on composite regularization parameters

Abstract

The present disclosure provides a radar imaging method based on a composite regularization parameter, which can be applied to the field of radar imaging technology. The radar imaging method based on the composite regularization parameter includes: acquiring an echo signal; determining a pre-imaging function according to the echo signal and a preset imaging function; determining an imaging hypersurface expression according to the pre-imaging function, the pre-imaging function including a regularization parameter; determining a target parameter value set corresponding to the regularization parameter according to the imaging hypersurface expression and a preset threshold value of each sub-regularization parameter in the regularization parameter; determining a target imaging function based on the pre-imaging function and the target parameter value set; and generating an image corresponding to the echo signal according to the target imaging function. The present disclosure also provides a radar imaging device, equipment, medium and program product based on the composite regularization parameter.

Description

Technical Field

[0001] The present disclosure relates to the field of radar imaging, and in particular to a radar imaging method, device, electronic device, medium and program product with a composite regularization parameter. Background Art

[0002] At present, in the field of radar imaging, sparse microwave imaging has the characteristics of reducing the amount and complexity of system data and improving imaging quality. Regularization method is an important means to achieve sparse microwave imaging reconstruction, and imaging is achieved by minimizing the loss function composed of residual term and penalty term.

[0003] With the development of compressed sensing technology, sparse microwave imaging is no longer limited to regularization models with a single penalty term, but a composite regularization model with multiple penalty terms. In the composite regularization model, the influence of each penalty term on the imaging result is controlled by the corresponding regularization parameter. The currently widely used regularization parameter selection method is only applicable to determining a single regularization parameter, and cannot determine multiple regularization parameters. Summary of the invention

[0004] In view of the above problems, the present disclosure provides a radar imaging method, apparatus, electronic device, medium and program product based on composite regularization parameters for improving the quality and efficiency of radar imaging.

[0005] According to one aspect of the present disclosure, a radar imaging method based on a composite regularization parameter is provided, comprising: acquiring an echo signal; determining a pre-imaging function according to the echo signal and a preset imaging function; determining an imaging hypersurface expression according to the pre-imaging function, the pre-imaging function including a regularization parameter; determining a target parameter value set corresponding to the regularization parameter according to the imaging hypersurface expression and a preset threshold value of each sub-regularization parameter in the regularization parameter; determining a target imaging function based on the pre-imaging function and the target parameter value set; and generating an image corresponding to the echo signal according to the target imaging function.

[0006] According to an embodiment of the present disclosure, the imaging hypersurface expression includes:

[0007]

[0008]

[0009] in, is the hypersurface function, y is the echo signal vector corresponding to the echo signal, A is the observation matrix, is the pre-imaging function, p i () is the i-th penalty term, λ is the regularization parameter of the penalty term, iis the sub-regularization parameter of the i-th penalty term, x is the observation image vector, and k is an integer greater than or equal to 2.

[0010] According to an embodiment of the present disclosure, the preset threshold includes a preset lower threshold and a preset upper threshold, and the preset upper threshold is greater than or equal to the preset lower threshold; according to the preset threshold of each sub-regularization parameter in the imaging hypersurface expression and the regularization parameter, determining the target parameter value set corresponding to the regularization parameter includes: for each sub-regularization parameter, according to the preset lower threshold and the preset upper threshold, respectively determining at least one test parameter value; according to the at least one test parameter value corresponding to each sub-regularization parameter, determining at least one test parameter value set; using the curvature formula and the directed area formula, processing the imaging hypersurface expression and at least one test parameter value set, determining the test curvature value and the test directed area value corresponding to each test parameter value set, and obtaining at least one test curvature value and at least one test directed area value; according to the at least one test curvature value and the at least one test directed area value, determining the first test curvature value corresponding to each test parameter value set, and obtaining at least one first test curvature value; and determining the target parameter value set according to the at least one first test curvature value.

[0011] According to an embodiment of the present disclosure, for each sub-regularization parameter, according to a preset lower threshold and a preset upper threshold, respectively determining at least one test parameter value includes: for each sub-regularization parameter, according to a preset lower threshold and a preset upper threshold, respectively determining multiple pre-test parameter values; and according to a preset sampling rate, determining at least one test parameter value from the multiple pre-test parameter values.

[0012] According to an embodiment of the present disclosure, determining a target parameter value set according to at least one first test curvature value includes: determining a pre-second test curvature value according to at least one first test curvature value; determining at least one updated test parameter value set according to a test parameter value set corresponding to the pre-second test curvature value and a sampling rate; determining updated test curvature values ​​and updated directed area values ​​corresponding to each updated test parameter value set according to an imaging hypersurface expression and each updated test parameter value set, to obtain at least one updated test curvature value and at least one updated directed area value; determining a second test curvature value corresponding to each updated test parameter value set according to at least one updated test curvature value and at least one updated directed area value, to obtain at least one second test curvature value; and determining a target parameter value set according to the pre-first test curvature value and at least one second test curvature value.

[0013] According to an embodiment of the present disclosure, the curvature formula includes:

[0014]

[0015] Where ρi is the i-th test curvature value corresponding to the test parameter set, A is the point on the hypersurface corresponding to the test parameter set, and B i is the point on the hypersurface corresponding to the i-th first auxiliary parameter set, C i is a point on the hypersurface corresponding to the i-th second auxiliary parameter set, wherein the first auxiliary parameter set and the second auxiliary parameter set are determined according to the test parameter value set and at least one test parameter value.

[0016] According to an embodiment of the present disclosure, determining the first test curvature value corresponding to each test parameter value set respectively according to at least one test curvature value and at least one test directed area value includes: determining at least one first test directed area value greater than or equal to a sub-preset threshold from at least one test directed area value; and determining the first test curvature value according to the test curvature values ​​corresponding to each first test directed area value.

[0017] Another aspect of the present disclosure provides a radar imaging device based on a composite regularization parameter, comprising: an acquisition module for acquiring an echo signal; a first determination module for determining a pre-imaging function based on the echo signal and a preset imaging function; a second determination module for determining an imaging hypersurface expression based on the pre-imaging function, the pre-imaging function including a regularization parameter; a third determination module for determining a target parameter value set corresponding to the regularization parameter based on the imaging hypersurface expression and a preset threshold value of each sub-regularization parameter in the regularization parameter; a fourth determination module for determining a target imaging function based on the pre-imaging function and the target parameter value set; and a generation module for generating an image corresponding to the echo signal based on the target imaging function.

[0018] Another aspect of the present disclosure provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the above-mentioned radar imaging method based on composite regularization parameters.

[0019] Another aspect of the present disclosure further provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the above radar imaging method based on composite regularization parameters.

[0020] Another aspect of the present disclosure further provides a computer program product, including a computer program, which implements the above radar imaging method based on composite regularization parameters when executed by a processor.

[0021] The present invention converts the pre-imaging function determined based on the echo signal into a hypersurface expression. The hypersurface constructed by the hypersurface expression is used to determine the value of each sub-regularization parameter in the composite regularization parameter. Finally, according to the value of each sub-regularization parameter, the target imaging function is determined for radar imaging. The present invention solves the problem of determining multiple regularization parameters in the composite regularization model by constructing a hypersurface to determine the value of each sub-regularization parameter, thereby improving the quality and efficiency of synthetic aperture radar imaging. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The above contents and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0023] Figure 1 The application scenario diagram of the radar imaging method, device, electronic device, medium and program product based on composite regularization parameters according to the embodiment of the present disclosure is schematically shown;

[0024] Figure 2 A flowchart of a radar imaging method based on a composite regularization parameter according to an embodiment of the present disclosure is schematically shown;

[0025] Figure 3 A schematic diagram of a method for determining a first test curvature value according to an embodiment of the present disclosure is shown;

[0026] Figures 4A to 4D A schematic diagram of a radar imaging method based on a composite regularization parameter according to another embodiment of the present disclosure is shown;

[0027] Figure 5 A structural block diagram of a radar imaging device based on a composite regularization parameter according to an embodiment of the present disclosure is schematically shown; and

[0028] Figure 6 A block diagram of an electronic device suitable for implementing a radar imaging method based on a composite regularization parameter according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0029] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0030] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0031] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0032] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0033] An embodiment of the present disclosure provides a radar imaging method based on a composite regularization parameter, which acquires an echo signal; determines a pre-imaging function according to the echo signal and a preset imaging function; determines an imaging hypersurface expression according to the pre-imaging function, wherein the pre-imaging function includes a regularization parameter; determines a target parameter value set corresponding to the regularization parameter according to the imaging hypersurface expression and a preset threshold value of each sub-regularization parameter in the regularization parameter; determines a target imaging function based on the pre-imaging function and the target parameter value set; and generates an image corresponding to the echo signal according to the target imaging function.

[0034] Figure 1 The application scenario diagram of radar imaging based on composite regularization parameters according to an embodiment of the present disclosure is schematically shown.

[0035] like Figure 1 As shown, the application scenario 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is used to provide a medium for a communication link between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0036] Users can use terminal devices 101, 102, 103 to interact with server 105 through network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only examples).

[0037] The terminal devices 101 , 102 , and 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, and desktop computers.

[0038] The server 105 may be a server that provides various services, such as a background management server (only an example) that provides support for websites browsed by users using the terminal devices 101, 102, and 103. The background management server may analyze and process the received data such as user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0039] It should be noted that the radar imaging method based on the composite regularization parameter provided in the embodiment of the present disclosure can generally be executed by the server 105. Accordingly, the radar imaging device based on the composite regularization parameter provided in the embodiment of the present disclosure can generally be set in the server 105. The radar imaging method based on the composite regularization parameter provided in the embodiment of the present disclosure can also be executed by a server or server cluster that is different from the server 105 and can communicate with the terminal devices 101, 102, 103 and / or the server 105. Accordingly, the radar imaging device based on the composite regularization parameter provided in the embodiment of the present disclosure can also be set in a server or server cluster that is different from the server 105 and can communicate with the terminal devices 101, 102, 103 and / or the server 105.

[0040] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0041] The following will be based on Figure 1 The scene described by Figure 2 to Figure 4D The radar imaging method based on the composite regularization parameter of the disclosed embodiment is described in detail.

[0042] Figure 2 The flowchart of the radar imaging method based on the composite regularization parameter according to the embodiment of the present disclosure is schematically shown.

[0043] like Figure 2 As shown, the radar imaging method based on the composite regularization parameter of this embodiment includes operations S210 to S260, and the radar imaging method based on the composite regularization parameter can be executed by a server.

[0044] In operation S210, an echo signal is acquired.

[0045] In operation S220, a pre-imaging function is determined according to the echo signal and a preset imaging function.

[0046] According to an embodiment of the present disclosure, the echo signal may be, for example, a signal received after the radar emits electromagnetic waves.

[0047] After receiving the echo signal, the echo signal is processed to obtain an echo signal vector, and an observation matrix and an observation image vector are determined. The echo signal vector, the observation matrix and the observation image vector are respectively substituted into a preset imaging function to obtain a pre-imaging function. The pre-imaging function may be, for example, as shown in the following formula (1).

[0048]

[0049] in, is the pre-imaging function, y is the echo signal vector corresponding to the echo signal, A is the observation matrix, x is the observation image vector, p i () is the i-th penalty term, λ is the regularization parameter of the penalty term, i is the sub-regularization parameter of the i-th penalty term, and k is an integer greater than or equal to 2.

[0050] In operation S230, an imaging hypersurface expression is determined according to a pre-imaging function, where the pre-imaging function includes a regularization parameter.

[0051] According to an embodiment of the present disclosure, the imaging hypersurface expression may be, for example, an imaging equation for determining the hypersurface.

[0052] According to the pre-imaging function, the echo signal vector, the observation matrix, the observation matrix vector, the penalty term and the sub-regularization parameter are determined. According to the echo signal vector, the observation matrix, the observation matrix vector, the penalty term and the sub-regularization parameter, the imaging hypersurface expression is determined using the preset hypersurface function. The imaging hypersurface expression can be shown in the following formula (2), for example.

[0053]

[0054] in, is the hypersurface function, y is the echo signal vector corresponding to the echo signal, A is the observation matrix, is the pre-imaging function, p i () is the i-th penalty term, λ is the regularization parameter of the penalty term, i is the sub-regularization parameter of the i-th penalty term, x is the observation image vector, and k is an integer greater than or equal to 2.

[0055] In operation S240, a target parameter value set corresponding to the regularization parameter is determined according to the imaging hypersurface expression and a preset threshold value of each sub-regularization parameter in the regularization parameter.

[0056] According to an embodiment of the present disclosure, the regularization parameter includes a plurality of sub-regularization parameters. A threshold is determined in advance for each sub-regularization parameter to obtain a preset threshold corresponding to each sub-regularization parameter. It should be noted that the preset threshold corresponding to each sub-regularization parameter may be the same or different.

[0057] According to the preset threshold value of each sub-regularization parameter, multiple parameter values ​​corresponding to each regularization parameter are determined. One parameter value is selected from the multiple parameter values ​​corresponding to each regularization parameter to form at least one test parameter value set.

[0058] Each test parameter value set is substituted into the imaging hypersurface expression, which is a point on the hypersurface. According to the preset conditional function, the point on the hypersurface that meets the preset condition is determined, and the test parameter value set corresponding to the point is used as the target parameter value set.

[0059] According to another embodiment of the present disclosure, the preset threshold may include, for example, a preset lower threshold and a preset upper threshold, and the preset upper threshold is greater than or equal to the preset lower threshold. Operation S240 also includes: for each sub-regularization parameter, according to the preset lower threshold and the preset upper threshold, respectively determine at least one test parameter value; according to at least one test parameter value corresponding to each sub-regularization parameter, determine at least one test parameter value set; using the curvature formula and the directed area formula, process the imaging hypersurface expression and at least one test parameter value set, determine the test curvature value and the test directed area value corresponding to each test parameter value set, and obtain at least one test curvature value and at least one test directed area value; according to at least one test curvature value and at least one test directed area value, determine the first test curvature value corresponding to each test parameter value set, and obtain at least one first test curvature value; and according to at least one first test curvature value, determine the target parameter value set.

[0060] Taking a sub-regularization parameter λ1 as an example, as shown in the following formula (3), at least one test parameter value is determined.

[0061]

[0062] in, is the preset lower limit of the sub-regularization parameter λ1, is the preset upper limit of the sub-regularization parameter λ1, is the S1+1th test parameter value for the sub-regularization parameter λ1, and S1 is an integer greater than or equal to 3. Determined by the above formula (3), for the sub-regularization parameter λ1, at least one test parameter value includes and Similarly, for each sub-regularization parameter, a test parameter value corresponding to the sub-regularization parameter is determined to obtain at least one test parameter value corresponding to each sub-regularization parameter.

[0063] After determining at least one test parameter value corresponding to each sub-regularization parameter, one test parameter value is selected from each of the at least one test parameter values ​​to determine at least one test parameter value set. For example, the test parameter value set can be in is the j1th test parameter value for the sub-regularization parameter λ1, is the j2-th test parameter value for the sub-regularization parameter λ2, is the regularization parameter λ for the sub i The jth i Test parameter values ​​for each test. is the regularization parameter λ for the sub k No. k Test parameter values, 2≤j i ≤S i -1, S i is an integer greater than or equal to 3, and k is an integer greater than or equal to 2.

[0064] The curvature formula may be, for example, the following formula (4), and the directed area formula may be, for example, the following formula (5).

[0065]

[0066]

[0067] Among them, ρ i is the i-th test curvature value corresponding to the test parameter set, A is the point on the hypersurface corresponding to the test parameter set, B i is the point on the hypersurface corresponding to the i-th first auxiliary parameter set, C i is the point on the hypersurface corresponding to the i-th second auxiliary parameter set, area(AB i C i ) for the reason that A and B i and C i The test directed area values ​​of triangles formed by the points on the corresponding hypersurfaces, wherein the first auxiliary parameter set and the second auxiliary parameter set are determined according to the test parameter value set and at least one test parameter value.

[0068] According to formula (4) and formula (5), determining the first test curvature value corresponding to each test parameter value set may include the following steps, for example.

[0069] To test the parameter value set As an example, construct multiple first auxiliary parameter sets B i , as shown in formula (6), and obtain multiple second auxiliary parameter sets C i , as shown in formula (8).

[0070]

[0071] Among them, B1, B2 and B k are the first auxiliary parameter set, is the sub-regularization parameter λ i The jth i Test parameter value, j′ i is greater than j i Less than or equal to S i An integer of (i=1, 2, ..., k), and k is an integer greater than or equal to 2. It should be noted that the first auxiliary parameter set B in formula (6) i Indicates S i -j1 sub-first auxiliary parameter sets. Taking the first auxiliary parameter set B1 as an example, the first auxiliary parameter set B1 is specifically S1-j1 sub-first auxiliary parameter sets shown in formula (7).

[0072]

[0073]

[0074] Among them, B 1，i is the i-th sub-first auxiliary parameter set for the first auxiliary parameter set B1, S1 is an integer greater than or equal to 3, is the sub-regularization parameter λ i The jth i test parameter values, (i=1, 2, . . . , k), and k is an integer greater than or equal to 2.

[0075]

[0076]

[0077] Among them, C1, C2 and C k are the second auxiliary parameter set, is the sub-regularization parameter λ i The first test parameter value of is the normalization parameter λ i The jth i test parameter values, (i=1, 2, . . . , k), and k is an integer greater than or equal to 2.

[0078] Determining the first test curvature value corresponding to each test parameter value set respectively according to at least one test curvature value and at least one test directed area value includes: determining at least one first test directed area value greater than or equal to a sub-preset threshold from at least one test directed area value; and determining the first test curvature value according to the test curvature values ​​corresponding to each first test directed area value.

[0079] Using formula (4) and formula (5), for the test parameter value set A and the first auxiliary parameter set B1, determine the test parameter value set A and S1-j1 sub-first auxiliary parameter sets B 1，i The test curvature values ​​of the second auxiliary parameter set C1 are compared to obtain S1-j1 test curvature values ​​and S1-j1 test directed area values. The S1-j1 test directed area values ​​are compared with the sub-preset threshold to determine at least one first test directed area value greater than the sub-preset threshold. The sub-preset threshold may be 0, for example. Among the test curvature values ​​corresponding to each first test directed area value, the largest test curvature value is used as the sub-test curvature value. Similarly, determine the test parameter value set A and the first auxiliary parameter set B2~B k The sub-test curvature values ​​corresponding to each of the test parameter value sets are respectively determined to obtain k sub-test curvature values ​​corresponding to the test parameter value set A. According to the k sub-test curvature values, the average value of the k sub-test curvature values ​​is taken as the first test curvature value corresponding to the test parameter value set A. Similarly, the first test curvature value corresponding to each test parameter value set in at least one test parameter value set is determined to obtain at least one first test curvature value.

[0080] Among at least one first test curvature value, a maximum first test curvature value is determined as a target test curvature value, and a test parameter set corresponding to the target test curvature value is used as a target parameter value set.

[0081] According to another embodiment of the present disclosure, operation S240 also includes determining, for each sub-regularization parameter, a plurality of pre-test parameter values ​​according to a preset lower threshold and a preset upper threshold, respectively; and determining at least one test parameter value from the plurality of pre-test parameter values ​​according to a preset sampling rate.

[0082] For each sub-regularization parameter, multiple pre-test parameter values ​​are determined according to a preset lower threshold and a preset upper threshold. In the case of insufficient computing power, a certain proportion of pre-test parameter values ​​corresponding to each sub-regularization parameter can be extracted as test parameter values ​​according to a sampling rate. The sampling rate is determined by the required accuracy, computing amount, computing speed, and other requirements.

[0083] For example, pre-test parameter values ​​include and The sampling rate is D, that is, Start sampling every D-1 points, including the last point, and the test parameter values ​​obtained include and Where T i It is determined by the following formula (9).

[0084]

[0085] in, To round down, S i is an integer greater than or equal to 3, and D is the sampling rate.

[0086] For the at least one test parameter value, after determining the first test curvature value corresponding to each test parameter value. According to the first test curvature value, determining the target parameter value set includes: determining a pre-second test curvature value according to at least one first test curvature value; determining at least one updated test parameter value set according to the test parameter value set corresponding to the pre-second test curvature value and the sampling rate; determining the updated test curvature value and the updated directed area value corresponding to each updated test parameter value set according to the imaging hypersurface expression and each updated test parameter value set, and obtaining at least one updated test curvature value and at least one updated directed area value; determining the second test curvature value corresponding to each updated test parameter value set according to at least one updated test curvature value and at least one updated directed area value, and obtaining at least one second test curvature value; and determining the target parameter value set according to the pre-second test curvature value and at least one second test curvature value.

[0087] From the plurality of first test curvature values, a maximum first test curvature value is determined as a pre-second test curvature value.

[0088] For example, the set of test parameter values ​​corresponding to the pre-second test curvature value is For each sub-regularization parameter, determine the surrounding test parameter values ​​of the test parameter value corresponding to the sub-regularization parameter. For example, the pre-test parameter values ​​corresponding to the sub-regularization parameter λ1 include and Sure in, is the updated test parameter value corresponding to the sub-regularization parameter λ1. Similarly, for each sub-regularization parameter, multiple updated test parameter values ​​are determined. One updated test parameter value is randomly selected from each of the multiple updated test parameter values ​​to determine at least one updated test parameter value set.

[0089] Using formula (4) and formula (5), determine the second test curvature value corresponding to each updated test parameter value set in at least one updated test parameter value set, and obtain at least one second test curvature value. The specific determination method is similar to the above.

[0090] Among the pre-second test curvature value and at least one second test curvature value, a maximum test curvature value is determined as a target test curvature value, and a test parameter set corresponding to the target test curvature value is used as a target parameter value set.

[0091] Based on this, it is possible to quickly determine the target parameter value set under limited computing conditions.

[0092] In operation S250, a target imaging function is determined based on the pre-imaging function and the target parameter value set.

[0093] According to an embodiment of the present disclosure, each test parameter value in the target parameter value set is substituted into the pre-imaging function to obtain the target imaging function.

[0094] In operation S260, an image corresponding to the echo signal is generated according to the target imaging function.

[0095] Figure 3 The principle diagram of the method for determining the first test curvature value according to an embodiment of the present disclosure is schematically shown.

[0096] like Figure 3 As shown, the first point 301 is a point on the hypersurface corresponding to the test parameter set A, the second point 311, the third point 312 and the fourth point 313 are respectively 1，1 , sub-first auxiliary parameter set B 1，2 and the first auxiliary parameter set B 1，3 The fifth point 321 is a point on the hypersurface corresponding to the second auxiliary parameter set C1.

[0097] For the test parameter set A and the sub-first auxiliary parameter set B 1，1 , using formula (4) and formula (5), calculate the test curvature value ρ corresponding to the triangle formed by the first point 301, the second point 311 and the fifth point 321 1，1 And test the directed area value area(AB 1，1 C1). Similarly, using formula (4) and formula (5), the test curvature value ρ corresponding to the triangle formed by the first point 301, the third point 312 and the fifth point 321 is calculated. 1，2 And test the directed area value area(AB 1，2C1). Similarly, using formula (4) and formula (5), the test curvature value ρ corresponding to the triangle formed by the first point 301, the fourth point 313 and the fifth point 321 is calculated. 1，3 And test the directed area value area(AB 1，3 C1).

[0098] In determining area(AB 1，1 C1)、area(AB 1，2 C1) and area(AB 1，3 C1) are greater than 0, determine area(AB 1，1 C1)、area(AB 1，2 C1) and area(AB 1，3 C1) are the first test directed area values. 1，1 Greater than ρ 1，2 and ρ 1，3 In the case of 1，1 As a subtest curvature value ρ1.

[0099] In the case where the test parameter set A includes k test parameter values, similarly, for the test parameter set A, the first auxiliary parameter sets B2 to B k and the second auxiliary parameter set C2~C k , determine the subtest curvature ρ2~ρ k It should be noted that k is an integer greater than or equal to 2.

[0100] For the test parameter set A, determine the sub-test curvatures ρ1~ρ k After that, determine ρ1~ρ k The average value of is the first test curvature value corresponding to the test parameter set A.

[0101] Those skilled in the art can understand that the above embodiments are only examples, and the number of the specific sub-first auxiliary parameter sets of the present invention is not limited thereto.

[0102] Figures 4A to 4D The principle diagram of a radar imaging method based on a composite regularization parameter according to another embodiment of the present disclosure is schematically shown.

[0103] Taking the L1+TV regularization model in synthetic aperture radar imaging as an example, a pre-imaging function as shown in formula (10) is constructed.

[0104]

[0105] in, is the pre-imaging function, y is the echo signal vector corresponding to the echo signal, A is the observation matrix, x is the observation image vector, X is the matrix form of the two-dimensional observation image vector x, and λ1 and λ2 are sub-regularization parameters respectively.

[0106] According to the pre-imaging function, an imaging hypersurface expression is determined. The hypersurface determined by the imaging hypersurface expression can be, for example, Figure 4A As shown. Determine the preset lower limit threshold and the preset upper limit threshold of each sub-regularization parameter respectively. And according to the imaging hypersurface expression, the preset lower limit threshold and the preset upper limit threshold, determine the test parameter value set corresponding to the target point 401 as the target parameter value set. The target point 401 is in the residual term and the position in the projection in the direction of the penalty term (||x||1), for example, Figure 4B The target point 401 in the residual term and the penalty term (the position in the projection in the TV(|X|) direction), which can be expressed as Figure 4C The target point 401 in .

[0107] Based on Figure 4A The target parameter value set corresponding to the target point 401 The pre-imaging function shown in formula (9) constitutes the target imaging function. According to the target imaging function, the generated image is as follows Figure 4D As shown in the figure, in the imaging process, the Fourier matrix is ​​used as the observation matrix, and the signal-to-noise ratio SNR = 20dB. Figure 4D As shown, based on the radar imaging method disclosed in the present invention, the positions of points, surfaces and boundary lines can be clearly determined.

[0108] In order to verify the radar imaging method disclosed in the present invention, the verification point 410, the verification surface 421, the verification surface 422, the verification edge 431 and the verification edge 432 are evaluated. For the verification point 410, the verification indicators used are the peak signal-to-noise ratio (PSNR) and the first evaluation index (AMP). For the verification surface 421 and the verification surface 422, the verification indicator used is the second evaluation index (ENL). For the verification edge 431 and the verification edge 432, the verification indicator used is the third evaluation index (EPI). The verification results are shown in Tables 1 to 3 below.

[0109] Table 1

[0110]

[0111] Table 2

[0112]

[0113] Table 3

[0114]

[0115] As can be seen from Tables 1 to 3 above, based on the target parameter value set The imaging effect of the composed target imaging function is optimal.

[0116] Those skilled in the art will appreciate that the above embodiments are merely examples, and the number of penalty items and the number of sub-regularization parameters in the present invention are not limited thereto.

[0117] Based on the above radar imaging method based on composite regularization parameters, the present disclosure also provides a radar imaging device based on composite regularization parameters. Figure 5 The device is described in detail.

[0118] Figure 5 The structure block diagram of a radar imaging device based on a composite regularization parameter according to an embodiment of the present disclosure is schematically shown.

[0119] like Figure 5 As shown, the radar imaging device 500 based on composite regularization parameters of this embodiment includes an acquisition module 510 , a first determination module 520 , a second determination module 530 , a third determination module 540 , a fourth determination module 550 and a generation module 560 .

[0120] The acquisition module 510 is used to acquire the echo signal. In one embodiment, the acquisition module 510 can be used to perform the operation S210 described above, which will not be described in detail here.

[0121] The first determination module 520 is used to determine the pre-imaging function according to the echo signal and the preset imaging function. In one embodiment, the first determination module 520 can be used to perform the operation S220 described above, which will not be described in detail here.

[0122] The second determination module 530 is used to determine the imaging hypersurface expression according to the pre-imaging function, where the pre-imaging function includes a regularization parameter. In one embodiment, the second determination module 530 can be used to perform the operation S230 described above, which will not be described in detail here.

[0123] According to an embodiment of the present disclosure, the imaging hypersurface expression in the second determination module includes:

[0124]

[0125]

[0126] in, is the hypersurface function, y is the echo signal vector corresponding to the echo signal, A is the observation matrix, is the pre-imaging function, p i() is the i-th penalty term, λ is the regularization parameter of the penalty term, i is the sub-regularization parameter of the i-th penalty term, x is the observation image vector, and k is an integer greater than or equal to 2.

[0127] The third determination module 540 is used to determine the target parameter value set corresponding to the regularization parameter according to the imaging hypersurface expression and the preset threshold of each sub-regularization parameter in the regularization parameter. In one embodiment, the third determination module 540 can be used to perform the operation S240 described above, which will not be repeated here.

[0128] According to an embodiment of the present disclosure, the preset threshold includes a preset lower threshold and a preset upper threshold, and the preset upper threshold is greater than or equal to the preset lower threshold; the third determination module 540 is also used to determine at least one test parameter value for each sub-regularization parameter according to the preset lower threshold and the preset upper threshold; determine at least one test parameter value set according to at least one test parameter value corresponding to each sub-regularization parameter; use the curvature formula and the directed area formula to process the imaging hypersurface expression and at least one test parameter value set, determine the test curvature value and the test directed area value corresponding to each test parameter value set, and obtain at least one test curvature value and at least one test directed area value; determine the first test curvature value corresponding to each test parameter value set according to the at least one test curvature value and the at least one test directed area value, and obtain at least one first test curvature value; and determine the target parameter value set according to the at least one first test curvature value.

[0129] According to an embodiment of the present disclosure, the third determination module 540 is also used to determine multiple pre-test parameter values ​​for each sub-regularization parameter according to a preset lower limit threshold and a preset upper limit threshold; and to determine at least one test parameter value from the multiple pre-test parameter values ​​according to a preset sampling rate.

[0130] According to an embodiment of the present disclosure, the third determination module 540 is also used to determine a pre-second test curvature value based on at least one first test curvature value; determine at least one updated test parameter value set based on a test parameter value set and a sampling rate corresponding to the pre-second test curvature value; determine the updated test curvature value and the updated directed area value corresponding to each updated test parameter value set respectively according to the imaging hypersurface expression and each updated test parameter value set, and obtain at least one updated test curvature value and at least one updated directed area value; determine the second test curvature value corresponding to each updated test parameter value set based on at least one updated test curvature value and at least one updated directed area value, and obtain at least one second test curvature value; and determine the target parameter value set based on the pre-second test curvature value and at least one second test curvature value.

[0131] According to an embodiment of the present disclosure, the curvature formula in the third determination module 540 includes:

[0132]

[0133] Among them, ρ i is the i-th test curvature value corresponding to the test parameter set, A is the point on the hypersurface corresponding to the test parameter set, B i is the point on the hypersurface corresponding to the i-th first auxiliary parameter set, C i is a point on the hypersurface corresponding to the i-th second auxiliary parameter set, wherein the first auxiliary parameter set and the second auxiliary parameter set are determined according to the test parameter value set and at least one test parameter value.

[0134] According to an embodiment of the present disclosure, the third determination module 540 is also used to determine at least one first test directed area value greater than or equal to a sub-preset threshold from at least one test directed area value; and to determine a first test curvature value based on the test curvature values ​​corresponding to each first test directed area value.

[0135] The fourth determination module 550 is used to determine the target imaging function based on the pre-imaging function and the target parameter value set. In one embodiment, the fourth determination module 550 can be used to perform the operation S250 described above, which will not be described in detail here.

[0136] The generating module 560 is used to generate an image corresponding to the echo signal according to the target imaging function. In one embodiment, the generating module 560 can be used to perform the operation S260 described above, which will not be described in detail here.

[0137] According to an embodiment of the present disclosure, any multiple modules among the acquisition module 510, the first determination module 520, the second determination module 530, the third determination module 540, the fourth determination module 550 and the generation module 560 can be combined in one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the acquisition module 510, the first determination module 520, the second determination module 530, the third determination module 540, the fourth determination module 550 and the generation module 560 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation modes of software, hardware and firmware or in a suitable combination of any of them. Alternatively, at least one of the acquisition module 510, the first determination module 520, the second determination module 530, the third determination module 540, the fourth determination module 550 and the generation module 560 can be at least partially implemented as a computer program module, and when the computer program module is executed, the corresponding function can be performed.

[0138] Figure 6 A block diagram of an electronic device suitable for implementing a radar imaging method based on a composite regularization parameter according to an embodiment of the present disclosure is schematically shown.

[0139] like Figure 6 As shown, the electronic device 600 according to an embodiment of the present disclosure includes a processor 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage part 608 into a random access memory (RAM) 603. The processor 601 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include an onboard memory for caching purposes. The processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0140] In RAM603, various programs and data required for the operation of electronic device 600 are stored. Processor 601, ROM602 and RAM603 are connected to each other via bus 604. Processor 601 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM602 and / or RAM603. It should be noted that the program can also be stored in one or more memories other than ROM602 and RAM603. Processor 601 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in one or more memories.

[0141] According to an embodiment of the present disclosure, the electronic device 600 may further include an input / output (I / O) interface 605, which is also connected to the bus 604. The electronic device 600 may further include one or more of the following components connected to the I / O interface 605: an input portion 606 including a keyboard, a mouse, etc.; an output portion 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 608 including a hard disk, etc.; and a communication portion 609 including a network interface card such as a LAN card, a modem, etc. The communication portion 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed, so that a computer program read therefrom is installed into the storage portion 608 as needed.

[0142] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0143] According to an embodiment of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device. For example, according to an embodiment of the present disclosure, a computer-readable storage medium may include the ROM602 and / or RAM603 described above and / or one or more memories other than ROM602 and RAM603.

[0144] The embodiment of the present disclosure also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the item recommendation method provided by the embodiment of the present disclosure.

[0145] The above functions defined in the system / device of the embodiment of the present disclosure are performed when the computer program is executed by the processor 601. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0146] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 609, and / or installed from a removable medium 611. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0147] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 609, and / or installed from the removable medium 611. When the computer program is executed by the processor 601, the above functions defined in the system of the embodiment of the present disclosure are performed. According to the embodiment of the present disclosure, the system, device, apparatus, module, unit, etc. described above can be implemented by a computer program module.

[0148] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0149] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0150] It will be appreciated by those skilled in the art that the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways, even if such combinations and / or combinations are not explicitly described in the present disclosure. In particular, the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways without departing from the spirit and teachings of the present disclosure. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0151] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. The scope of the present disclosure is defined by the attached claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A radar imaging method based on a composite regularization parameter, comprising: Acquire echo signal; Determining a pre-imaging function according to the echo signal and a preset imaging function; According to the pre-imaging function, an imaging hypersurface expression is determined, wherein the pre-imaging function includes a regularization parameter; wherein the imaging hypersurface expression includes: in, is the hypersurface function, is the echo signal vector corresponding to the echo signal, is the observation matrix, is the pre-imaging function, For the Penalty items, is the regularization parameter of the penalty term, For the The sub-regularization parameter of the penalty term, is the observed image vector, and is an integer greater than or equal to 2; According to the imaging hypersurface expression and the preset threshold of each sub-regularization parameter in the regularization parameter, a target parameter value set corresponding to the regularization parameter is determined; wherein the preset threshold includes a preset lower threshold and a preset upper threshold, and the preset upper threshold is greater than or equal to the preset lower threshold; according to the imaging hypersurface expression and the preset threshold of each sub-regularization parameter in the regularization parameter, determining the target parameter value set corresponding to the regularization parameter includes: For each sub-regularization parameter, determine at least one test parameter value according to the preset lower threshold and the preset upper threshold; Determining at least one test parameter value set according to the at least one test parameter value corresponding to each sub-regularization parameter; Using the curvature formula and the directed area formula, the imaging hypersurface expression and the at least one test parameter value set are processed to determine the test curvature value and the test directed area value corresponding to each test parameter value set, and obtain at least one test curvature value and at least one test directed area value; Determine, according to the at least one test curvature value and the at least one test directed area value, a first test curvature value corresponding to each of the test parameter value sets, to obtain at least one first test curvature value; and determining a set of target parameter values ​​based on the at least one first test curvature value; Determining a target imaging function based on the pre-imaging function and the target parameter value set; and An image corresponding to the echo signal is generated according to the target imaging function.

2. The method according to claim 1, wherein: The determining, for each sub-regularization parameter, at least one test parameter value according to the preset lower threshold and the preset upper threshold, respectively comprises: For each sub-regularization parameter, determining a plurality of pre-test parameter values ​​respectively according to the preset lower threshold and the preset upper threshold; and At least one test parameter value is determined from the plurality of pre-test parameter values ​​according to a preset sampling rate.

3. The method according to claim 2, wherein: Determining a target parameter value set according to the at least one first test curvature value comprises: Determining a second test curvature value based on the at least one first test curvature value; Determining at least one updated test parameter value set according to the test parameter value set corresponding to the pre-second test curvature value and the sampling rate; According to the imaging hypersurface expression and each updated test parameter value set, determine the updated test curvature value and the updated directed area value respectively corresponding to each updated test parameter value set, and obtain at least one updated test curvature value and at least one updated directed area value; Determine a second test curvature value corresponding to each updated test parameter value set according to the at least one updated test curvature value and the at least one updated directed area value, to obtain at least one second test curvature value; and A target parameter value set is determined based on the pre-second test curvature value and at least one second test curvature value.

4. The method according to claim 1, wherein: The curvature formula includes: in, is the first Test curvature values, is a point on the hypersurface corresponding to the test parameter set, For the points on the hypersurface corresponding to the first auxiliary parameter set, For the The first auxiliary parameter set and the second auxiliary parameter set are determined according to the test parameter value set and the at least one test parameter value.

5. The method according to claim 1, wherein: Determining the first test curvature value corresponding to each test parameter value set respectively according to the at least one test curvature value and the at least one test directed area value comprises: Determine at least one first test directed area value greater than or equal to a sub-preset threshold from the at least one test directed area value; and A first test curvature value is determined according to the test curvature value corresponding to each first test directed area value.

6. A radar imaging device based on a composite regularization parameter, comprising: An acquisition module, used for acquiring an echo signal; A first determination module, configured to determine a pre-imaging function according to the echo signal and a preset imaging function; The second determination module is used to determine an imaging hypersurface expression according to the pre-imaging function, wherein the pre-imaging function includes a regularization parameter; wherein the imaging hypersurface expression includes: in, is the hypersurface function, is the echo signal vector corresponding to the echo signal, is the observation matrix, is the pre-imaging function, For the Penalty items, is the regularization parameter of the penalty term, For the The sub-regularization parameter of the penalty term, is the observed image vector, and is an integer greater than or equal to 2; A third determination module is used to determine a target parameter value set corresponding to the regularization parameter according to the imaging hypersurface expression and a preset threshold of each sub-regularization parameter in the regularization parameter; wherein the preset threshold includes a preset lower threshold and a preset upper threshold, and the preset upper threshold is greater than or equal to the preset lower threshold; the third determination module is also used to perform the following steps: For each sub-regularization parameter, determine at least one test parameter value according to the preset lower threshold and the preset upper threshold; Determining at least one test parameter value set according to the at least one test parameter value corresponding to each sub-regularization parameter; Using the curvature formula and the directed area formula, the imaging hypersurface expression and the at least one test parameter value set are processed to determine the test curvature value and the test directed area value corresponding to each test parameter value set, and obtain at least one test curvature value and at least one test directed area value; Determine, according to the at least one test curvature value and the at least one test directed area value, a first test curvature value corresponding to each of the test parameter value sets, to obtain at least one first test curvature value; and determining a set of target parameter values ​​based on the at least one first test curvature value; a fourth determination module, configured to determine a target imaging function based on the pre-imaging function and the target parameter value set; and A generating module is used to generate an image corresponding to the echo signal according to the target imaging function.

7. An electronic device comprising: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors execute the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the method according to any one of claims 1 to 5.

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