CN114152945A

CN114152945A - MIMO-SAR echo separation method and device, electronic equipment and storage medium

Info

Publication number: CN114152945A
Application number: CN202111413766.9A
Authority: CN
Inventors: 张岩岩; 王宇; 邓云凯; 昌盛; 张永伟; 王伟
Original assignee: Aerospace Information Research Institute of CAS
Current assignee: Aerospace Information Research Institute of CAS
Priority date: 2021-11-25
Filing date: 2021-11-25
Publication date: 2022-03-08

Abstract

The application relates to a multi-input multi-output synthetic aperture radar echo separation method and device, electronic equipment and a storage medium, wherein the method comprises the following steps: determining the maximum number of observed sub-swaths, and in a transmission time window of a pulse repetition interval, using M sub-antennas to simultaneously transmit radar signals to respectively irradiate M sub-swaths not greater than the maximum number for observation; receiving mixed echo signals of M sub mapping bands through N sub antennas in the same echo window to obtain N groups of mixed echo signals; performing echo separation based on N groups of mixed echo signals and a characteristic matrix joint approximation diagonalization JADE algorithm by using the independent statistical characteristics of echo signals of each sub-band to obtain echo signals of M sub-swaths; and respectively imaging the separated echo signals based on a Synthetic Aperture Radar (SAR) imaging algorithm to obtain radar images of M sub-swaths, thereby realizing SAR wide-range imaging. The processing system is low in complexity and high in applicability.

Description

MIMO-SAR echo separation method and device, electronic equipment and storage medium

Technical Field

The embodiment of the application relates to a Multiple-Input Multiple-Output Synthetic Aperture Radar (MIMO-SAR) echo separation method and device, electronic equipment and a storage medium.

Background

In recent decades, High-Resolution and Wide-Swath Synthetic Aperture radars (HRWS-SAR) have been studied more. Among them, scanning synthetic aperture radar (ScanSAR) is an imaging mode that can realize wide coverage. However, the radar image acquired in this mode may be affected by the scallop effect, since the observation area is not illuminated by the entire antenna pattern. Progressive scanning synthetic aperture radar (TOPSAR) for topographical observations can improve the scallop effect of ScanSAR. This mode acquires greater mapping bandwidth by sacrificing azimuthal resolution. Offset Phase Center Antenna (DPCA) is another imaging mode. However, for DPCA with fixed antenna length, it does not in itself allow to increase the mapping bandwidth, but only to improve the azimuthal resolution of the system. A Quad-array (Quad-array) system is an extended mode of DPCA and requires the receive function to be turned off when transmitting signals. Thus, the swath acquired in this mode is discontinuous. The maximum mapping bandwidth of many classical SAR imaging modes can be approximated as:

wherein T is represented by Pulse Repetition Time (PRT), T is 1/PRF, PRF is pulse repetition frequency, T is represented by_pIs the pulse width, and C is the speed of light.

From the above, the bandwidth for obtaining the mapping is M.W_sIn a high resolution image ofT to T_pIn the echo receiving window, the observation system needs to collect M sub-swath scattered mixed echo signals. The existing echo separation methods all have larger system complexity, which is also a problem that the current satellite-borne SAR needs to pay attention.

Disclosure of Invention

In view of the above, embodiments of the present application provide a mimo synthetic aperture radar echo separation method and apparatus, an electronic device, and a storage medium.

According to a first aspect of embodiments of the present application, there is provided a multiple-input multiple-output synthetic aperture radar echo separation method, including:

determining the maximum number of observed sub-swaths, and in a transmission time window of a pulse repetition interval, using M sub-antennas to simultaneously transmit radar signals to respectively irradiate M sub-swaths not greater than the maximum number for observation; receiving mixed echo signals of M sub mapping bands through N sub antennas in the same echo window to obtain N groups of mixed echo signals; wherein N is more than or equal to M;

performing echo separation based on N groups of mixed echo signals and a characteristic matrix joint approximation diagonalization JADE algorithm by using the independent statistical characteristics of echo signals of each sub-band to obtain echo signals of M sub-swaths;

and respectively imaging the separated echo signals based on a Synthetic Aperture Radar (SAR) imaging algorithm to obtain radar images of M sub-swaths, thereby realizing SAR wide-range imaging.

In one embodiment, the determining the maximum number of observed sub-swaths comprises:

determining the maximum number of observed sub-swaths M by_max：

Wherein H_satIs satellite altitude, R_eIs the radius of the earth, C is the speed of light, T is the pulse repetition time PRT, floor [ ]]Denotes the largest integer no greater than x.

In an embodiment, the performing echo separation based on N groups of mixed echo signals and a feature matrix joint approximation diagonalization JADE algorithm by using the independent statistical characteristics of each sub-band echo signal to obtain echo signals of M sub-swaths includes:

whitening the N groups of echo observation data x (t) to obtain whitening data z (t), and degrading the obtained mixed matrix into an orthogonal matrix;

performing feature matrix joint approximate diagonalization processing on a feature matrix of a fourth-order cumulant matrix of whitening data z (t) to obtain an orthogonal matrix U (VJP), wherein P is a permutation matrix, and J is a diagonal matrix;

and (3) multiplying the whitening data z (t) by a conjugate transpose matrix of U to obtain echo signals of M separated sub mapping bands, wherein the echo signals are represented as: y (t) is U^Hz(t)＝PJs(t)。

In one embodiment, the slant range difference between adjacent sub-swaths in the M sub-swaths is maintained at T.C/4, so that the mixed echoes of the M sub-swaths are within the same echo window.

According to a second aspect of the embodiments of the present application, there is provided a multiple-input multiple-output synthetic aperture radar echo separating device, including:

a determining unit for determining a maximum number of observed sub-swaths;

the observation unit is used for simultaneously emitting radar signals by using M sub-antennas to respectively irradiate M sub-swaths not greater than the maximum number for observation in a pulse repetition interval emission time window;

the receiving unit is used for receiving the mixed echo signals of the M sub mapping bands through the N sub antennas in the same echo window to obtain N groups of mixed echo signals; wherein N is more than or equal to M;

the echo separation unit is used for carrying out echo separation on the basis of N groups of mixed echo signals and a characteristic matrix joint approximation diagonalization JADE algorithm by utilizing the independent statistical characteristics of echo signals of each sub-band to obtain echo signals of M sub-swaths;

and the imaging unit is used for respectively imaging the separated echo signals based on a Synthetic Aperture Radar (SAR) imaging algorithm to obtain radar images of M sub swaths, so that SAR wide-width imaging is realized.

In one embodiment, the determining unit is further configured to:

determining the maximum number of observed sub-swaths M by_max：

In one embodiment, the echo separation unit is further configured to:

According to a third aspect of embodiments of the present application, there is provided an electronic device, comprising a processor, a memory, and an executable program stored on the memory and executable by the processor, wherein the processor executes the executable program to perform the steps of the multiple-input multiple-output synthetic aperture radar echo separation method.

According to a fourth aspect of embodiments herein, there is provided a storage medium having stored thereon the steps of the multiple-input multiple-output synthetic aperture radar echo separation method as described when the executable program is executed by a processor.

In the embodiment of the application, the MIMO-SAR echo separation method is provided based on the blind source separation principle, mixed echoes of a plurality of sub mapping bands are separated, and the independent statistical characteristics of scattering echoes of different sub mapping bands are mainly utilized. And the method does not need DBF technology, which can reduce the complexity of the design of the satellite-borne SAR system. Through simulation verification, the technical scheme of the embodiment of the application needs to divide the SAR antenna into N sub-antennas (N is more than or equal to M, and M represents the number of the sub-swaths), so as to separate the mixed echo signals of the M sub-swaths; therefore, the method has strong applicability, does not need complex distance-oriented DBF technology, and is suitable for satellite-borne MIMO-SAR tasks.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below. It is obvious that the drawings in the following description are some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.

Fig. 1 is a schematic space geometry diagram of an on-board SAR according to an embodiment of the present application;

FIG. 2 is a schematic diagram of a space geometry of an on-board MIMO-SAR imaging according to an embodiment of the present application;

FIG. 3 is a schematic diagram of echo mixing and signal processing for multiple sub-swaths according to an embodiment of the present application;

FIG. 4 is a flowchart of echo separation based on feature matrix joint approximation diagonalization according to an embodiment of the present application;

FIG. 5 shows 3 sub-swaths of the spaceborne MIMO-SAR observation according to the embodiment of the present application;

FIG. 6 is a schematic diagram of a first set of simulation results of satellite-borne MIMO-SAR echo separation according to an embodiment of the present application;

FIG. 7 is a diagram illustrating a second set of simulation results of satellite-borne MIMO-SAR echo separation according to an embodiment of the present application;

fig. 8 is a third set of simulation results schematic diagram of the satellite-borne MIMO-SAR echo separation according to the embodiment of the present application;

fig. 9 is a schematic diagram of a final simulation result of the satellite-borne MIMO-SAR echo separation according to the embodiment of the present application;

FIG. 10 is a schematic diagram illustrating a comparison of simulation results of satellite-borne MIMO-SAR echo separation according to an embodiment of the present application;

FIG. 11 is a schematic diagram of an error of a simulation result of satellite-borne MIMO-SAR echo separation according to an embodiment of the present application;

fig. 12 is a schematic structural diagram of a mimo synthetic aperture radar echo separation apparatus according to an embodiment of the present application;

fig. 13 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

The essence of the technical solution of the embodiments of the present application is explained in detail below with reference to the accompanying drawings.

The technical scheme of the embodiment of the application aims to provide a MIMO-SAR echo separation method, and solves the problems of echo separation and high-resolution wide-width imaging of a satellite-borne SAR.

Fig. 1 is a space geometric schematic diagram of a space-borne SAR according to an embodiment of the present application, and as shown in fig. 1, a MIMO-SAR imaging mode according to an embodiment of the present application may simultaneously observe a plurality of sub-swaths, and in the imaging mode, the maximum number M of observed sub-swaths_maxCan be determined by the following formula:

wherein H_satIs satellite altitude, R_eIs the radius of the earth, C is the speed of light, T is the Pulse Repetition Time (PRT), floor [. gamma. ]]A deterministic function representing the largest integer no greater than x. For the convenience of analysis, it is assumed hereinafter that the numbers of the sub swaths and the sub antennas are M ═ 5 and N ═ 5, respectively.

Fig. 2 is a schematic diagram of a space geometry of a satellite-borne MIMO-SAR imaging according to an embodiment of the present application, and as shown in fig. 2, the MIMO-SAR imaging mode shown in the present application mainly includes that, in an emission time window of a pulse repetition interval, 5 sub-antennas simultaneously emit radar signals to respectively irradiate 5 sub-swaths. Suppose that the center slant distance of the 1 st sub-swath is R_refThen the range of slope distance of the mth sub-swath can be expressed as:

wherein, w_SFor the child swath width, m ∈ {1, …,5 }. As can be seen from the above equation, a satellite receives its PRT signal within a certain echo window_k+4The echo signal illuminating the mth sub-swath within the transmit time window of (a) may be represented as:

wherein, Echo_mThe echo signal of the mth sub mapping band is shown, k +4 shows that the signal emission window corresponding to the echo signal is in PRT_k+4And (4) the following steps. Further, the following expression can be obtained:

visible, satellite at PRT_k+4，PRT_k+3，PRT_k+2，PRT_k+1And PRT_k+0The echo signals within the

respective sub swaths

1, 2, 3, 4 and 5 may be received within the same echo window. That is, since the slant-distance difference between each adjacent sub swath is T.C/4, the mixed echoes of the plurality of sub swaths are received within the same echo window.

For the radar signal transmitting time sequence adopted by the MIMO-SAR imaging mode, in order to realize echo separation, N (N is more than or equal to 5) sub-antennas are required to be adopted to simultaneously receive scattered radar echoes to obtain N groups of mixed echo signals. For the MIMO-SAR imaging mode described above, the embodiments of the present application employ the following echo separation method, specifically as follows.

The MIMO-SAR-based imaging mode according to the embodiment of the present application may be performed according to a blind source separation principle, fig. 3 is an echo mixing and signal processing schematic diagram of a plurality of sub mapping bands according to the embodiment of the present application, and as shown in fig. 3, an application scenario according to the embodiment of the present application is shown, which mainly includes the following processing steps:

1) the mixed echo signals of the M sub mapping bands are received by N sub antennas of the SAR system at the same time to obtain N groups of mixed echo signals (N is more than or equal to M);

2) performing echo separation based on N groups of mixed echo signals and a feature matrix Joint Approximation Diagonalization (JADE) algorithm by using the independent statistical characteristics of echo signals of each sub-band to obtain echo signals of M sub-swaths;

3) and respectively imaging the separated echo signals based on an SAR imaging algorithm to obtain radar images of M sub-swaths, and simultaneously realizing the wide-width imaging function of the SAR.

The imaging process in the step 3) may use an imaging Algorithm such as a classical Range-Doppler Algorithm (RDA), a Chirp Scaling Algorithm (CSA), and the like.

Fig. 4 is an echo separation flowchart based on feature matrix joint approximation diagonalization according to an embodiment of the present application, and as shown in fig. 4, the echo separation process in step 2) mainly includes the following three steps:

1) whitening the N groups of observation data x (t) to obtain whitening data z (t), degrading the obtained mixed matrix into an orthogonal matrix, reducing the workload of Independent Component Analysis (ICA) and reducing the dimensionality of the observation data;

2) performing feature matrix Joint Approximate Diagonalization (JADE) processing on a feature matrix of a fourth-order cumulant matrix of whitening data z (t) to obtain an orthogonal matrix U which is VJP, wherein P is a permutation matrix and J is a diagonal matrix;

3) the whitening data z (t) is left multiplied by the U conjugate transpose matrix to obtain the echo signals of the M separate sub-swaths, which may be expressed as y (t) U^Hz(t)＝PJs(t)。

Then, based on the processing steps shown in fig. 3, the M echo signals included in y (t) are respectively processed based on the SAR imaging algorithm, so as to obtain a radar image meeting the user requirements.

The essence of the technical solution of the examples of the present application is further illustrated by the following detailed description.

Currently, echo separation is mainly used in the MIMO-SAR mode, whereas MIMO radar has multiple transmitters and receivers. Multiple sub-antennas transmit radar signals, which may be uncorrelated, and the receive antennas attempt to distinguish the signals. SAR can be considered as a form of MIMO radar. Although the conventional SAR employs a single transmitting antenna and a single receiving antenna, the positions of the two antennas are shifted, and a radar image is obtained by joint processing of all information. The MIMO-SAR of the embodiments of the present application refers to a radar system that divides a conventional SAR antenna into a plurality of sub-antennas along the track and vertical track directions.

M of MIMO-SAR of the embodiment of the application_TSub-antenna transmission M_TThe radar signal irradiates one or more target regions simultaneously, the scattered echo signals are mixed with each other and N_RThe channels receive simultaneously. Here, it is assumed that the signal transmitted by the p-th sub-antenna is s_p(t)，p∈{1，2，…，M_TIt is represented as:

where T is the pulse width, T is the time, θ_p(t) is the phase of the radar signal, an

Q (q e {1, …, N) th with antenna gain and transmission loss taken into account_R}) the echo of the channel receiving the radar signal transmitted by the p-th sub-antenna can be represented as:

wherein G is_T，pRepresenting the p-th sub-antenna pattern，G_R，qFor q-channel antenna patterns, σ₀Is the backscattering coefficient, τ, of the target_p，q＝(R_T，p+R_R，q) C is the path delay, R_T，pAnd R_R，qThe distance between the p-th sub-antenna and the q-th channel and the target, c is the speed of light, alpha is the path loss index, and f_cIs the carrier frequency. Thus, the hybrid echo signal received by the q-th channel can be expressed as follows:

that is, have the same τ_p，qWill be received simultaneously.

In order to realize high resolution and wide SAR imaging simultaneously, N needs to be separated firstly_RThe mixed echo signals received by the sub-channels are also the main problems to be solved by the embodiments of the present application.

Generally, Blind Source Separation (BSS) and Independent Component Analysis (ICA) generally rely on unsupervised learning algorithms, and have a wide application prospect in the fields of engineering, neuroscience, and the like. Blind separation originally originated from the "cocktail party" problem, which aims to separate out each person's voice from the mixed sound signal received by multiple sensors. "blind" in which blind separation is intended to encompass two main meanings: 1) an unknown source signal; 2) a mixing process of unknown source signals.

Blind separation has three mathematical models: 1) a linear transient mixture model, 2) a linear convolution mixture model, and 3) a non-linear mixture model.

Assuming that K are independent of each other's source signal s without considering time delay_k(t), K ∈ {1, …, K }, incident on the N elements, the mixed signal x received by each element_n(t), N ∈ {1, …, N }, which is a linear combination of the K source signals at the same time. Here, the linear instantaneous mixture model is rewritten into a matrix form as shown below:

x(t)＝As(t)

wherein the source signal vector is s (t) ═ s₁(t)，s₂(t)，s₃(t)，…，s_K(t)]The mixed signal vector is x (t) ═ x₁(t)，x₂(t)，…，x_N(t)]^TAnd A is an unknown mixing matrix of dimension NxK.

The mathematical expression of the linear convolution mixture model is:

wherein x is_i(t) is the mixed signal received by the i-th array element, s_k(t) is the kth source signal, a_i，k(τ) represents the impulse response of the k-th source signal to the i-th array element. The above formula is expressed in a matrix form as shown below:

wherein the source signal vector is s (t) ═ s₁(t)，s₂(t)，s₃(t)，…，s_K(t)]The mixed signal vector is x (t) ═ x₁(t)，x₂(t)，…，x_N(t)]^T，A(τ)＝[a_i，k(τ)]∈R^N×KIs an unknown mixing matrix of dimension N x K. The observation matrix x (t) is equivalent to the convolution aliasing of the source signal s (t) by a (τ).

The method and the device well solve the problems of echo separation and high-resolution wide-range imaging of the satellite-borne SAR based on a linear mixed model of blind separation and a feature matrix Joint Approximation Diagonalization (JADE) algorithm. In addition, the embodiment of the application can use the system parameters of the three sub mapping bands to image the 3 disordered echoes respectively, and automatically select the imaging results corresponding to the 3 sub mapping bands according to the entropy minimum principle.

In the embodiment of the present application, for the situation that the amplitude of the source signal is not solvable, whitening processing needs to be performed on the observation data, that is, each component of the source signal is converted into a random variable s with a mean value of 0 and a variance of 1_k(t) of (d). Suppose the observed data is x_k(t), then the whitened data can be represented as:

z_k(t)＝T·x_k(t)

where T is a linear transformation.

Observed data x_kThe correlation matrix of (t) can be expressed as:

R_x＝E[x(t)x(t)^H]＝QΛQ^H

wherein Λ is a diagonal matrix, R_xAnd Q is an orthogonal matrix.

Observation data z_kThe correlation matrix of (t) can be expressed as:

R_z＝E[z(t)z(t)^H]＝TE[x(t)x(t)^H]T^H＝TQΛQ^HT^H＝I

then, the whitening matrix may be represented as

T＝Λ^-1/2Q^H

Further, the air conditioner is provided with a fan,

z(t)＝T·A·s(t)＝V·s(t)

R_z＝VE[s(t)s(t)^H]V^H＝VV^H＝I

where V is an orthogonal matrix.

The JADE algorithm of the embodiment of the application aims at: finding the orthogonal matrix U-VJP such that y (t) -U^Hz (t) ═ pjs (t). Where P is a permutation matrix and J is a diagonal matrix. It should be noted that the whitening process as a preprocessing of the BSS can effectively reduce the complexity of the problem, which can be implemented by conventional Principal Component Analysis (PCA). Among them, the purpose of whitening is mainly: 1) degrading the solved mixing matrix into an orthogonal matrix, and reducing the workload of ICA; 2) dimensionality reduction, i.e., when the observation dimension is greater than the number of source signals, the observation signal dimension can be reduced to be the same as the dimension of the source signals through whitening processing.

First, the measure of independence between the components of the random vector can be described as the following comparison function:

wherein, cum (y)_i(t)，y_j ^*(t)，y_k(t)，y_l ^*(t)) represents a fourth order cumulant function, an

Is in the range of { i, j, K, l ∈ [1, …, K [ ]]}-{i≠j≠k≠l}。

Therefore, the maximization of max c (U) is equivalent to the minimization of the sum of squares { i ≠ j ≠ k ≠ l } of all the mutual accumulation amounts other than the fourth-order accumulation amount contained in c (U), i.e., signal separation.

Given a set of matrices N ═ N { (N)_rL 1 is less than or equal to r and less than or equal to s, and joint diagonalization of a unitary matrix U is equivalent to maximization of the following objective function:

in general, the matrix set N cannot be diagonalized completely by U-union at the same time, but only approximately. Therefore, it is called joint approximation diagonalization.

Among them, Cardoso has demonstrated that:

max c(U)＝max C(U，N)

this converts the maximization problem of the contrast function into a joint approximation diagonalization problem of a set of matrices.

Cardoso has demonstrated that: the fourth order cumulant matrix may be represented by a feature matrix. For any given matrix M ═ M_i，j]_KXKDefining a matrix P_z(M)＝[n_i，j]_KXKThe following are:

for any K-dimensional random vector z with fourth order cumulant, there is K²Real number λ_iAnd K²KxK VirteSign matrix M_iSatisfies the following conditions:

P_z(M_i)＝λ_i·M_i

wherein, Trace (M)_rM_s ^H) δ (r-s), Trace (×) is the tracing function.

All fourth order cumulants K with random vector z (t)²×K²Matrix C_zTo C_zAnd decomposing the eigenvalue to obtain the eigenvalue and the eigenvalue matrix.

From K²Reversely piling up the feature vectors of the dimension into a K multiplied by K feature matrix, arranging the feature values in a descending order, and taking the former K feature values and the corresponding feature matrix to form a cumulant feature matrix set N^e＝λ_i·M_i. To N^eThe unitary matrix U can be solved by joint diagonalization, so that

y(t)＝U^Hz(t)＝PJs(t)

Where y (t) represents the separated source signal.

And performing an MIMO-SAR echo separation simulation experiment based on the signal processing flow shown in the figures 3 and 4 and the satellite-borne SAR system parameters shown in the table I. To reduce the performance requirements of the computer required for the simulation, the simulation experiment assumes that M-3 and N-3. The echo signals of the 3 sub swaths are weighted and summed respectively using a complex weight W of 3 × 3 as shown below, resulting in 3 mixed echoes, where Rand (3, 3) represents a random phase of 3 × 3. And realizing echo separation based on 3 mixed echoes and a JADE algorithm. Furthermore, the separated 3 echo signals are imaged and processed respectively to obtain a radar image meeting the user requirements, as follows:

FIG. 5 shows 3 observed sub swath images in an embodiment of the present application. The side view angle ranges of the sub swath 1, the sub swath 2 and the sub swath 3 are 36.8533-37.3923 degrees, 36.8533-37.3923 degrees and 42.0167-42.3692 degrees. And performing distributed target echo simulation based on the 3 × 3 complex value W and the image in fig. 5 to obtain 3 mixed radar echo signals. Further, echo separation is carried out based on a mixed echo and JADE algorithm, and 3 separated echo signals are obtained.

The sequence of separated echo signals obtained based on the JADE algorithm is scrambled. Therefore, it is necessary to use the system parameters of the three sub-swaths to image the 3 out-of-order echoes respectively, and automatically select the imaging results corresponding to the 3 sub-swaths according to the entropy minimum principle. Based on this, the obtained imaging results are shown in fig. 6, 7 and 8. The result of the minimum entropy is selected from fig. 6, fig. 7 and fig. 8, respectively, and the final imaging result is obtained, as shown in fig. 9.

To further quantify the effect of echo separation, the pixel amplitudes corresponding to the white dashed lines in the sub-swaths 3 of fig. 5 and 9 are compared, as shown in fig. 10. And, the difference of the pixel amplitudes corresponding to the two dotted lines is shown in fig. 11.

As shown in table 1 below, simulation parameters for echo separation are shown:

carrier frequency	Altitude of satellite	Number of subchannels	Azimuthal resolution	Distance resolution
					10GHz	607km	3	3m	3m
Antenna mounting angle	Pulse width	Bandwidth of signal	Antenna length	Breadth width
					30°	100us	50MHz	6m	10km
Doppler bandwidth	Pulse repetition frequency	Sub swath 1 Range	Sub swath 2 Range	Sub swath 3 Range
					2156.8Hz	2588.2Hz	36.8533～37.3923°	39.7097-40.1427°	42.0167-42.3692°

TABLE 1

From the simulation results shown in fig. 9, fig. 10, and fig. 11, it can be seen that: the MIMO-SAR echo separation method based on JADE can well separate the mixed echoes of a plurality of sub mapping bands. Based on the method of the embodiment of the application, high-resolution imaging of M sub-swaths can be simultaneously realized. In addition, the method of the embodiment of the application only needs the satellite-borne SAR system to have N sub-channels (N is larger than or equal to M), and does not need to use a DBF technology to realize the echo separation of different sub-swaths, thereby reducing the complexity of the design of the satellite-borne SAR system.

Fig. 12 is a schematic diagram of a structure of a mimo synthetic aperture radar echo separation apparatus according to an embodiment of the present application, and as shown in fig. 12, the mimo synthetic aperture radar echo separation apparatus according to the embodiment of the present application includes:

a determining unit 60 for determining the maximum number of observed sub-swaths;

the observation unit 61 is used for simultaneously emitting radar signals by using M sub-antennas to respectively irradiate M sub-swaths not greater than the maximum number for observation in a transmission time window of a pulse repetition interval;

a receiving unit 62, configured to receive the mixed echo signals of the M sub swaths through the N sub antennas in the same echo window, so as to obtain N groups of mixed echo signals; wherein N is more than or equal to M;

the echo separation unit 63 is configured to perform echo separation based on N groups of mixed echo signals and a feature matrix joint approximation diagonalization JADE algorithm by using the independent statistical characteristics of the echo signals of each sub-band, so as to obtain echo signals of M sub-swaths;

and the imaging unit 64 is used for respectively imaging the separated echo signals based on a synthetic aperture radar SAR imaging algorithm to obtain radar images of M sub swaths, so that SAR wide-width imaging is realized.

As an implementation manner, the determining unit 60 is further configured to:

determining the maximum number of observed sub-swaths M by_max：

As an implementation manner, the echo separation unit 63 is further configured to:

In one embodiment, the slant range difference between adjacent sub bands among the M sub bands is maintained at T.C/4, and the mixed echoes of the M sub bands are within the same echo window.

In an exemplary embodiment, the determination Unit 60, the observation Unit 61, the receiving Unit 62, the echo separating Unit 63, the imaging Unit 64, and the like may be implemented by one or more Central Processing Units (CPUs), Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Programmable Logic Devices (PLDs), Complex Programmable Logic Devices (CPLDs), Field Programmable Gate Arrays (FPGAs), general purpose processors, controllers, Micro Controller Units (MCUs), microprocessors (processors), or other electronic elements for performing the steps of the multi-input multi-output synthetic aperture radar echo separating method of the foregoing embodiments.

In the disclosed embodiment, the specific manner in which each unit in the mimo-sar echo separation apparatus shown in fig. 12 performs operations has been described in detail in the embodiment related to the method, and will not be elaborated here.

Next, an electronic apparatus 11 according to an embodiment of the present application is described with reference to fig. 13.

As shown in fig. 13, the electronic device 11 includes one or more processors 111 and memory 112.

The processor 111 may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control other components in the electronic device 11 to perform desired functions.

Memory 112 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, Random Access Memory (RAM), cache memory (cache), and/or the like. The non-volatile memory may include, for example, Read Only Memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium and executed by processor 111 to implement the cross-system network device call method and/or other desired functionality of the various embodiments of the present application described above. Various contents such as an input signal, a signal component, a noise component, etc. may also be stored in the computer-readable storage medium.

In one example, the electronic device 11 may further include: an input device 113 and an output device 114, which are interconnected by a bus system and/or other form of connection mechanism (not shown in fig. 13).

The input device 113 may include, for example, a keyboard, a mouse, and the like.

The output device 114 may output various information including the determined distance information, direction information, and the like to the outside. The output devices 114 may include, for example, a display, speakers, a printer, and a communication network and its connected remote output devices, among others.

Of course, for the sake of simplicity, only some of the components related to the present application in the electronic device 11 are shown in fig. 13, and components such as a bus, an input/output interface, and the like are omitted. In addition, the electronic device 11 may include any other suitable components, depending on the particular application.

The embodiments of the present application also describe a storage medium having an executable program stored thereon, the executable program being executed by a processor to perform the steps of the multiple-input multiple-output synthetic aperture radar echo separation method of the foregoing embodiments.

It is understood that in some embodiments, the coupled lines and the branch lines may also be referred to as transmission lines, and the names of the branch lines of the coupled lines in the embodiments of the present application are for the function of each part of the circuit in the signal processing process, and are not intended to specifically limit the scope of the present application.

The foregoing describes the general principles of the present application in conjunction with specific embodiments, however, it is noted that the advantages, effects, etc. mentioned in the present application are merely examples and are not limiting, and they should not be considered essential to the various embodiments of the present application. Furthermore, the foregoing disclosure of specific details is for the purpose of illustration and description and is not intended to be limiting, since the foregoing disclosure is not intended to be exhaustive or to limit the disclosure to the precise details disclosed.

The block diagrams of devices, apparatuses, systems referred to in this application are only given as illustrative examples and are not intended to require or imply that the connections, arrangements, configurations, etc. must be made in the manner shown in the block diagrams. These devices, apparatuses, devices, systems may be connected, arranged, configured in any manner, as will be appreciated by those skilled in the art. Words such as "including," "comprising," "having," and the like are open-ended words that mean "including, but not limited to," and are used interchangeably therewith. The words "or" and "as used herein mean, and are used interchangeably with, the word" and/or, "unless the context clearly dictates otherwise. The word "such as" is used herein to mean, and is used interchangeably with, the phrase "such as but not limited to".

It should also be noted that in the devices, apparatuses, and methods of the present application, the components or steps may be decomposed and/or recombined. These decompositions and/or recombinations are to be considered as equivalents of the present application.

The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the application. Thus, the present application is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

The foregoing description has been presented for purposes of illustration and description. Furthermore, the description is not intended to limit embodiments of the application to the form disclosed herein. While a number of example aspects and embodiments have been discussed above, those of skill in the art will recognize certain variations, modifications, alterations, additions and sub-combinations thereof.

Claims

1. A multiple-input multiple-output synthetic aperture radar echo separation method, the method comprising:

2. The method of claim 1, wherein said determining the maximum number of observed sub-swaths comprises:

determining the maximum number of observed sub-swaths M by_max：

3. The method according to claim 1, wherein the echo separation is performed based on N sets of mixed echo signals and a feature matrix joint approximation diagonalization JADE algorithm by using the independent statistical characteristics of each sub-band echo signal to obtain echo signals of M sub-swaths, and the method comprises:

performing feature matrix joint approximate diagonalization processing on a feature matrix of a fourth-order cumulant matrix of the whitening data z (t) to obtain an orthogonal matrix U (VJP), wherein P is a permutation matrix, and J is a diagonal matrix;

4. The method of claim 1 wherein the difference in slope distance between adjacent sub-swaths in the M sub-swaths is maintained at T · C/4 such that the mixed echoes of the M sub-swaths are within the same echo window.

5. A multiple-input multiple-output synthetic aperture radar echo separation device, the device comprising:

a determining unit for determining a maximum number of observed sub-swaths;

6. The apparatus of claim 5, wherein the determining unit is further configured to:

determining the maximum number of observed sub-swaths M by_max：

7. The apparatus of claim 5, wherein the echo separation unit is further configured to:

8. The apparatus of claim 5 wherein the difference in slope distance between adjacent sub-swaths in the M sub-swaths is maintained at T C/4 such that the mixed echoes of the M sub-swaths are within the same echo window.

9. An electronic device comprising a processor, a memory, and an executable program stored on the memory and executable by the processor, the processor when executing the executable program performing the steps of the multiple-input multiple-output synthetic aperture radar echo separation method of any one of claims 1 to 4.

10. A storage medium having stored thereon an executable program which, when executed by a processor, performs the steps of the multiple-input multiple-output synthetic aperture radar echo separation method according to any one of claims 1 to 4.