A real synthetic aperture imaging method for multichannel radar forward-looking imaging

Abstract

The application discloses a kind of real synthetic aperture imaging methods for multichannel radar forward-looking imaging, first, the echo data of the region to be imaged is obtained, second, the data obtained is compressed in range direction pulse, then the data after pulse compression is respectively processed in synthetic aperture and real aperture, for synthetic aperture dimension, using BP algorithm is focused in azimuth direction, and the results of each channel are incoherently accumulated, to obtain left-right ambiguous image, for real aperture dimension, the imaging scene is divided into grid, constructs guide matrix, reconstructs target scattering coefficient to realize super-resolution imaging, finally, the results of two dimensions are multiplied, to obtain non-ambiguous and super-resolution result.The method of the application fully utilizes the advantages of high resolution obtained by platform motion synthetic aperture in squint region and high resolution obtained by azimuth real aperture super-resolution in forward-looking region, overcomes the problem of single-base radar forward-looking imaging ambiguity and low resolution, and realizes multichannel radar non-ambiguous forward-looking high-resolution imaging.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of radar imaging, and particularly relates to a real synthetic aperture imaging method for multi-channel radar forward imaging. BACKGROUND

[0002] Radar forward-looking imaging has important applications in the fields of autonomous landing, autonomous navigation, forward-looking reconnaissance guidance, etc. However, due to the reasons of Doppler symmetry ambiguity and small Doppler variation in the forward-looking area, the conventional single-channel SAR or Doppler beam sharpening technology has a forward-looking imaging blind area. The bistatic SAR can realize the imaging of the forward-looking area of the receiving platform through the separation of the transmitter and receiver, but due to the assistance of an external radiation source, the imaging autonomy is limited, and the separation of the transmitter and receiver introduces complex synchronization and motion compensation problems.

[0003] The document "G. Krieger, J. Mittermayer, M. Wendler, F. Witte, and A. Moreira, Sirev-sector imaging radar for enhanced vision. Proceedings of the 2nd International Symposium on Image and Signal Processing and Analysis. 2001" proposes that it is possible to form an aperture in the azimuth direction and have the potential for forward-looking imaging by using one or more transmit channels and multiple receive channels on a single platform. However, due to the size limitation of the platform, the azimuth resolution of the forward-looking multi-channel radar is usually low. In order to improve the azimuth resolution, different algorithms have been developed in recent years to realize the super-resolution imaging of the multi-channel radar, for example, the document "Zhang Jie, Wu Di, Zhu Daoyin. An airborne / missile array radar forward-looking super-resolution imaging algorithm. Radar Science and Technology, 2018, 16 (2): 6" proposes to use the MUSIC algorithm for forward-looking super-resolution imaging. Since the algorithm needs to know the number of sources, and usually needs multiple snapshot data to obtain better performance. The document "Wang Jian, Zong Zhelin. Forward-looking SAR compressive sensing imaging algorithm. Radar Science and Technology, 2012, 10 (1): 27-31" studies the forward-looking super-resolution imaging of compressive sensing. However, the imaging performance is usually limited by the signal-to-noise ratio of the echo data. The document "Lu Jingyue, Zhang Lei, Wang Guanyong. Forward-looking multi-channel synthetic aperture radar deblurring imaging method. Journal of Electronics and Information Engineering, 2018, 40 (12): 2820-2825" proposes a multi-channel forward-looking synthetic aperture radar scheme. In this scheme, the platform Doppler information is first used to obtain a forward-looking image with left / right ambiguity, and then the data of multiple channels are combined to resolve the left / right ambiguity. Since its azimuth resolution mainly depends on the change of the viewing angle, this scheme can obtain good resolution in the platform squint region. However, in the normal forward-looking observation region, its azimuth resolution is still poor due to the small change of the viewing angle. SUMMARY

[0004] To solve the above technical problems, the present application proposes a real synthetic aperture imaging method for forward-looking imaging of a multi-channel radar, which aims to overcome the problems of left / right Doppler ambiguity in single-base radar forward-looking imaging and low resolution in the normal forward-looking region, and realizes real synthetic aperture imaging of a multi-channel radar in forward-looking.

[0005] The technical scheme of the present application is as follows: a real synthetic aperture imaging method for forward-looking imaging of a multi-channel radar, the specific steps are as follows:

[0006] A, obtaining echo data of the region to be imaged;

[0007] Multi-channel radar forward-looking imaging adopts a single-transmit multi-receive channel configuration, in which multiple receiving channels receive simultaneously; assuming that the transmitted signal is a linear frequency modulation pulse, the echo signals received by multiple channels S echo (y i , t r , t a ) can be expressed as:

[0008]

[0009] wherein β0represents a constant preset, K r represents a distance frequency, c represents a light speed, λ represents a wavelength of the transmitted signal, t r represents a fast time, t a represents a slow time, y i represents an azimuth coordinate of the ith receiving antenna, w r represents a distance envelope, R(t a , y i ) represents a two-way distance history.

[0010] The distance history R Tx (t a ) from the transmitting antenna to any point P(x0, y0) in the observed scene and the distance history R Rx (t a , y i ) from the different receiving antennas to the point P(x0, y0) are expressed as:

[0011]

[0012]

[0013] wherein v r represents a flight speed of the platform, and h represents a flight height of the platform.

[0014] Then, for a point target, the two-way distance history R(t a , y i ) is expressed as:

[0015] R(t a , y i ) = R Rx (t a , y i ) + R Tx (t a ) (4)

[0016] B, distance direction pulse compression is performed on the acquired data;

[0017] A matching function S ref (t r ) = exp(-jπKr t r 2 , then the pulse compressed signal S c (y i , t r , t a ) is shown as:

[0018] S c (y i , t r , t a ) = IFFT{FFT[S echo (y i , t r , t a ) · FFT[S ref (t r )]}

[0019]

[0020] where IFFT denotes the inverse Fourier transform operator and FFT denotes the Fourier transform operator

[0021] The echo S1(t r , t a ) of the arbitrary channel synthetic aperture is expressed as:

[0022]

[0023] where R(t a ) denotes the two-way range history.

[0024] In a given slow time, the instantaneous data of multiple channels are formed into snapshots or real aperture data, and the echo S2(y i , t r ) of the real aperture is obtained:

[0025]

[0026] where R(y i ) denotes the two-way range history.

[0027] C. Synthetic aperture dimension processing;

[0028] First, the range pulse compression data S1(t r , t a ) of each channel is coherently accumulated using the polar coordinate back-projection algorithm, and the reconstruction result f bp (ρ, γ) is expressed as:

[0029]

[0030] where p represents the slant range, and y represents the azimuth angle.

[0031] D, real aperture super resolution processing;

[0032] For equation (7), according to the knowledge of array signal processing, if the antenna array is composed of M channels and N remote narrowband signals incident on the spatial array, the received signal z of the i-th channel of a certain range unit is i represented as:

[0033]

[0034] where β k represents the scattering coefficient of the k-th target, n i represents the noise of the i-th channel, τ ki represents the delay of the k-th signal reaching the i-th channel relative to the reference channel, i.e., the wave path difference delay, represents the wave path difference phase, and f0 represents the carrier frequency of the transmitted signal.

[0035] The same grid is divided for the scene to represent the position P(ρcosγ k , ρsinγ k ) of the k-th target, and γ k represents the azimuth angle of the k-th target. Equation (7) is the result of taking the first snapshot, and at this time the position of each receiving element is represented as (0, y i , h). Then the following formula is used to obtain τ ki :

[0036]

[0037] Then the echo of a range unit formed by different channels can be written as:

[0038]

[0039] and equation (11) can be written as:

[0040] Z M×1 = A M×N · β N×1 + N M×1 (12)

[0041] where Z M×1 represents the echo vector in a range unit, N M×1 represents the noise vector, A M×N represents the steering matrix, β N×1 represents the scattering coefficient vector.

[0042] According to equation (12), the weighted least squares cost function is defined in the form as follows:

[0043]

[0044] wherein Z M×1 is a diagonal matrix, and a k denotes the k-th column of the steering matrix A, R denotes the covariance matrix, and R = A H P denotes a diagonal matrix, and the diagonal elements denotes the target scattering coefficient, and (·) H denotes the transpose operation of a matrix.

[0045] The partial derivative of in equation (13) is taken, and the result is set to zero, to obtain:

[0046]

[0047] According to the matrix inversion lemma, we have Substituting it into equation (14), we have:

[0048]

[0049] The diagonal loading regularization covariance matrix is used, i.e. in the covariance matrix R, a positive diagonal matrix μI M×M is introduced.

[0050] wherein μ denotes the regularization coefficient, μ > 0, and I M×M denotes a positive diagonal matrix. Then the iteration steps are as follows:

[0051] a. Calculate

[0052] b. Calculate the covariance matrix R = A M×N · diag(P) · (A M×N ) H + μI M×M ;

[0053] c. Update

[0054] d. Return to step a.

[0055] Finally, the imaging result f riaa (ρ, γ) is obtained, i.e. the reconstruction result of the scattering coefficient .

[0056] E. Image fusion;

[0057] The synthetic aperture processing result and the real aperture super-resolution result are fused, and the final imaging result f(ρ, γ) is obtained by:

[0058] f(p, g) = f bp (p, g) f riaa (p, g) (16)

[0059] The method of the present application first acquires echo data of the region to be imaged, then performs range direction pulse compression on the acquired data, and then respectively processes the pulse compressed data in the synthetic aperture and the real aperture. For the synthetic aperture dimension, the BP algorithm is used for azimuth focusing, and the results of each channel are incoherently accumulated to obtain a left-right blurred image. For the real aperture dimension, the imaging scene is divided into a grid, a steering matrix is constructed, and the target scattering coefficient is reconstructed to realize super-resolution imaging. Finally, the results of the two dimensions are multiplied to obtain a non-blurred and super-resolved result. The method of the present application fully utilizes the advantages of high resolution in the squint region by platform motion synthetic aperture and high resolution in the forward-looking region by azimuth real aperture super resolution, overcomes the problems of blurred forward-looking imaging and low resolution of single-base radar, and realizes multi-channel radar non-blurred forward-looking high-resolution imaging. BRIEF DESCRIPTION OF DRAWINGS

[0060] Figure 1 It is a geometric model diagram of multi-channel radar forward-looking imaging in the embodiment of the present application.

[0061] Figure 2 It is a flowchart of a real synthetic aperture imaging method for multi-channel radar forward-looking imaging of the present application.

[0062] Figure 3 It is a schematic diagram of an observed scene in the embodiment of the present application.

[0063] Figure 4 It is a schematic diagram of synthetic aperture dimension echo of an observed scene in the embodiment of the present application.

[0064] Figure 5 It is a schematic diagram of real aperture dimension echo of an observed scene in the embodiment of the present application.

[0065] Figure 6 It is a schematic diagram of synthetic aperture dimension pulse compressed echo of an observed scene in the embodiment of the present application.

[0066] Figure 7 It is a schematic diagram of real aperture dimension pulse compressed echo of an observed scene in the embodiment of the present application.

[0067] Figure 8 It is a schematic diagram of synthetic aperture dimension single-channel imaging of an observed scene in the embodiment of the present application.

[0068] Figure 9 It is a schematic diagram of real aperture dimension super-resolution imaging of an observed scene in the embodiment of the present application.

[0069] Figure 10 This is a schematic diagram of the fusion of two imaging dimensions of the observation scene in an embodiment of the present invention. Detailed Implementation

[0070] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0071] In this embodiment, the geometric configuration of the forward-looking multi-channel radar is as follows: Figure 1 As shown in Table 1, the parameters of the forward-looking multi-channel radar are as follows:

[0072] Table 1

[0073] Parameter Symbol Value Unit Carrier flight height h 5000 m Carrier flight speed v r ]]> 400 m / s Pulse width [TECHNICAL FIELD] r ]] 1 μs Signal bandwidth B 60 MHz Array antenna length [[ L e ]]> 3.00 m Pulse repetition frequency PRF 400 Hz Transmit signal wavelength λ 0.0315 m Signal-to-noise ratio after range-pulsing SNR 10 dB Synthetic aperture length [[ L s ]]> 80 m Number of range samples <![CDATA[N r ]]> 256 Number of channels

[0009] N a ]] 64 Number of synthetic aperture dimension samples <![CDATA[N sa ]]> 128

[0074] like Figure 1 As shown, in an xyz coordinate system, O represents the origin of the coordinate system, and the forward-looking multi-channel radar travels at a velocity v. r =400m / s, altitude h=5000m, flying at a constant speed in a straight line along the X-axis, forming a formation of length L s The synthetic aperture. The center position of the target scene is X. c =5000m, Y c =0m, Z c =0, meaning the angle between the aircraft and the center of the scene is 45 degrees. ° On the platform, the channels are evenly arranged along the Y-axis, with the transmission channel T... x Signals are transmitted at a pulse repetition frequency (PRF = 400Hz), and each channel receives signals simultaneously, where R xi This represents the i-th receiving channel, with an antenna element spacing of d = L. e / (N a -1)≈0.047m, which is equivalent to having a real aperture on the Y-axis. In this simulation, it is assumed that the radar transmitted signal wavelength is λ=0.0315m and the pulse duration T r A linear frequency modulated pulse signal with a duration of 1 μs and a bandwidth of B = 60 MHz. The number of sampling points N in the distance direction. r The number of channels is 256, and the number of channels is N. a The number of sampling points N in the synthetic aperture dimension is 64. sa The signal-to-noise ratio of the echo after pulse compression is 10dB, which is 128.

[0075] like Figure 2 The flowchart shown is a real synthetic aperture imaging method for forward-looking imaging of multi-channel radar according to the present invention. The specific steps are as follows:

[0076] A. Acquire echo data of the area to be imaged;

[0077] like Figure 3As shown, the azimuth direction length of the scene in the embodiment is-8.5°-8.5°, and the distance direction length is 250 m. For each channel, according to the number of sampling points in the synthetic aperture dimension and the number of distance sampling points N sa and N r , assuming that the scene is uniformly divided into a 64*256 grid, the transmission distance R Tx (t a ) and the receiving distance R Rx (t a ,y i ) can be calculated using formula (2) (3), and then the echo signal can be calculated using formula (1). The echo of the first channel is selected for display, as shown in Figure 4 . The results of the first fast flicker of each channel are taken to form the echo in the real aperture dimension, as shown in Figure 5 .

[0078] B, distance direction pulse compression is performed on the obtained data;

[0079] Assuming that the center position of the target scene is X c =5000 m, Y c =0 m, Z c =0, the reference transmission distance and receiving distance are calculated using formula (2) (3), and then the fast time t r and the pulse compression matching function S ref (t r ) = exp(-jπK r t r 2 ) are obtained. Considering the echo data generated in step A in the embodiment, the results of pulse compression of the echo of each channel can be obtained using formula (4). Noise is added in each channel so that the signal-to-noise ratio of each channel after pulse compression is 10 dB. Figure 6 The results of distance direction pulse compression of the first channel are displayed. The echo after distance direction pulse compression of the first fast flicker of each channel is taken, as shown in Figure 7 .

[0080] C, synthetic aperture dimension processing;

[0081] For the synthetic aperture echo of a channel of formula (7), according to formula (2) and (3), (4), the back projection (Back Projection, BP) algorithm is used to perform coherent accumulation according to formula (8) to obtain the azimuth direction focusing result, as shown in Figure 8 . At this time, there is left-right blur in the imaging result, and the center resolution of the scene is low.

[0082] D, real aperture super-resolution processing;

[0083] Using the 64x256 grid divided in A, combined with equation (10) to get the time delay τ of each grid point ki , a steering matrix A of one distance unit is constructed M×N , since is related to the target, it needs to be solved iteratively. In addition, since the steering matrix A M×N may be ill-conditioned, which is not conducive to super-resolution at low signal-to-noise ratio, a diagonal loaded regularized covariance matrix is adopted, that is, a positive diagonal matrix μI is introduced in the covariance matrix R M×M , the regularization coefficient μ is set to 0.1, and then the super-resolution imaging result can be obtained by iterating 15 times according to the iterative steps in step D in the disclosure content, as shown in Figure 9 .

[0084] E. Image fusion

[0085] For the synthetic aperture imaging result obtained in step C, since only one channel data is used, there will be left / right blur, and since the angle change is relatively large, the azimuth resolution for the area far from the flight path is significantly improved. However, in the adjacent area of the flight path, the azimuth resolution is still limited by the actual aperture size formed by the azimuth multi-channel.

[0086] And for the real aperture super-resolution result obtained in step D, since super-resolution processing is performed, the resolution of the adjacent area of the flight path is better than that of the synthetic aperture, and there is no left / right blur. However, due to the limitation of signal-to-noise ratio, the resolution improvement of this method is limited, especially in the area far from the flight path, the resolution capability is usually worse than that of the synthetic aperture scheme.

[0087] Since the two processing methods display imaging results on the same grid, f bp (ρ,γ) and f riaa (ρ,γ) obtained according to steps C and D, and then using equation (16), the final fusion result f(ρ,γ) is obtained, as shown in Figure 10 .

[0088] Using the real synthetic aperture imaging method for multi-channel radar forward-looking imaging in this embodiment, the problems of single-base radar forward-looking imaging blur and low imaging resolution are solved. Specifically, by utilizing the advantages of high resolution in the squint region obtained by platform motion synthetic aperture and high resolution in the forward-looking region obtained by azimuth real aperture super-resolution, the results of two dimensions are fused, and multi-channel radar non-blur forward-looking high-resolution imaging can be realized.

[0089] Those skilled in the art will appreciate that the embodiments described herein are presented for purposes of illustration and understanding of the principles of the application and should not be construed as limiting the scope of the application to such specifically enumerated embodiments. Various modifications and changes can be made to the application by those skilled in the art which will be apparent from this disclosure without departing from the spirit and principles of the application. Any modifications, equivalent substitutions, improvements, etc. made to the application should be included within the scope of the application as defined in the following claims.

Claims

1. A real synthetic aperture imaging method for forward-looking imaging of multi-channel radar, the specific steps of which are as follows: A. Acquire echo data of the area to be imaged; Multi-channel radar forward-looking imaging employs a single-transmitter, multi-receiver channel configuration, in which... Multiple receiving channels receive signals simultaneously; assuming the transmitted signal is a linear frequency modulated pulse, the echo signals S received by the multiple channels... echo (y i ,t r ,t a This can be represented as: Where β0 represents a pre-defined constant, K r The distance represents the frequency modulation, c represents the speed of light, λ represents the wavelength of the emitted signal, and t represents the distance frequency modulation. r t indicates fast time. a Indicates slow time, y i Let w represent the azimuth coordinates of the i-th receiving antenna. r R(t) represents the distance to the envelope. a ,y i This indicates the history of two-way distances; The distance history R from any point P(x0,y0) in the observation scene to the transmitting antenna Tx (t a ) and distance history R to different receiving antennas Rx (t a ,y i This can be represented as: Among them, v r h represents the platform's flight speed, and h represents the platform's flight altitude; For a point target, the two-way distance history R(t) a ,y i ) is represented as: R(t a ,y i )=R Rx (t a ,y i )+R Tx (t a ) (4) B. Perform range-direction pulse compression on the acquired data; Set the matching function for pulse compression to S. ref (t r )=exp(-jπK r t r 2 Then the pulse-compressed signal S c (y i ,t r ,t a This is shown as: S c (y i ,t r ,t a )=IFFT{FFT[S echo (y i ,t r ,t a )]·FFT[S ref (t r )]} Wherein, IFFT represents the inverse Fourier transform operator, and FFT represents the Fourier transform operator. Then the echo S1(t) of any channel synthesized aperture r ,t a ) is represented as: Wherein, R(t) a This indicates the history of two-way distances; At a given slow time, instantaneous data from multiple channels are captured as a snapshot or real aperture data to obtain the real aperture echo S2(y). i ,t r ): Among them, R(y) i This indicates the history of two-way distances; C. Processing of synthetic aperture dimensions; First, the distance pulse compression data S1(t) of each channel is processed. r ,t a If a polar coordinate back projection algorithm is used for coherent accumulation, then the reconstruction result f bp (ρ,γ) is represented as: Where ρ represents the slant distance and γ represents the azimuth angle; D. Real aperture super-resolution processing; For equation (7), according to the knowledge of array signal processing, if the antenna array consists of M channels and N long-range narrowband signals incident on the spatial array, then the received signal z of the i-th channel of a certain range element... i Represented as: Where, β k Let n represent the scattering coefficient of the k-th target. i τ represents the noise of the i-th channel. ki This represents the delay relative to the reference channel when the k-th signal arrives at the i-th channel, i.e., the path difference delay. f0 represents the path difference phase, and f0 represents the carrier frequency of the transmitted signal; The scene is divided into identical grids to represent the position P(ρcosγ) of the k-th target. k ,ρsinγ k ), γ k This represents the azimuth angle of the k-th target; Equation (7) is the result of taking the first snapshot, at which point the positions of each receiving array element are represented as (0, y). i If τ = h), then the following formula is used to obtain τ. ki : The echo of a single range cell formed by different channels can then be written as: And equation (11) can be written as: Z M×1 =A M×N ·β N×1 +N M×1 (12) Among them, Z M×1 N represents the echo vector in a range cell. M×1 Represents the noise vector, A M×N Denotes the guidance matrix, β N×1 Represents the scattering coefficient vector; According to equation (12), the weighted least squares cost function is defined. The format is as follows: Among them, Z M×1 Abbreviated as Z, a k This represents the k-th column of the guidance matrix A. R represents the covariance matrix, and R = A·P·A H P represents a diagonal matrix, and the diagonal elements are... Represents the target scattering coefficient, (·) H This indicates that the matrix is ​​transposed. For equation (13) Taking the partial derivative and setting the result to zero, we get: According to the matrix inversion lemma, we can obtain... Substituting it into equation (14), we get: A diagonally loaded regularized covariance matrix is ​​used, that is, a diagonal matrix μI is introduced into the covariance matrix R. M×M ; Where μ represents the regularization coefficient, μ>0, I M×M Let represent a diagonal matrix; then the iteration steps are as follows: a. Calculation b. Calculate the covariance matrix R = A M×N ·diag(P)·(A M×N ) H +μI M×M ; c. Update d. Return to step a; The final imaging result f riaa (ρ,γ), i.e., scattering coefficient The reconstruction results; E. Image fusion; The synthetic aperture processing result is fused with the real aperture super-resolution result, and the final imaging result f(ρ,γ) is obtained by the following formula: f(ρ,γ)=f bp (p,c)·f riaa (p,c) (16).

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