A near-field MIMO-SAR imaging method with non-uniform sparse arrays

Abstract

The present application relates to a near-field MIMO-SAR imaging method of a non-uniform sparse array, wherein the method comprises: obtaining original echo data using a preset multi-input multi-output synthetic aperture radar system, decomposing the multi-input multi-output synthetic aperture radar system into multiple dual-static synthetic aperture radar subsystems, and obtaining the first frequency domain reconstruction data corresponding to each subsystem in Cartesian coordinates, and then converting it into the second frequency domain reconstruction data of each dual-static synthetic aperture radar subsystem in an elliptical bipolar cylindrical coordinate system, and performing a two-dimensional Fourier inverse transform process on it to generate spatial domain reconstruction data of each subsystem in an elliptical bipolar cylindrical coordinate system; generating a Cartesian 3D reconstruction result of each subsystem in a Cartesian coordinate system based on the spatial domain reconstruction data, so as to obtain a 3D imaging result of the multi-input multi-output synthetic aperture radar system according to the Cartesian 3D reconstruction result. Thus, the problems of cross-imaging quality and high computational complexity of traditional imaging technology are solved.

Description

Technical Field

[0001] The present application relates to the technical field of millimeter wave near-field imaging, and in particular to a near-field MIMO-SAR imaging method of a non-uniform sparse array. Background Art

[0002] Compared with traditional dense arrays, MIMO-SAR (Multiple Input Multiple Output Synthetic Aperture Radar) imaging systems have lower system complexity and richer target information due to their advantages of sparsity and multi-angle observation, and have gradually become a hot topic in industry research. At present, traditional MIMO-SAR systems usually adopt uniform and sparse antenna arrays to facilitate engineering implementation. The use of non-uniform sparse arrays can further reduce the number of channels and system complexity, and can also effectively reduce sidelobe interference and improve imaging quality. However, the imaging methods currently applicable to non-uniform sparse arrays cannot achieve fast and accurate imaging. In many application scenarios, especially security detection and medical diagnosis, the imaging speed requirements are extremely high, and real-time imaging technology is urgently needed. Among the existing traditional imaging methods, such as the back-projection method in the time domain, the Kirchhoff migration method, and the distance migration method in the frequency domain, only the back-projection method is applicable to non-uniform sparse MIMO arrays, but its imaging speed still needs to be improved. Although existing research literature has proposed methods suitable for non-uniform sparse arrays, such as the range migration method based on non-uniform fast Fourier transform and the equivalent phase center approximation, the imaging quality and computational efficiency are not high.

[0003] In the field of near-field imaging, millimeter-wave imaging technology based on near-field active arrays can achieve high spatial resolution when performing large aperture and wide operating bandwidth. In addition, due to the non-ionizing characteristics and penetrability of millimeter waves, this technology has been widely studied and applied in various fields such as security inspection, medical diagnosis, through-wall imaging and non-destructive testing.

[0004] At present, the imaging system represented by MIMO-SAR is the mainstream technology. The advantages of this system are mainly high resolution and large coverage, which makes imaging more accurate and effective. The traditional array adopts a uniform and dense arrangement. Although this structure is reliable, it is costly and complex. The use of non-uniform sparse arrays can reduce costs and system complexity, and can also effectively reduce sidelobe interference and improve imaging quality. However, there is currently a lack of accurate and efficient imaging methods in this field. In application fields such as security detection and medical diagnosis that have extremely high requirements for imaging speed, real-time imaging technology is urgently needed.

[0005] In addition, among the traditional methods suitable for MIMO-SAR near-field imaging, such as the back-projection method in the time domain, the Kirchhoff migration method, or the range migration method in the frequency domain, only the back-projection method can be applied to non-uniform sparse MIMO arrays, but its computational complexity is too high; although the ranging migration method based on non-uniform fast Fourier transform and the method based on equivalent phase center can be applied to non-uniform sparse arrays, the imaging quality and computational efficiency are at odds.

[0006] In summary, existing imaging technologies are difficult to achieve both good imaging quality and high computing efficiency at the same time, and cannot meet the needs of real-time imaging applications, which needs to be solved urgently. Summary of the invention

[0007] The present application provides a near-field MIMO-SAR imaging method of a non-uniform sparse array to solve the problems of cross-imaging quality and high computational complexity of traditional imaging technologies.

[0008] The first aspect of the present application provides a near-field MIMO-SAR imaging method for a non-uniform sparse array, comprising the following steps: obtaining original echo data using a preset multi-input multi-output synthetic aperture radar system, and decomposing the multi-input multi-output synthetic aperture radar system into multiple dual-static synthetic aperture radar subsystems, and obtaining first frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in Cartesian coordinates based on the original echo data; obtaining second frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in an elliptical bipolar cylindrical coordinate system based on the first frequency domain reconstruction data, and performing two-dimensional inverse Fourier transform processing on the second frequency domain reconstruction data to generate spatial domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system; generating a Cartesian 3D reconstruction result of each dual-static synthetic aperture radar subsystem in the Cartesian coordinate system based on the spatial domain reconstruction data, so as to obtain a 3D imaging result of the multi-input multi-output synthetic aperture radar system according to the Cartesian 3D reconstruction result.

[0009] Optionally, in an embodiment of the present application, acquiring first frequency domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in Cartesian coordinates based on the original echo data includes:

[0010] Based on the original echo data of the multi-input multi-output synthetic aperture radar system, the subsystem echo data of each dual-static synthetic aperture radar subsystem is obtained, and the reconstruction result of the subsystem echo signal is calculated by using the subsystem echo data and a preset Fourier transform strategy, and the phase function of the stationary point is determined, so that the stationary point satisfies the preset target equation through the phase function and the preset POSP solution strategy, wherein the expression of the phase function is as follows:

[0011]

[0012] The mathematical expression of the objective equation is as follows:

[0013]

[0014] In the Cartesian coordinate system, the solution of the target equation is expressed as: yt0 =g(k,k y ; x, z);

[0015] The first frequency domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the Cartesian coordinates is obtained according to the solution of the target equation and the reconstruction result. The mathematical expression of the first frequency domain reconstruction data is as follows:

[0016]

[0017] Where x, y, z are the coordinates of the scattering point; k y represents the wave number component of the echo signal along the y direction; k represents the wave number; x t represents the x-axis coordinate of the transmitting array in the dual-static synthetic aperture radar subsystem; r represents the x-axis coordinate of the receiving array in the bi-static synthetic aperture radar subsystem; is a phase function; S(·) represents the echo signal spectrum of the dual-static synthetic aperture radar subsystem.

[0018] Optionally, in one embodiment of the present application, obtaining second frequency domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in an elliptical bipolar cylindrical coordinate system based on the first frequency domain reconstruction data includes:

[0019] Based on the first frequency domain reconstructed data, a stationary point in an elliptical bipolar cylindrical coordinate system is obtained, and the stationary point expression in the elliptical bipolar cylindrical coordinate system is as follows:

[0020] k yt0 =g(k,k y ; x,z)=h′(k,k y ; v(x,z));

[0021] Determine the elliptical bipolar cylindrical coordinate system transformation strategy, the mathematical expression of the elliptical bipolar cylindrical coordinate system transformation strategy is as follows:

[0022]

[0023]

[0024] y=y;

[0025] The second frequency domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system is calculated according to the stationary point expression and the elliptical bipolar cylindrical coordinate system transformation strategy, and the initial expression of the second frequency domain reconstruction data is as follows:

[0026]

[0027] Determine the wave number component of the echo signal along the u direction in the elliptical bipolar cylindrical coordinate system, and obtain the final expression of the second frequency domain reconstructed data according to the initial expression of the second frequency domain reconstructed data, the elliptical bipolar cylindrical coordinate system transformation strategy, the wave number component and the preset Fourier transform strategy. The mathematical expression of the wave number component is as follows:

[0028]

[0029] The final expression of the second frequency domain reconstructed data is as follows:

[0030]

[0031] Wherein, u, y, v are the coordinates in the elliptical bipolar cylindrical coordinate system; ln(·) is the logarithmic transformation function; k u represents the wave number component of the echo signal along the u direction in the elliptical bipolar cylindrical coordinate system; v i represents the value of v corresponding to the i-th reconstructed surface in the elliptical bipolar cylindrical coordinate system.

[0032] Optionally, in one embodiment of the present application, the second frequency domain reconstruction data is subjected to a two-dimensional inverse Fourier transform to generate spatial domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system, including: obtaining the spatial domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system based on a final expression of the second frequency domain reconstruction data and a preset two-dimensional inverse Fourier transform processing strategy.

[0033] Optionally, in one embodiment of the present application, the generating a Cartesian 3D reconstruction result of each dual-static synthetic aperture radar subsystem in the Cartesian coordinate system based on the spatial reconstruction data, so as to obtain a 3D imaging result of the multi-input multi-output synthetic aperture radar system according to the Cartesian 3D reconstruction result, includes:

[0034] The spatial reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar coordinates is interpolated to obtain the Cartesian 3D reconstruction results of the multiple bi-static synthetic aperture radar subsystems in the Cartesian coordinates. The mathematical expression of the Cartesian 3D reconstruction result is as follows:

[0035]

[0036] Among them, Interp(·) represents the interpolation function, reconstructing data for the airspace;

[0037] A coherent sum operation is performed on the Cartesian 3D reconstruction result corresponding to each of the dual-static synthetic aperture radar subsystems to obtain a 3D imaging result of the multi-input multi-output synthetic aperture radar system.

[0038] The second aspect of the present application provides a near-field MIMO-SAR imaging device with a non-uniform sparse array, including: a decomposition module, used to obtain original echo data using a preset multi-input multi-output synthetic aperture radar system, and decompose the multi-input multi-output synthetic aperture radar system into multiple dual-static synthetic aperture radar subsystems, and obtain first frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in Cartesian coordinates based on the original echo data; a conversion module, used to obtain second frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in an elliptical bipolar cylindrical coordinate system based on the first frequency domain reconstruction data, and perform two-dimensional Fourier inverse transform processing on the second frequency domain reconstruction data to generate spatial domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system; a reconstruction module, used to generate a Cartesian 3D reconstruction result of each dual-static synthetic aperture radar subsystem in the Cartesian coordinate system based on the spatial domain reconstruction data, so as to obtain a 3D imaging result of the multi-input multi-output synthetic aperture radar system according to the Cartesian 3D reconstruction result.

[0039] Optionally, in one embodiment of the present application, the decomposition module includes:

[0040] The first acquisition unit is used to acquire subsystem echo data of each dual-static synthetic aperture radar subsystem based on the original echo data of the multi-input multi-output synthetic aperture radar system, and calculate the reconstruction result of the subsystem echo signal by using the subsystem echo data and a preset Fourier transform strategy, and determine the phase function of the stationary point, so that the stationary point satisfies the preset target equation through the phase function and the preset POSP solution strategy, wherein the expression of the phase function is as follows:

[0041]

[0042] The mathematical expression of the objective equation is as follows:

[0043]

[0044] In the Cartesian coordinate system, the solution of the target equation is expressed as: yt0 =g(k,k y; x, z);

[0045] The first calculation unit is used to obtain first frequency domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the Cartesian coordinates according to the solution of the target equation and the reconstruction result, wherein the mathematical expression of the first frequency domain reconstruction data is as follows:

[0046]

[0047] Where x, y, z are the coordinates of the scattering point; k y represents the wave number component of the echo signal along the y direction; k represents the wave number; x t represents the x-axis coordinate of the transmitting array in the dual-static synthetic aperture radar subsystem; r represents the x-axis coordinate of the receiving array in the bi-static synthetic aperture radar subsystem; is a phase function; S(·) represents the echo signal spectrum of the dual-static synthetic aperture radar subsystem.

[0048] Optionally, in one embodiment of the present application, the conversion module includes:

[0049] The second acquisition unit is used to acquire a stationary point in an elliptical bipolar cylindrical coordinate system based on the first frequency domain reconstruction data. The stationary point expression in the elliptical bipolar cylindrical coordinate system is as follows:

[0050] k yt0 =g(k,k y ; x,z)=g′(k,k y ; v(x,z));

[0051] The determination unit is used to determine the elliptical bipolar cylindrical coordinate system transformation strategy, and the mathematical expression of the elliptical bipolar cylindrical coordinate system transformation strategy is as follows:

[0052]

[0053]

[0054] y=y;

[0055] The second calculation unit is used to calculate the second frequency domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system according to the stationary point expression and the elliptical bipolar cylindrical coordinate system transformation strategy, and the initial expression of the second frequency domain reconstruction data is as follows:

[0056]

[0057] The first transformation unit is used to determine the wave number component of the echo signal along the u direction in the elliptical bipolar cylindrical coordinate system, and obtain the final expression of the second frequency domain reconstructed data according to the initial expression of the second frequency domain reconstructed data, the elliptical bipolar cylindrical coordinate system transformation strategy, the wave number component and the preset Fourier transform strategy, and the mathematical expression of the wave number component is as follows:

[0058]

[0059] The final expression of the second frequency domain reconstructed data is as follows:

[0060]

[0061] Wherein, u, y, v are the coordinates in the elliptical bipolar cylindrical coordinate system; ln(·) is the logarithmic transformation function; k u represents the wave number component of the echo signal along the u direction in the elliptical bipolar cylindrical coordinate system; v i represents the value of v corresponding to the i-th reconstructed surface in the elliptical bipolar cylindrical coordinate system.

[0062] Optionally, in one embodiment of the present application, the conversion module also includes: a second transformation unit, used to obtain the spatial domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in the elliptical bipolar coordinate system based on the final expression of the second frequency domain reconstruction data and a preset two-dimensional Fourier inverse transform processing strategy.

[0063] Optionally, in one embodiment of the present application, the reconstruction module includes:

[0064] The interpolation unit is used to perform interpolation processing on the spatial reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar coordinates to obtain the Cartesian 3D reconstruction results of the multiple bi-static synthetic aperture radar subsystems in the Cartesian coordinates. The mathematical expression of the Cartesian 3D reconstruction result is as follows:

[0065]

[0066] Among them, Interp(·) represents the interpolation function, reconstructing data for the airspace;

[0067] A summing unit is used to perform a coherent summing operation on the Cartesian 3D reconstruction result corresponding to each of the dual-static synthetic aperture radar subsystems to obtain a 3D imaging result of the multi-input multi-output synthetic aperture radar system.

[0068] A third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the near-field MIMO-SAR imaging method for a non-uniform sparse array as described in the above embodiment.

[0069] A fourth aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned near-field MIMO-SAR imaging method for a non-uniform sparse array.

[0070] Therefore, the embodiments of the present application have the following beneficial effects:

[0071] The embodiment of the present application can obtain the original echo data by using a preset multi-input multi-output synthetic aperture radar system, and decompose the multi-input multi-output synthetic aperture radar system into multiple dual-static synthetic aperture radar subsystems, and obtain the first frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in Cartesian coordinates based on the original echo data; obtain the second frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in an elliptical bipolar cylindrical coordinate system based on the first frequency domain reconstruction data, and perform two-dimensional Fourier inverse transform processing on the second frequency domain reconstruction data to generate the spatial domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system; generate the Cartesian 3D reconstruction result of each dual-static synthetic aperture radar subsystem in the Cartesian coordinate system based on the spatial domain reconstruction data, so as to obtain the 3D imaging result of the multi-input multi-output synthetic aperture radar system according to the Cartesian 3D reconstruction result, thereby overcoming the limitation of the MIMO array in the traditional frequency domain method, and effectively improving the calculation efficiency on the basis of ensuring the imaging quality. Therefore, the problems of cross-imaging quality and high calculation complexity of traditional imaging technology are solved.

[0072] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0074] Figure 1 A flowchart of a near-field MIMO-SAR imaging method of a non-uniform sparse array provided according to an embodiment of the present application;

[0075] Figure 2 A schematic diagram of the geometric structure of a MIMO-SAR imaging system provided for one embodiment of the present application;

[0076] Figure 3 A schematic diagram of execution logic of a near-field MIMO-SAR imaging method of a non-uniform sparse array provided for one embodiment of the present application;

[0077] Figure 4 A schematic diagram of imaging in an elliptical bipolar cylindrical coordinate system provided for one embodiment of the present application;

[0078] Figure 5 A schematic diagram of an imaging effect based on BPA (Back Projection Algorithm) provided for one embodiment of the present application;

[0079] Figure 6 Schematic diagram of imaging effect of a near-field MIMO-SAR imaging method based on a non-uniform sparse array according to an embodiment of the present application;

[0080] Figure 7 This is an example diagram of a near-field MIMO-SAR imaging device with a non-uniform sparse array according to an embodiment of the present application;

[0081] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0082] Among them, 10 is a near-field MIMO-SAR imaging device with a non-uniform sparse array, 100 is a decomposition module, 200 is a conversion module, 300 is a reconstruction module, 801 is a memory, 802 is a processor, and 803 is a communication interface. DETAILED DESCRIPTION

[0083] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0084] A near-field MIMO-SAR imaging method for a non-uniform sparse array according to an embodiment of the present application is described below with reference to the accompanying drawings. In view of the problems mentioned in the above background technology, the present application provides a near-field MIMO-SAR imaging method of a non-uniform sparse array. In the method, raw echo data is obtained by using a preset multi-input multi-output synthetic aperture radar system, and the multi-input multi-output synthetic aperture radar system is decomposed into multiple dual-static synthetic aperture radar subsystems. Based on the raw echo data, first frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in Cartesian coordinates is obtained; based on the first frequency domain reconstruction data, second frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in an elliptical bipolar cylindrical coordinate system is obtained, and two-dimensional Fourier inverse transform processing is performed on the second frequency domain reconstruction data to generate spatial domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system; based on the spatial domain reconstruction data, a Cartesian 3D reconstruction result of each dual-static synthetic aperture radar subsystem in a Cartesian coordinate system is generated, so as to obtain a 3D imaging result of the multi-input multi-output synthetic aperture radar system according to the Cartesian 3D reconstruction result, thereby overcoming the limitations of the MIMO array in the traditional frequency domain method, and effectively improving the calculation efficiency while ensuring the imaging quality. This solves the problems of poor imaging quality and high computational complexity of traditional imaging technologies.

[0085] In order to facilitate those skilled in the art to understand the near-field MIMO-SAR imaging method of the non-uniform sparse array of the present application, the parameter symbols and corresponding parameter schematics involved in the present application are explained below through Table 1.

[0086] Table 1

[0087]

[0088]

[0089] Specifically, Figure 1 A flowchart of a near-field MIMO-SAR imaging method for a non-uniform sparse array provided in an embodiment of the present application.

[0090] like Figure 1 As shown, the near-field MIMO-SAR imaging method of the non-uniform sparse array includes the following steps:

[0091] In step S101, raw echo data is acquired by using a preset multi-input multi-output synthetic aperture radar system, and the multi-input multi-output synthetic aperture radar system is decomposed into a plurality of dual-static synthetic aperture radar subsystems, and first frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in Cartesian coordinates is acquired based on the raw echo data.

[0092] The embodiment of the present application can obtain the original echo data s(x) by collecting the original data of the multi-input multi-output synthetic aperture radar system and correcting the inconsistency of the amplitude and delay between different channel signals and the amplitude imbalance between different frequencies of each channel signal. t ,x r ,y s ,k), and decompose the MIMO-SAR system into multiple Bistatic-SAR subsystems, each of which consists of a single transmitting and receiving element. The subsystem echo data is extracted from the original echo data to obtain the original echo data corresponding to each bistatic synthetic aperture radar subsystem. And convert it to the frequency domain to obtain the first frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in Cartesian coordinates

[0093] Therefore, the embodiments of the present application overcome the array limitation in the traditional frequency domain method by decomposing the MIMO-SAR system into a Bistatic-SAR subsystem, and realize imaging of a non-uniform sparse array.

[0094] Optionally, in one embodiment of the present application, based on the original echo data, obtaining the first frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in Cartesian coordinates includes: based on the original echo data of the multi-input multi-output synthetic aperture radar system, obtaining the subsystem echo data of each dual-static synthetic aperture radar subsystem, and using the subsystem echo data and a preset Fourier transform strategy to calculate the reconstruction result of the subsystem echo signal, and determine the phase function of the stationary point, so that the stationary point satisfies the preset target equation through the phase function and the preset POSP solution strategy, wherein the expression of the phase function is as follows:

[0095]

[0096] The mathematical expression of the objective equation is as follows:

[0097]

[0098] In the Cartesian coordinate system, the solution of the objective equation is expressed as: yt0 =g(k,k y ; x, z);

[0099] According to the solution of the target equation and the reconstruction result, the first frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in Cartesian coordinates is obtained. The mathematical expression of the first frequency domain reconstruction data is as follows:

[0100]

[0101] Where x, y, z are the coordinates of the scattering point; k y represents the wave number component of the echo signal along the y direction; k represents the wave number; x t represents the x-axis coordinate of the transmitting array in the dual-static synthetic aperture radar subsystem; r represents the x-axis coordinate of the receiving array in the bi-static synthetic aperture radar subsystem; is the phase function; S(·) represents the echo signal spectrum of the dual-static synthetic aperture radar subsystem.

[0102] Specifically, Figure 2 is a schematic diagram of the geometric structure of the near-field MIMO-SAR imaging system. Figure 2 As shown, the embodiment of the present application can first scan along the vertical direction through a one-dimensional linear MIMO array to form a rectangular synthetic aperture to illuminate the target in front of the array. The MIMO array is composed of non-uniform and sparse transmitting and receiving elements, and the coordinates are (x t ,y s ,0) and (x r ,y s ,0), and the coordinates of the scattering point are (x,y,z).

[0103] Assuming that the millimeter wave signal propagation process satisfies the first-order Born approximation and the propagation attenuation is ignored, the echo signal can be expressed as:

[0104]

[0105] Where s represents the echo signal; k = 2πf / c, c is the speed of light; o represents the reflectivity distribution function of the target, which is also the target function in the reconstruction process; R t and R r Respectively represent the distance between the transmitting / receiving element and the target, specifically:

[0106]

[0107]

[0108] like Figure 2 In the scenario shown, the embodiment of the present application first provides a calculation formula for a back-projection method with high imaging accuracy:

[0109]

[0110] Secondly, the embodiment of the present application can decompose MIMO-SAR into multiple Bistatic-SAR subsystems, extracting the echo signal received by each subsystem Then the three-dimensional imaging result of MIMO-SAR is obtained by superposition, that is, the target equation, as shown below:

[0111]

[0112] in, and The echo signals and results for each subsystem are shown separately, each subsystem consisting of a single transmitting and receiving element.

[0113] To improve computational efficiency, the embodiment of the present application may convert the Bistatic-SAR subsystem into the frequency domain, and utilize the stationary phase principle and spherical wave decomposition to obtain:

[0114]

[0115]

[0116] Among them, k yt and k yr are the wave number components of the spherical wave signals of the transmitting element and the receiving element in the vertical direction, and when the echo signal is brought in, we can get:

[0117]

[0118] Let k y =k yt +k yr have to:

[0119]

[0120] For the y on both sides of equation (9), s And y are Fourier transformed, so the frequency domain representation can be changed to:

[0121]

[0122] k yt The integral term in the above equation can be solved using POSP, assuming:

[0123]

[0124] Based on POSP, station point k yt0 Satisfies the following equation

[0125]

[0126] make:

[0127] k yt0 =g(k,k y ;x,z)(13)

[0128] Ignoring the slowly changing amplitude term in POSP, the integral result in equation (10) is:

[0129]

[0130] According to formula (12) and formula (13), k yt0 The reliance on two spatial dimensions, x and z, indicates that in the Cartesian coordinate system, k yt0 represents a two-dimensional spatial variation variable, which causes the reconstructed spectrum in the Bistatic-SAR subsystem to have a two-dimensional spatial variation characteristic, which contradicts the requirements of the traditional frequency domain method. Most existing methods use an approximate method to convert k yt0 It is regarded as a spatial invariant, or a high-order power series approximation with smaller errors is used, but it does not achieve accurate imaging.

[0131] In step S102, second frequency domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system is obtained based on the first frequency domain reconstruction data, and two-dimensional inverse Fourier transform processing is performed on the second frequency domain reconstruction data to generate spatial domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system.

[0132] After obtaining the first frequency domain reconstruction data, further, the embodiment of the present application needs to perform Stolt interpolation according to the frequency domain mapping relationship corresponding to different v to obtain the reconstructed spectrum in the elliptical bipolar cylindrical coordinate system (ie, the second frequency domain reconstruction data) And for k u and k y Perform a two-dimensional inverse Fourier transform, such as Figure 3 As shown, to obtain spatial domain reconstruction data

[0133] Therefore, the embodiments of the present application are based on precise and efficient frequency domain imaging technology in an elliptical bipolar cylindrical coordinate system, which enables the application of frequency domain methods without the need for additional approximations, thereby ensuring the computational efficiency and imaging quality of the imaging method, and effectively solving the problem that the imaging quality and computational efficiency of traditional MIMO-SAR imaging methods cannot be taken into account at the same time.

[0134] Optionally, in one embodiment of the present application, obtaining second frequency domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in an elliptical bipolar cylindrical coordinate system based on the first frequency domain reconstruction data includes: obtaining a stationary point in an elliptical bipolar cylindrical coordinate system based on the first frequency domain reconstruction data, and the stationary point expression in the elliptical bipolar cylindrical coordinate system is as follows:

[0135] k yt0 =g(k,k y ; x,z)=g′(k,k y ; v(x,z));

[0136] Determine the elliptical bipolar cylindrical coordinate system transformation strategy. The mathematical expression of the elliptical bipolar cylindrical coordinate system transformation strategy is as follows:

[0137]

[0138]

[0139] y=y;

[0140] The second frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system is calculated according to the stationary point expression and the elliptical bipolar cylindrical coordinate system transformation strategy. The initial expression of the second frequency domain reconstruction data is as follows:

[0141]

[0142] Determine the wave number component of the echo signal along the u direction in the elliptical bipolar cylindrical coordinate system, and obtain the final expression of the second frequency domain reconstructed data according to the initial expression of the second frequency domain reconstructed data, the elliptical bipolar cylindrical coordinate system transformation strategy, the wave number component and the preset Fourier transform strategy. The mathematical expression of the wave number component is as follows:

[0143]

[0144] The final expression of the second frequency domain reconstructed data is as follows:

[0145]

[0146] Where u, y, v are the coordinates in the elliptical bipolar cylindrical coordinate system; ln(·) is the logarithmic transformation function; k u represents the wave number component of the echo signal along the u direction in the elliptical bipolar cylindrical coordinate system; v i Represents the value of v corresponding to the i-th reconstructed surface in the elliptical bipolar cylindrical coordinate system.

[0147] In the actual implementation process, in order to solve the problem of spatial variation of the spectrum, the embodiment of the present application introduces a new coordinate system (u, y, v), in which k is only related to one spatial dimension of yt0, such as v, so the two-dimensional spatial variation of the spectrum in the Cartesian coordinates is simplified to the one-dimensional spatial variation in the new coordinates:

[0148] k yt0 =g(k,k y ; x,z)=g′(k,k y ; v(x,z)) (15)

[0149] The solution of v(x,z) in the above formula is:

[0150]

[0151] Among them, h is a single mapping function. To maintain the coordinate symmetry, h is selected as the natural logarithm ln according to the bipolar coordinates. The transformation relationship of the last dimension u(x,z) can be set arbitrarily. Considering the spectrum bandwidth and sampling issues of the new coordinates, the coordinate transformation is best consistent with the shape of the point spread function (PSF) of the Bistatic-SAR subsystem. Therefore, u is set to the sum of the lateral distances between the transmitting / receiving elements and the target. The elliptical bipolar cylindrical coordinate system can show the following transformation:

[0152]

[0153]

[0154] y=y (17)

[0155] The frequency domain reconstruction in equation (14) is converted into an elliptical bipolar cylindrical coordinate system, and the coordinate transformation in equation (17) is applied to equation (14) to obtain the initial expression of the second frequency domain reconstruction data:

[0156]

[0157] Because k ut0 It depends only on v in the elliptical bipolar cylindrical coordinate system. When v is fixed, k yt0 The spatial variation of is eliminated, so the embodiment of the present application can use the frequency domain method to reconstruct the results on each surface determined by k, such as Figure 4 As shown, for v = c i For a specific value of , let:

[0158]

[0159] By performing Fourier transform on both edges u of equation (18), we can obtain the final expression of the second frequency domain reconstructed data:

[0160]

[0161] Among them, k u represents the wave number component of the echo signal along the u direction in the elliptical bipolar cylindrical coordinate system; k y represents the wave number component of the echo signal along the y direction in the elliptical bipolar cylindrical coordinate system; v i represents the value of v corresponding to the i-th reconstructed surface in the elliptical bipolar cylindrical coordinate system; k represents the wave number; x t represents the x-axis coordinate of the transmitting array in the dual-static synthetic aperture radar subsystem; r represents the x-axis coordinate of the receiving array in the bi-static synthetic aperture radar subsystem; S(·) represents the echo signal spectrum of the bi-static synthetic aperture radar subsystem.

[0162] Equation (20) represents the relationship between the spectrum of the Bistatic-SAR subsystem echo data and the spectrum of the target reflectivity distribution function. The spectrum of the imaging result on each surface determined by v can be derived from the spectrum of the echo data. Different values ​​of v correspond to k in equation (19): u Since Fourier transform operation is required later, the sampling value must be uniform, so u Direction Stolt interpolation.

[0163] Optionally, in one embodiment of the present application, a two-dimensional inverse Fourier transform is performed on the second frequency domain reconstruction data to generate spatial domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in an elliptical bipolar cylindrical coordinate system, including: obtaining the spatial domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in an elliptical bipolar cylindrical coordinate system based on a final expression of the second frequency domain reconstruction data and a preset two-dimensional inverse Fourier transform processing strategy.

[0164] In k u After Stolt interpolation is performed in the direction, the embodiment of the present application can be used to calculate k u and k y Performing a two-dimensional inverse Fourier transform yields:

[0165]

[0166] By solving equations (20) and (21) for all v values, the 3D results of the Bistatic-SAR subsystem in the elliptical bipolar cylindrical coordinate system can be obtained, that is, the spatial reconstruction data corresponding to each bistatic synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system is generated.

[0167] Therefore, in view of the two-dimensional space-varying characteristics of the reconstructed spectrum of the Bistatic-SAR subsystem in Cartesian coordinates, the embodiments of the present application define an elliptical bipolar cylindrical coordinate system to simplify the two-dimensional space-varying of the spectrum in Cartesian coordinates into a one-dimensional space-varying in the new coordinates, thereby effectively solving the problem of imaging quality degradation caused by approximate processing in traditional methods.

[0168] In step S103, a Cartesian 3D reconstruction result of each dual-static synthetic aperture radar subsystem in a Cartesian coordinate system is generated based on the spatial reconstruction data, so as to obtain a 3D imaging result of the multi-input multi-output synthetic aperture radar system according to the Cartesian 3D reconstruction result.

[0169] After generating the spatial reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system, the embodiment of the present application can further implement the transformation of the elliptical bipolar cylindrical coordinate system to the Cartesian coordinate sampling grid by interpolation to obtain the Cartesian 3D reconstruction result of each bi-static synthetic aperture radar subsystem in the Cartesian coordinate system. The above process is repeated for each pair of transmitting and receiving antennas, and the reconstructed images of all Bistatic-SAR subsystems are calculated in turn. Finally, the results of each subsystem are coherently summed to obtain the 3D imaging result of the MIMO-SAR system.

[0170] Therefore, the embodiment of the present application decomposes the MIMO-SAR system into Bistatic-SAR subsystems, each subsystem includes a transmitting antenna and a receiving antenna, and calculates the reconstruction results of the subsystems respectively. Finally, these reconstruction results are coherently accumulated to obtain the reconstruction result of the MIMO-SAR system, thereby solving the array topology constraint in the traditional frequency domain method, that is, requiring the array elements to be evenly and densely distributed, and overcoming the limitations of the traditional frequency domain method on the MIMO array.

[0171] Optionally, in one embodiment of the present application, a Cartesian 3D reconstruction result of each bi-static synthetic aperture radar subsystem in a Cartesian coordinate system is generated based on the spatial reconstruction data, so as to obtain a 3D imaging result of a multi-input multi-output synthetic aperture radar system according to the Cartesian 3D reconstruction result, including: interpolating the spatial reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar coordinate system to obtain the Cartesian 3D reconstruction results of multiple bi-static synthetic aperture radar subsystems in the Cartesian coordinate system, and the mathematical expression of the Cartesian 3D reconstruction result is as follows:

[0172]

[0173] Among them, Interp(·) represents the interpolation function, Reconstruct data for the airspace;

[0174] A coherent summation operation is performed on the Cartesian 3D reconstruction result corresponding to each dual-static synthetic aperture radar subsystem to obtain a 3D imaging result of a multi-input multi-output synthetic aperture radar system.

[0175] It should be noted that the embodiment of the present application can interpolate equation (21) to achieve coordinate transformation and obtain the result in the Cartesian coordinates of the subsystem:

[0176]

[0177] Then, for each transmitting and receiving antenna pair, the above steps are repeated to calculate the reconstructed images of all Bistatic-SAR subsystems in turn. Finally, the results of each subsystem are coherently summed to obtain the 3D imaging result of the MIMO-SAR system.

[0178]

[0179] Therefore, in view of the high computational complexity of the traditional MIMO-SAR near-field imaging method, the embodiment of the present application utilizes the reduced spatial resolution of the subsystem and the frequency domain imaging method in the subsystem. For the near-field imaging of the non-uniform sparse array, the computational complexity of the back-projection method used as the benchmark is O(N 5 ) level, its imaging effect is as follows Figure 5 As shown, the embodiment of the present application only needs O(N 4 ) has a computational complexity of Figure 6 As shown, the computational efficiency is greatly improved.

[0180] According to the near-field MIMO-SAR imaging method of a non-uniform sparse array proposed in an embodiment of the present application, the original echo data is obtained by using a preset multi-input multi-output synthetic aperture radar system, and the multi-input multi-output synthetic aperture radar system is decomposed into multiple dual-static synthetic aperture radar subsystems. Based on the original echo data, first frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in Cartesian coordinates is obtained; based on the first frequency domain reconstruction data, second frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in an elliptical bipolar cylindrical coordinate system is obtained, and two-dimensional Fourier inverse transform processing is performed on the second frequency domain reconstruction data to generate spatial domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system; based on the spatial domain reconstruction data, a Cartesian 3D reconstruction result of each dual-static synthetic aperture radar subsystem in a Cartesian coordinate system is generated, so as to obtain a 3D imaging result of the multi-input multi-output synthetic aperture radar system according to the Cartesian 3D reconstruction result, thereby overcoming the limitations of the MIMO array in the traditional frequency domain method, and effectively improving the calculation efficiency while ensuring the imaging quality.

[0181] Next, a near-field MIMO-SAR imaging device with a non-uniform sparse array proposed in an embodiment of the present application is described with reference to the accompanying drawings.

[0182] Figure 7 It is a block diagram of a near-field MIMO-SAR imaging device with a non-uniform sparse array according to an embodiment of the present application.

[0183] like Figure 7 As shown, the non-uniform sparse array near-field MIMO-SAR imaging device 10 includes: a decomposition module 100 , a conversion module 200 and a reconstruction module 300 .

[0184] Among them, the decomposition module 100 is used to obtain original echo data using a preset multi-input multi-output synthetic aperture radar system, and decompose the multi-input multi-output synthetic aperture radar system into multiple dual-static synthetic aperture radar subsystems, and obtain first frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in Cartesian coordinates based on the original echo data.

[0185] The conversion module 200 is used to obtain second frequency domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system based on the first frequency domain reconstruction data, and perform two-dimensional inverse Fourier transform processing on the second frequency domain reconstruction data to generate spatial domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system.

[0186] The reconstruction module 300 is used to generate a Cartesian 3D reconstruction result of each dual-static synthetic aperture radar subsystem in a Cartesian coordinate system based on the spatial reconstruction data, so as to obtain a 3D imaging result of the multi-input multi-output synthetic aperture radar system according to the Cartesian 3D reconstruction result.

[0187] Optionally, in one embodiment of the present application, the decomposition module 100 includes: a first acquisition unit and a first calculation unit.

[0188] The first acquisition unit is used to acquire the subsystem echo data of each dual-static synthetic aperture radar subsystem based on the original echo data of the multi-input multi-output synthetic aperture radar system, and calculate the reconstruction result of the subsystem echo signal by using the subsystem echo data and the preset Fourier transform strategy, and determine the phase function of the stationary point, so that the stationary point satisfies the preset target equation through the phase function and the preset POSP solution strategy, wherein the expression of the phase function is as follows:

[0189]

[0190] The mathematical expression of the objective equation is as follows:

[0191]

[0192] In the Cartesian coordinate system, the solution of the objective equation is expressed as: yt0 =g(k,k y ; x,z).

[0193] The first calculation unit is used to obtain first frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in Cartesian coordinates according to the solution of the target equation and the reconstruction result. The mathematical expression of the first frequency domain reconstruction data is as follows:

[0194]

[0195] Where x, y, xz are the coordinates of the scattering point; k y represents the wave number component of the echo signal along the y direction; k represents the wave number; x t represents the x-axis coordinate of the transmitting array in the dual-static synthetic aperture radar subsystem; r represents the x-axis coordinate of the receiving array in the bi-static synthetic aperture radar subsystem; is the phase function; S(·) represents the echo signal spectrum of the dual-static synthetic aperture radar subsystem.

[0196] Optionally, in one embodiment of the present application, the conversion module 200 includes: a second acquisition unit, a determination unit, a second calculation unit and a first transformation unit.

[0197] The second acquisition unit is used to acquire a stationary point in an elliptical bipolar cylindrical coordinate system based on the first frequency domain reconstruction data. The stationary point expression in the elliptical bipolar cylindrical coordinate system is as follows:

[0198] k yt0 =g(k,k y ; x,z)=g′(k,k y ; v(x,z)).

[0199] The determination unit is used to determine the elliptical bipolar cylindrical coordinate system transformation strategy. The mathematical expression of the elliptical bipolar cylindrical coordinate system transformation strategy is as follows:

[0200]

[0201]

[0202] y=y。

[0203] The second calculation unit is used to calculate the second frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system according to the stationary point expression and the elliptical bipolar cylindrical coordinate system transformation strategy. The initial expression of the second frequency domain reconstruction data is as follows:

[0204]

[0205] The first transformation unit is used to determine the wave number component of the echo signal along the u direction in the elliptical bipolar cylindrical coordinate system, and obtain the final expression of the second frequency domain reconstructed data according to the initial expression of the second frequency domain reconstructed data, the elliptical bipolar cylindrical coordinate system transformation strategy, the wave number component and the preset Fourier transform strategy. The mathematical expression of the wave number component is as follows:

[0206]

[0207] The final expression of the second frequency domain reconstructed data is as follows:

[0208]

[0209] Where u, y, v are the coordinates in the elliptical bipolar cylindrical coordinate system; ln(·) is the logarithmic transformation function; k u represents the wave number component of the echo signal along the u direction in the elliptical bipolar cylindrical coordinate system; v iRepresents the value of v corresponding to the i-th reconstructed surface in the elliptical bipolar cylindrical coordinate system.

[0210] Optionally, in one embodiment of the present application, the conversion module 200 also includes: a second transformation unit, which is used to obtain the spatial domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in the elliptical bipolar coordinate system based on the final expression of the second frequency domain reconstruction data and a preset two-dimensional inverse Fourier transform processing strategy.

[0211] Optionally, in one embodiment of the present application, the reconstruction module 300 includes: an interpolation unit and a summing unit.

[0212] The interpolation unit is used to interpolate the spatial reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar coordinates to obtain the Cartesian 3D reconstruction results of multiple bi-static synthetic aperture radar subsystems in the Cartesian coordinates. The mathematical expression of the Cartesian 3D reconstruction result is as follows:

[0213]

[0214] Among them, Interp(·) represents the interpolation function, Reconstruct data for the airspace domain.

[0215] The summing unit is used to perform a coherent summing operation on the Cartesian 3D reconstruction result corresponding to each dual-static synthetic aperture radar subsystem to obtain a 3D imaging result of the multi-input multi-output synthetic aperture radar system.

[0216] It should be noted that the above explanation of the embodiment of the near-field MIMO-SAR imaging method of a non-uniform sparse array is also applicable to the near-field MIMO-SAR imaging device of a non-uniform sparse array of this embodiment, and will not be repeated here.

[0217] A near-field MIMO-SAR imaging device with a non-uniform sparse array proposed in an embodiment of the present application includes a decomposition module, which is used to obtain original echo data using a preset multi-input multi-output synthetic aperture radar system, and decompose the multi-input multi-output synthetic aperture radar system into multiple dual-static synthetic aperture radar subsystems, and obtain first frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in Cartesian coordinates based on the original echo data; a conversion module, which is used to obtain second frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in an elliptical bipolar cylindrical coordinate system based on the first frequency domain reconstruction data, and perform two-dimensional Fourier inverse transform processing on the second frequency domain reconstruction data to generate spatial domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system; and a reconstruction module, which is used to generate a Cartesian 3D reconstruction result of each dual-static synthetic aperture radar subsystem in a Cartesian coordinate system based on the spatial domain reconstruction data, so as to obtain a 3D imaging result of the multi-input multi-output synthetic aperture radar system according to the Cartesian 3D reconstruction result, thereby overcoming the limitation of the MIMO array in the traditional frequency domain method, and effectively improving the calculation efficiency on the basis of ensuring the imaging quality.

[0218] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0219] A memory 801 , a processor 802 , and a computer program stored in the memory 801 and executable on the processor 802 .

[0220] When the processor 802 executes the program, the near-field MIMO-SAR imaging method of the non-uniform sparse array provided in the above embodiment is implemented.

[0221] Furthermore, the electronic device further comprises:

[0222] The communication interface 803 is used for communication between the memory 801 and the processor 802 .

[0223] The memory 801 is used to store computer programs that can be executed on the processor 802 .

[0224] The memory 801 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0225] If the memory 801, the processor 802 and the communication interface 803 are implemented independently, the communication interface 803, the memory 801 and the processor 802 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 8 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0226] Optionally, in a specific implementation, if the memory 801, the processor 802 and the communication interface 803 are integrated on a chip, the memory 801, the processor 802 and the communication interface 803 can communicate with each other through an internal interface.

[0227] The processor 802 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0228] An embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned near-field MIMO-SAR imaging method for a non-uniform sparse array.

[0229] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0230] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0231] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0232] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary and then storing it in a computer memory.

[0233] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0234] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0235] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0236] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A near-field MIMO-SAR imaging method for a non-uniform sparse array, characterized in that: The following steps are involved: Acquire original echo data using a preset multi-input multi-output synthetic aperture radar system, decompose the multi-input multi-output synthetic aperture radar system into a plurality of dual-static synthetic aperture radar subsystems, and acquire first frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in Cartesian coordinates based on the original echo data; Obtaining second frequency domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in an elliptical bipolar cylindrical coordinate system based on the first frequency domain reconstruction data, and performing two-dimensional inverse Fourier transform processing on the second frequency domain reconstruction data to generate spatial domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system; A Cartesian 3D reconstruction result of each dual-static synthetic aperture radar subsystem in the Cartesian coordinate system is generated based on the spatial reconstruction data, so as to obtain a 3D imaging result of the multi-input multi-output synthetic aperture radar system according to the Cartesian 3D reconstruction result.

2. The method according to claim 1, characterized in that The step of obtaining first frequency domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in Cartesian coordinates based on the original echo data includes: Based on the original echo data of the multi-input multi-output synthetic aperture radar system, the subsystem echo data of each dual-static synthetic aperture radar subsystem is obtained, and the reconstruction result of the subsystem echo signal is calculated by using the subsystem echo data and a preset Fourier transform strategy, and the phase function of the stationary point is determined, so that the stationary point satisfies the preset target equation through the phase function and the preset POSP solution strategy, wherein the expression of the phase function is as follows: The mathematical expression of the objective equation is as follows: In the Cartesian coordinate system, the solution of the target equation is expressed as: yt0 =g(k,k y ; x, z); The first frequency domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the Cartesian coordinates is obtained according to the solution of the target equation and the reconstruction result. The mathematical expression of the first frequency domain reconstruction data is as follows: Where x, y, z are the coordinates of the scattering point; k y represents the wave number component of the echo signal along the y direction; k yt represents the wave number component of the spherical wave signal of the transmitting element in the vertical direction; k represents the wave number; x t represents the x-axis coordinate of the transmitting array in the dual-static synthetic aperture radar subsystem; r represents the x-axis coordinate of the receiving array in the bi-static synthetic aperture radar subsystem; is a phase function; S(·) represents the echo signal spectrum of the dual-static synthetic aperture radar subsystem.

3. The method according to claim 2, characterized in that The obtaining, based on the first frequency domain reconstruction data, second frequency domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in an elliptical bipolar cylindrical coordinate system comprises: Based on the first frequency domain reconstructed data, a stationary point in an elliptical bipolar cylindrical coordinate system is obtained, and the stationary point expression in the elliptical bipolar cylindrical coordinate system is as follows: k yt0 =g(k,k y ;x,z)=g′(k,k y ;v(x,z)); Determine the elliptical bipolar cylindrical coordinate system transformation strategy, the mathematical expression of the elliptical bipolar cylindrical coordinate system transformation strategy is as follows: w = y; The second frequency domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system is calculated according to the stationary point expression and the elliptical bipolar cylindrical coordinate system transformation strategy, and the initial expression of the second frequency domain reconstruction data is as follows: Determine the wave number component of the echo signal along the u direction in the elliptical bipolar cylindrical coordinate system, and obtain the final expression of the second frequency domain reconstructed data according to the initial expression of the second frequency domain reconstructed data, the elliptical bipolar cylindrical coordinate system transformation strategy, the wave number component and the preset Fourier transform strategy. The mathematical expression of the wave number component is as follows: The final expression of the second frequency domain reconstructed data is as follows: Wherein, u, w, v are the coordinates in the elliptical bipolar cylindrical coordinate system; ln(·) is the logarithmic transformation function; k u represents the wave number component of the echo signal along the u direction in the elliptical bipolar cylindrical coordinate system; v i represents the value of v corresponding to the i-th reconstructed surface in the elliptical bipolar cylindrical coordinate system.

4. The method according to claim 3, characterized in that The performing two-dimensional inverse Fourier transform processing on the second frequency domain reconstruction data to generate spatial domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system includes: Based on the final expression of the second frequency domain reconstructed data and a preset two-dimensional inverse Fourier transform processing strategy, the spatial domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system is obtained.

5. The method according to claim 4, characterized in that The step of generating a Cartesian 3D reconstruction result of each dual-static synthetic aperture radar subsystem in the Cartesian coordinate system based on the spatial reconstruction data, so as to obtain a 3D imaging result of the multi-input multi-output synthetic aperture radar system according to the Cartesian 3D reconstruction result, comprises: The spatial reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar coordinates is interpolated to obtain the Cartesian 3D reconstruction results of the multiple bi-static synthetic aperture radar subsystems in the Cartesian coordinates. The mathematical expression of the Cartesian 3D reconstruction result is as follows: Among them, Interp(·) represents the interpolation function, reconstructing data for the airspace; A coherent sum operation is performed on the Cartesian 3D reconstruction result corresponding to each of the dual-static synthetic aperture radar subsystems to obtain a 3D imaging result of the multi-input multi-output synthetic aperture radar system.

6. A near-field MIMO-SAR imaging device with a non-uniform sparse array, characterized in that: include: a decomposition module, configured to obtain original echo data by using a preset multi-input multi-output synthetic aperture radar system, decompose the multi-input multi-output synthetic aperture radar system into a plurality of dual-static synthetic aperture radar subsystems, and obtain first frequency domain reconstruction data corresponding to each dual-static synthetic aperture radar subsystem in Cartesian coordinates based on the original echo data; a conversion module, configured to obtain second frequency domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in an elliptical bipolar cylindrical coordinate system based on the first frequency domain reconstruction data, and perform a two-dimensional inverse Fourier transform process on the second frequency domain reconstruction data to generate spatial domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system; A reconstruction module is used to generate a Cartesian 3D reconstruction result of each dual-static synthetic aperture radar subsystem in the Cartesian coordinate system based on the spatial reconstruction data, so as to obtain a 3D imaging result of the multi-input multi-output synthetic aperture radar system according to the Cartesian 3D reconstruction result.

7. The device according to claim 6, characterized in that The decomposition module comprises: The first acquisition unit is used to acquire subsystem echo data of each dual-static synthetic aperture radar subsystem based on the original echo data of the multi-input multi-output synthetic aperture radar system, and calculate the reconstruction result of the subsystem echo signal by using the subsystem echo data and a preset Fourier transform strategy, and determine the phase function of the stationary point, so that the stationary point satisfies the preset target equation through the phase function and the preset POSP solution strategy, wherein the expression of the phase function is as follows: The mathematical expression of the objective equation is as follows: In the Cartesian coordinate system, the solution of the target equation is expressed as: yt0 =g(k,k y ; x, z); The first calculation unit is used to obtain first frequency domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the Cartesian coordinates according to the solution of the target equation and the reconstruction result, wherein the mathematical expression of the first frequency domain reconstruction data is as follows: Where x, y, z are the coordinates of the scattering point; k y represents the wave number component of the echo signal along the y direction; k yt represents the wave number component of the spherical wave signal of the transmitting element in the vertical direction; k represents the wave number; x t represents the x-axis coordinate of the transmitting array in the dual-static synthetic aperture radar subsystem; r represents the x-axis coordinate of the receiving array in the bi-static synthetic aperture radar subsystem; is a phase function; S(·) represents the echo signal spectrum of the dual-static synthetic aperture radar subsystem.

8. The device according to claim 7, characterized in that The conversion module comprises: The second acquisition unit is used to acquire a stationary point in an elliptical bipolar cylindrical coordinate system based on the first frequency domain reconstruction data. The stationary point expression in the elliptical bipolar cylindrical coordinate system is as follows: k yt0 =g(k,k y ;x,z)=g′(k,k y ;v(x,z)); The determination unit is used to determine the elliptical bipolar cylindrical coordinate system transformation strategy, and the mathematical expression of the elliptical bipolar cylindrical coordinate system transformation strategy is as follows: w = y; The second calculation unit is used to calculate the second frequency domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system according to the stationary point expression and the elliptical bipolar cylindrical coordinate system transformation strategy, and the initial expression of the second frequency domain reconstruction data is as follows: The first transformation unit is used to determine the wave number component of the echo signal along the u direction in the elliptical bipolar cylindrical coordinate system, and obtain the final expression of the second frequency domain reconstructed data according to the initial expression of the second frequency domain reconstructed data, the elliptical bipolar cylindrical coordinate system transformation strategy, the wave number component and the preset Fourier transform strategy, and the mathematical expression of the wave number component is as follows: The final expression of the second frequency domain reconstructed data is as follows: Wherein, u, w, v are the coordinates in the elliptical bipolar cylindrical coordinate system; ln(·) is the logarithmic transformation function; k u represents the wave number component of the echo signal along the u direction in the elliptical bipolar cylindrical coordinate system; v i represents the value of v corresponding to the i-th reconstructed surface in the elliptical bipolar cylindrical coordinate system.

9. The device according to claim 8, characterized in that The conversion module also includes: The second transformation unit is used to obtain the spatial domain reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar cylindrical coordinate system based on the final expression of the second frequency domain reconstruction data and a preset two-dimensional inverse Fourier transform processing strategy.

10. The device according to claim 9, characterized in that The reconstruction module comprises: The interpolation unit is used to perform interpolation processing on the spatial reconstruction data corresponding to each bi-static synthetic aperture radar subsystem in the elliptical bipolar coordinates to obtain the Cartesian 3D reconstruction results of the multiple bi-static synthetic aperture radar subsystems in the Cartesian coordinates. The mathematical expression of the Cartesian 3D reconstruction result is as follows: Among them, Interp(·) represents the interpolation function, reconstructing data for the airspace; A summing unit is used to perform a coherent summing operation on the Cartesian 3D reconstruction result corresponding to each of the dual-static synthetic aperture radar subsystems to obtain a 3D imaging result of the multi-input multi-output synthetic aperture radar system.

Images