Synthetic aperture radar imaging method and system based on agile pulse repetition frequency

Abstract

The present invention provides a synthetic aperture radar imaging method and system based on agile pulse repetition frequency, comprising: step 1: arranging and combining the signals of the channels according to the order of receiving time; step 2: performing range pulse compression on the signals after the arrangement and combination; step 3: transforming the echo signal after the range pulse compression into the range frequency domain; step 4: converting the signals after the arrangement and combination into a uniform sampling signal by using time scale transformation; step 5: performing range migration correction according to the uniform sampling signal; step 6: performing azimuth compression to complete point target SAR imaging. The method of the present invention has fast running speed and high precision, and is conducive to real-time processing of engineering.

Description

Technical Field

[0001] The present invention relates to the technical field of synthetic aperture radar imaging, and in particular to a synthetic aperture radar imaging method and system based on agile pulse repetition frequency. Background Art

[0002] For the HRWS system, since the Doppler bandwidth of the echo signal is much larger than the PRF, the signal of each channel will experience Doppler aliasing. If SAR imaging is directly performed, the final imaging result will be blurred, reducing the image quality.

[0003] Patent document CN106772368B (application number: CN201611090487.2) discloses a super-resolution three-dimensional imaging method of a multi-random frequency radar array, which mainly realizes real-time and fast super-resolution three-dimensional imaging in high-dimensional and single-pulse conditions. The implementation process is as follows: each transmitting array element in the transmitting array transmits signals of different frequencies to form a random radiation field in space. After the transmitting signal in the random radiation field hits the target, the scattered signal is received by the receiving array composed of receiving array elements to obtain the radar echo signal; the radar echo signal is stretched into an observation vector to construct a three-dimensional grid sparse recovery observation model. However, the data processing of this patent is complex, resulting in slow operation and low accuracy. Summary of the invention

[0004] In view of the defects in the prior art, an object of the present invention is to provide a synthetic aperture radar imaging method and system based on agile pulse repetition frequency.

[0005] The synthetic aperture radar imaging method based on agile pulse repetition frequency provided by the present invention comprises:

[0006] Step 1: Arrange and combine the channel signals in the order of receiving time;

[0007] Step 2: Perform range pulse compression on the arranged and combined signals;

[0008] Step 3: transform the echo signal after range pulse compression into range frequency domain;

[0009] Step 4: Use time scale transformation to convert the permuted and combined signal into a uniformly sampled signal;

[0010] Step 5: Perform range migration correction based on the uniformly sampled signal;

[0011] Step 6: Perform azimuth compression to complete point target SAR imaging.

[0012] Preferably, the azimuth multi-channel SAR sets M evenly spaced receiving channels in the azimuth direction, the channel spacing is d, the radar platform uniform motion speed is v, and channel 1 is set as the reference channel, then the distance from channel m to the reference channel is recorded as d m =(M-1)d, m=1,...,M;

[0013] The Cartesian geometric coordinate system of the azimuth multi-channel SAR is established. The X-axis represents the direction of movement of the radar platform, the Z-axis represents the direction away from the earth, H represents the height of the radar platform, R0 represents the slant distance from the target P(x0,y0,0) to the radar platform at the initial time point, and R m (t a ) represents the instantaneous slant distance from target P to receiving channel m, t a represents the azimuth slow time variable, θ Cone represents the spatial cone angle, θ El represents the downward viewing angle, θ Azi represents the azimuth, and the three angles have the following relationship:

[0014] sinθ Cone = cosθ Azi sinθ El

[0015] The radar platform moves in a straight line within the preset time. Using the equivalent phase center principle, the slant range of the mth receiving channel is expressed as:

[0016]

[0017] Among them, x0 represents the coordinate of the target P on the X-axis at the initial time point; y0 represents the coordinate of the target P on the Y-axis at the initial time point.

[0018] Preferably, the first channel transmits a linear frequency modulation signal, and all channels receive echo signals. The transmitted signal is expressed as:

[0019]

[0020] Among them, t is the distance time series, K r is the modulation frequency, f c is the center frequency of the transmitted signal;

[0021] Then the received signal of the mth channel is:

[0022]

[0023] Where λ is the carrier wavelength; T p represents the pulse width; j represents the imaginary unit; R(t a ) represents the slant range; c represents the speed of light.

[0024] Preferably, in a high-resolution wide-band SAR system, a signal reconstruction algorithm based on time scale transformation is used to restore a periodic non-uniform signal into a uniformly sampled signal, thereby achieving reconstruction of an unambiguous Doppler spectrum of the target signal;

[0025] Establish a non-uniform time signal model, the expression is:

[0026] t a =τ m +γ m =mPRI mean +γ' m PRI mean

[0027] Then the signal after combining the M channels is expressed as:

[0028]

[0029] Perform range Fourier transform and range pulse compression to obtain the range frequency domain-azimuth time domain signal, which is expressed as:

[0030]

[0031] The matching function of range pulse compression is:

[0032]

[0033] Using time scale transformation, the non-uniform time basis m+γ' m Transformed to uniform time basis m', the expression is:

[0034] (f r +f c )(m+γ' m ) = f c ·m'

[0035] Where m'=1,2,…,M', M' represents the number of effective points after time scale transformation; γ' m represents the offset basis, 0≤γ' m <1; f r represents the distance frequency domain; t a Indicates the azimuth time; τ m represents the uniform azimuth time; γ m Indicates the azimuth time offset; PRI mean represents the average pulse repetition interval; A0 represents the signal amplitude after the distance pulse is compressed; R(t a ) represents the slant range history; A1 represents the signal amplitude in the range frequency domain-azimuth time domain; B represents the signal bandwidth; T a represents the aperture time; 2Υ+1 represents the fuzzy number; f dcIndicates the Doppler center frequency.

[0036] Preferably, the range frequency domain-azimuth time domain signal after the time scale transformation after reconstruction is:

[0037]

[0038] Also taking into account:

[0039]

[0040] Therefore, the distance frequency domain-azimuth time domain signal after time scale transformation is written as:

[0041]

[0042] Set the decoupling matched filter to:

[0043]

[0044] After decoupling, the SPECAN or RD algorithm is used to perform azimuth compression to obtain the final imaging result;

[0045] Among them, A2 represents the range frequency domain-azimuth time domain signal amplitude after time scale transformation.

[0046] A synthetic aperture radar imaging system based on agile pulse repetition frequency provided by the present invention comprises:

[0047] Module M1: Arrange and combine the channel signals in the order of receiving time;

[0048] Module M2: Perform range pulse compression on the arranged and combined signals;

[0049] Module M3: transform the echo signal after range pulse compression to the range frequency domain;

[0050] Module M4: Use time scale transformation to convert the permuted and combined signals into uniformly sampled signals;

[0051] Module M5: Perform range migration correction based on uniformly sampled signals;

[0052] Module M6: Perform azimuth compression to complete point target SAR imaging.

[0053] Preferably, the azimuth multi-channel SAR sets M evenly spaced receiving channels in the azimuth direction, the channel spacing is d, the radar platform uniform motion speed is v, and channel 1 is set as the reference channel, then the distance from channel m to the reference channel is recorded as d m =(M-1)d, m=1,...,M;

[0054] The Cartesian geometric coordinate system of the azimuth multi-channel SAR is established. The X-axis represents the direction of movement of the radar platform, the Z-axis represents the direction away from the earth, H represents the height of the radar platform, R0 represents the slant distance from the target P(x0,y0,0) to the radar platform at the initial time point, and R m (t a ) represents the instantaneous slant distance from target P to receiving channel m, t a represents the azimuth slow time variable, θ Cone represents the spatial cone angle, θ El represents the downward viewing angle, θ Azi represents the azimuth, and the three angles have the following relationship:

[0055] sinθ Cone = cosθ Azi sinθ El

[0056] The radar platform moves in a straight line within the preset time. Using the equivalent phase center principle, the slant range of the mth receiving channel is expressed as:

[0057]

[0058] Among them, x0 represents the coordinate of the target P on the X-axis at the initial time point; y0 represents the coordinate of the target P on the Y-axis at the initial time point.

[0059] Preferably, the first channel transmits a linear frequency modulation signal, and all channels receive echo signals. The transmitted signal is expressed as:

[0060]

[0061] Among them, t is the distance time series, K r is the modulation frequency, f c is the center frequency of the transmitted signal;

[0062] Then the received signal of the mth channel is:

[0063]

[0064] Where λ is the carrier wavelength; T p represents the pulse width; j represents the imaginary unit; R(t a ) represents the slant range; c represents the speed of light.

[0065] Preferably, in a high-resolution wide-band SAR system, a signal reconstruction algorithm based on time scale transformation is used to restore a periodic non-uniform signal into a uniformly sampled signal, thereby achieving reconstruction of an unambiguous Doppler spectrum of the target signal;

[0066] Establish a non-uniform time signal model, the expression is:

[0067] t a =τ m +γ m =mPRI mean +γ' m PRI mean

[0068] Then the signal after combining the M channels is expressed as:

[0069]

[0070] Perform range Fourier transform and range pulse compression to obtain the range frequency domain-azimuth time domain signal, which is expressed as:

[0071]

[0072] The matching function of range pulse compression is:

[0073]

[0074] Using time scale transformation, the non-uniform time basis m+γ' m Transformed to uniform time basis m', the expression is:

[0075] (f r +f c )(m+γ' m ) = f c ·m'

[0076] Where m'=1,2,…,M', M' represents the number of effective points after time scale transformation; γ' m represents the offset basis, 0≤γ' m <1; f r represents the distance frequency domain; t a Indicates the azimuth time; τ m represents the uniform azimuth time; γ m Indicates the azimuth time offset; PRI mean represents the average pulse repetition interval; A0 represents the signal amplitude after the distance pulse is compressed; R(t a ) represents the slant range history; A1 represents the signal amplitude in the range frequency domain-azimuth time domain; B represents the signal bandwidth; T a represents the aperture time; 2Υ+1 represents the fuzzy number; f dc Indicates the Doppler center frequency.

[0077] Preferably, the range frequency domain-azimuth time domain signal after the time scale transformation after reconstruction is:

[0078]

[0079] Also taking into account:

[0080]

[0081] Therefore, the distance frequency domain-azimuth time domain signal after time scale transformation is written as:

[0082]

[0083] Set the decoupling matched filter to:

[0084]

[0085] After decoupling, the SPECAN or RD algorithm is used to perform azimuth compression to obtain the final imaging result;

[0086] Among them, A2 represents the range frequency domain-azimuth time domain signal amplitude after time scale transformation.

[0087] Compared with the prior art, the present invention has the following beneficial effects:

[0088] The present invention proposes a method for azimuth multi-channel reconstruction in a high-resolution wide-band mode based on time scale transformation. Compared with the traditional space-time adaptive algorithm and the Doppler fuzzy suppression algorithm based on a filter group, the algorithm has a fast running speed and high accuracy, which is conducive to real-time processing of engineering. BRIEF DESCRIPTION OF THE DRAWINGS

[0089] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0090] Figure 1 It is a flow chart of the method for multi-channel reconstruction of orientation in a high-resolution wide-band mode based on time scale transformation of the present invention;

[0091] Figure 2a is the original echo signal diagram of channel 1, Figure 2b is the Doppler spectrum of channel 1, Figure 2c and Figure 2d They are the imaging result of the point target after azimuth compression and the azimuth slice diagram respectively;

[0092] Figure 3 This is a diagram of the azimuth multi-channel SAR three-dimensional model of the present invention. DETAILED DESCRIPTION

[0093] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0094] Example:

[0095] like Figure 1 The present invention provides a method for multi-channel reconstruction of position in a high-resolution wide-band mode based on time scale transformation, comprising the following steps:

[0096] Step 1: First, arrange and combine the signals of M channels in the order of receiving time;

[0097] Step 2: Perform range pulse compression on the signal processed in step 1;

[0098] Step 3: transform the echo signal after the range pulse compression into the range frequency domain;

[0099] Step 4: Use time scale transformation to convert the combined signal in step 1 into a uniformly sampled signal;

[0100] Step 5: Distance migration correction;

[0101] Step 6: Azimuth compression completes point target SAR imaging.

[0102] Specifically, assume that the azimuth multi-channel SAR sets M evenly spaced receiving channels in the azimuth direction, the channel spacing is d, and the radar platform moves at a uniform speed of v. Set channel 1 as the reference channel, then the distance from channel m (m = 1, ..., M) to the reference channel can be recorded as d m =(M-1)d. Figure 3 The Cartesian geometric coordinate system of the azimuth multi-channel SAR is represented by the X-axis, which represents the direction of the radar platform, the Z-axis, which represents the direction away from the earth, and H, which represents the height of the radar platform. R0 represents the slant distance from the target P(x0,y0,0) to the radar platform at the initial time point, and R m (t a ) represents the instantaneous slant distance from target P to receiving channel m, θ Cone represents the spatial cone angle, θ El represents the downward viewing angle, θ Azi represents the azimuth, and the three angles have the following relationship:

[0103] sinθ Cone = cosθ Azi sinθ El

[0104] For the convenience of analysis, it is considered that the radar platform moves in a straight line in a short period of time. Figure 3 It can be seen that, using the equivalent phase center principle, the slant range of the mth receiving channel can be expressed as:

[0105]

[0106] Among them, t a Represents the azimuth slow-time variable.

[0107] Without loss of generality, assume that the first channel transmits a linear frequency modulation signal and all channels receive echo signals. The transmitted signal can be expressed as:

[0108]

[0109] Among them, t is the distance time series, K r is the modulation frequency, f c is the center frequency of the transmitted signal.

[0110] Then the received signal of the mth channel is:

[0111]

[0112] Where λ is the carrier wavelength.

[0113] The distance compression matching function is as follows:

[0114]

[0115] In the formula, f r Indicates the distance frequency.

[0116] For the HRWS system, since the Doppler bandwidth of the echo signal is much larger than the PRF, Doppler aliasing will occur in the signal of each channel. The purpose of the signal reconstruction algorithm based on time scale transformation is to restore the time non-uniform sampling signal that does not meet the optimal configuration into an ideal signal with time uniform sampling through time scale transformation. Therefore, in the high-resolution wide-band SAR system, this algorithm can be used to restore the periodic non-uniform signal into a uniformly sampled signal, thereby realizing the reconstruction of the unambiguous Doppler spectrum of the target signal.

[0117] The non-uniform time signal model is established as:

[0118] t a =τ m +γ m =mPRI mean +γ' m PRI mean

[0119] Then the signal after combining the M channels can be expressed as:

[0120]

[0121] Perform range Fourier transform and range pulse compression to obtain the range frequency domain-azimuth time domain signal, which is expressed as:

[0122]

[0123] Using time scale transformation, the non-uniform time basis m+γ' m Transform to uniform time basis m':

[0124] (f r +f c )(m+γ' m ) = f c ·m'

[0125] Where m'=1, 2, ..., M', M' represents the number of effective points of the orientation after the time scale transformation.

[0126] In the formula, f r , f c Represents the range frequency domain and the center carrier frequency. m'=1,2,…,M', M' represents the number of effective points of azimuth after time scale transformation. γ' m (0≤γ' m <1) indicates an offset basis.

[0127] The range frequency domain-azimuth time domain signal after time scale transformation is:

[0128]

[0129] Since the azimuthally uniform time can be expressed as the product of the uniform time base and the average pulse repetition interval, that is:

[0130] t m '=m'PRI mean

[0131] Also taking into account:

[0132]

[0133] Therefore, the above signal can also be written as:

[0134]

[0135] Set the decoupling matched filter to:

[0136]

[0137] After decoupling, the SPECAN or RD algorithm is used for azimuth compression to obtain the final imaging result.

[0138] The effect of the present invention can be further illustrated by the following simulation:

[0139] (1) Simulation conditions

[0140] The simulation experiment platform parameters are given in Table 1. All implementation steps of this example are carried out on the MATLAB2018B simulation platform.

[0141] Table 1 Simulation system parameters

[0142] parameter Value Antenna panel azimuth aperture 10.24m wavelength 0.03m Carrier frequency 9.6GHz Number of azimuth channels 10 Track height 700km Antenna panel distance aperture 1.5m Signal bandwidth 240MHz

[0143] (2) Simulation content

[0144] To analyze the performance of the reconstruction algorithm in this section, the following simulation experiment analysis is carried out using a signal bandwidth of 240MHz, an antenna panel azimuth size of 10.24m, 10 azimuth channels, a carrier frequency of 9.6GHz, and a pulse repetition frequency of 1542Hz as an example. The following figure shows the simulation results. Figure 2a It shows the original echo signal of channel 1. Figure 2b The Doppler spectrum of channel 1 is shown. Figure 2b It can be seen that since the pulse repetition frequency is less than the Doppler bandwidth, the Doppler spectrum folding phenomenon occurs. After reconstruction using the reconstruction algorithm in this section, Figure 2c and Figure 2d The imaging results of the point target after azimuth compression and the azimuth slice diagram are given respectively. Table 2 shows the statistics of the azimuth ambiguity signal ratio, output signal-to-noise ratio, signal-to-noise ratio ratio factor, reconstruction algorithm running time and other indicators of the algorithm of the present invention. It can be seen from the table that the running time of the reconstruction algorithm of the present invention is 2.4s, the processing time is short, and it is conducive to real-time processing of the project. Tables 3 and 4 respectively show the indicator statistics of azimuth multi-channel reconstruction using the space-time adaptive algorithm and the filter group algorithm. Obviously, the algorithm of the present invention is both short and highly accurate.

[0145] Table 2 Statistics of algorithm indicators of the present invention

[0146] <![CDATA[Signal-to-noise ratio SNR after distance compression in (dB)]]> 20dB <![CDATA[Theoretical output signal-to-noise ratio SNR out (dB)]]> 60.66B <![CDATA[Actual output signal-to-noise ratio SNR out (dB)]]> 60.02dB <![CDATA[SNR ratio factor Φ bf (dB)]]> 0.64dB Azimuth Ambiguity Signal Ratio AASR (dB) -50.45dB Running time of reconstruction algorithm (s) 2.4s

[0147] Table 3 Statistics of space-time adaptive algorithm indicators

[0148] <![CDATA[Signal-to-noise ratio SNR after distance compression in (dB)]]> 20dB <![CDATA[Theoretical output signal-to-noise ratio SNR out (dB)]]> 61.65dB <![CDATA[Actual output signal-to-noise ratio SNR out (dB)]]> 58.40dB <![CDATA[SNR ratio factor Φ bf (dB)]]> 3.25dB Azimuth Ambiguity Signal Ratio AASR (dB) -42.51dB Running time of reconstruction algorithm (s) 120.81s

[0149] Table 4 Statistics of filter bank algorithm indicators

[0150] <![CDATA[Signal-to-noise ratio SNR after distance compression in (dB)]]> 20dB <![CDATA[Theoretical output signal-to-noise ratio SNR out (dB)]]> 61.66dB <![CDATA[Actual output signal-to-noise ratio SNR out (dB)]]> 58.28dB <![CDATA[SNR Scaling Factor Φ bf (dB)]]> 3.37dB Azimuth Ambiguity Signal Ratio AASR (dB) -37.98dB Running time of reconstruction algorithm (s) 7454s

[0151] The synthetic aperture radar imaging system based on agile pulse repetition frequency provided by the present invention comprises: module M1: arranging and combining the signals of the channels according to the order of receiving time; module M2: performing range pulse compression on the signals after the arrangement and combination; module M3: transforming the echo signals after the range pulse compression into the range frequency domain; module M4: converting the signals after the arrangement and combination into uniform sampling signals by using time scale transformation; module M5: performing range migration correction according to the uniform sampling signals; module M6: performing azimuth compression to complete point target SAR imaging.

[0152] Azimuth multi-channel SAR sets M evenly spaced receiving channels in azimuth, with a channel spacing of d. The radar platform moves at a uniform speed of v. Channel 1 is set as the reference channel, and the distance from channel m to the reference channel is recorded as d. m =(M-1)d, m=1,...,M; establish the Cartesian geometric coordinate system of the azimuth multi-channel SAR, where the X-axis represents the direction of movement of the radar platform, the Z-axis represents the direction away from the earth, H represents the height of the radar platform, R0 represents the slant distance from the target P(x0,y0,0) to the radar platform at the initial time point, and R m (t a ) represents the instantaneous slant distance from target P to receiving channel m, t a represents the azimuth slow time variable, θ Cone represents the spatial cone angle, θ El represents the downward viewing angle, θ Azi represents the azimuth, and these three angles have the following relationship: sinθ Cone = cosθ Azi sinθ El ; Within the preset time, the radar platform moves in a straight line. Using the equivalent phase center principle, the slant range of the mth receiving channel is expressed as:

[0153]

[0154] Among them, x0 represents the coordinate of the target P on the X-axis at the initial time point; y0 represents the coordinate of the target P on the Y-axis at the initial time point.

[0155] The first channel transmits a linear frequency modulation signal, and all channels receive echo signals. The transmitted signal is expressed as: Among them, t is the distance time series, K r is the modulation frequency, f c is the center frequency of the transmitted signal; then the received signal of the mth channel is:

[0156]

[0157] Where λ is the carrier wavelength; T p represents the pulse width; j represents the imaginary unit; R(ta ) represents the slant range; c represents the speed of light.

[0158] In the high-resolution wide-band SAR system, a signal reconstruction algorithm based on time scale transformation is used to restore the periodic non-uniform signal to a uniformly sampled signal, thereby realizing the reconstruction of the unambiguous Doppler spectrum of the target signal; a non-uniform time signal model is established, and the expression is: a =τ m +γ m =mPRI mean +γ' m PRI mean , then the signal after combining the M channels is expressed as: Perform range Fourier transform and range pulse compression to obtain the range frequency domain-azimuth time domain signal, which is expressed as:

[0159]

[0160] The matching function of range pulse compression is: Using time scale transformation, the non-uniform time basis m+γ' m Transformed to the uniform time base m', the expression is: (f r +f c )(m+γ' m ) = f c m', where m' = 1, 2, ..., M', M' represents the number of effective points after the time scale transformation; γ' m represents the offset basis, 0≤γ' m <1; f r represents the distance frequency domain; t a Indicates the azimuth time; τ m represents the uniform azimuth time; γ m Indicates the azimuth time offset; PRI mean represents the average pulse repetition interval; A0 represents the signal amplitude after the distance pulse is compressed; R(t a ) represents the slant range history; A1 represents the signal amplitude in the range frequency domain-azimuth time domain; B represents the signal bandwidth; T a represents the aperture time; 2Υ+1 represents the fuzzy number; f dc Indicates the Doppler center frequency.

[0161] The distance frequency domain-azimuth time domain signal after the reconstruction and time scale transformation is:

[0162]

[0163] Also taking into account: Therefore, the distance frequency domain-azimuth time domain signal after time scale transformation is written as: Set the decoupling matched filter to: After decoupling, the SPECAN or RD algorithm is used to perform azimuth compression to obtain the final imaging result; where A2 represents the range frequency domain-azimuth time domain signal amplitude after time scale transformation.

[0164] Those skilled in the art know that, in addition to implementing the system, device and its various modules provided by the present invention in a purely computer-readable program code, it is entirely possible to implement the same program in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers and embedded microcontrollers by logically programming the method steps. Therefore, the system, device and its various modules provided by the present invention can be considered as a hardware component, and the modules included therein for implementing various programs can also be considered as structures within the hardware component; the modules for implementing various functions can also be considered as both software programs for implementing the method and structures within the hardware component.

[0165] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A synthetic aperture radar imaging method based on agile pulse repetition frequency, characterized in that: include: Step 1: Arrange and combine the channel signals in the order of receiving time; Step 2: Perform range pulse compression on the arranged and combined signals; Step 3: transform the echo signal after range pulse compression into range frequency domain; Step 4: Use time scale transformation to convert the permuted and combined signal into a uniformly sampled signal; Step 5: Perform range migration correction based on the uniformly sampled signal; Step 6: Perform azimuth compression to complete point target SAR imaging; Azimuth multi-channel SAR sets M evenly spaced receiving channels in azimuth, with a channel spacing of d. The radar platform moves at a uniform speed of v. Channel 1 is set as the reference channel, and the distance from channel m to the reference channel is recorded as d. m =(M-1)d, m=1,...,M; The Cartesian geometric coordinate system of the azimuth multi-channel SAR is established. The X-axis represents the direction of movement of the radar platform, the Z-axis represents the direction away from the earth, H represents the height of the radar platform, R0 represents the slant distance from the target P(x0,y0,0) to the radar platform at the initial time point, and R m (t a ) represents the instantaneous slant distance from target P to receiving channel m, t a represents the azimuth slow time variable, θ Cone represents the spatial cone angle, θ El represents the downward viewing angle, θ Azi represents the azimuth, and the three angles have the following relationship: sinθ Cone =cosθ Azi sinθ El The radar platform moves in a straight line within the preset time. Using the equivalent phase center principle, the slant range of the mth receiving channel is expressed as: in, x0 Indicates the coordinate of the target P on the X-axis at the initial time point; y0 Indicates the coordinate of the target P on the Y axis at the initial time point; The first channel transmits a linear frequency modulation signal, and all channels receive echo signals. The transmitted signal is expressed as: Among them, t is the distance time series, K r is the modulation frequency, f c is the center frequency of the transmitted signal; Then the received signal of the mth channel is: Where λ is the carrier wavelength; Tp is the pulse width; j is the imaginary unit; R(t a ) represents the slant range; c represents the speed of light; In the high-resolution wide-band SAR system, a signal reconstruction algorithm based on time scale transformation is used to restore the periodic non-uniform signal to a uniformly sampled signal, thereby realizing the reconstruction of the unambiguous Doppler spectrum of the target signal. Establish a non-uniform time signal model, the expression is: t a =t m +g m =mPRI mean +γ′ m PRI mean Then the signal after combining the M channels is expressed as: Perform range Fourier transform and range pulse compression to obtain the range frequency domain-azimuth time domain signal, which is expressed as: The matching function of range pulse compression is: Using time scale transformation, the non-uniform time basis m+γ' m Transformed to uniform time basis m', the expression is: (f r +f c )(m+γ' m )=f c ·m' Where m'=1,2,…,M', M' represents the number of effective points after time scale transformation; γ' m represents the offset basis, 0≤γ' m <1;f r represents the distance frequency domain; t a Indicates the azimuth time; τ m represents the uniform azimuth time; γ m Indicates the azimuth time offset; PRI mean represents the average pulse repetition interval; A0 represents the signal amplitude after the distance pulse is compressed; R(t a ) represents the slant range history; A1 represents the signal amplitude in the range frequency domain-azimuth time domain; B represents the signal bandwidth; T a represents the aperture time; 2γ+1 represents the fuzzy number; f dc Indicates the Doppler center frequency.

2. The synthetic aperture radar imaging method based on agile pulse repetition frequency according to claim 1, characterized in that: The distance frequency domain-azimuth time domain signal after the reconstruction and time scale transformation is: Also taking into account: Therefore, the distance frequency domain-azimuth time domain signal after time scale transformation is written as: Set the decoupling matched filter to: After decoupling, the SPECAN or RD algorithm is used to perform azimuth compression to obtain the final imaging result; Among them, A2 represents the range frequency domain-azimuth time domain signal amplitude after time scale transformation.

3. A synthetic aperture radar imaging system based on agile pulse repetition frequency, characterized in that: include: Module M1: Arrange and combine the channel signals in the order of receiving time; Module M2: Perform range pulse compression on the arranged and combined signals; Module M3: transform the echo signal after range pulse compression to the range frequency domain; Module M4: Use time scale transformation to convert the permuted and combined signals into uniformly sampled signals; Module M5: Perform range migration correction based on uniformly sampled signals; Module M6: Perform azimuth compression to complete point target SAR imaging; Azimuth multi-channel SAR sets M evenly spaced receiving channels in azimuth, with a channel spacing of d. The radar platform moves at a uniform speed of v. Channel 1 is set as the reference channel, and the distance from channel m to the reference channel is recorded as d. m =(M-1)d, m=1,...,M; The Cartesian geometric coordinate system of the azimuth multi-channel SAR is established. The X-axis represents the direction of movement of the radar platform, the Z-axis represents the direction away from the earth, H represents the height of the radar platform, R0 represents the slant distance from the target P(x0,y0,0) to the radar platform at the initial time point, and R m (t a ) represents the instantaneous slant distance from target P to receiving channel m, t a represents the azimuth slow time variable, θ Cone represents the spatial cone angle, θ El represents the downward viewing angle, θ Azi represents the azimuth, and the three angles have the following relationship: sinθ Cone =cosθ Azi sinθ El The radar platform moves in a straight line within the preset time. Using the equivalent phase center principle, the slant range of the mth receiving channel is expressed as: in, x0 Indicates the coordinate of the target P on the X-axis at the initial time point; y0 Indicates the coordinate of the target P on the Y axis at the initial time point; The first channel transmits a linear frequency modulation signal, and all channels receive echo signals. The transmitted signal is expressed as: Among them, t is the distance time series, K r is the modulation frequency, f c is the center frequency of the transmitted signal; Then the received signal of the mth channel is: Where λ is the carrier wavelength; T p represents the pulse width; j represents the imaginary unit; R(t a ) represents the slant range; c represents the speed of light; In the high-resolution wide-band SAR system, a signal reconstruction algorithm based on time scale transformation is used to restore the periodic non-uniform signal to a uniformly sampled signal, thereby realizing the reconstruction of the unambiguous Doppler spectrum of the target signal. Establish a non-uniform time signal model, the expression is: t a =t m +g m =mPRI mean +γ′ m PRI mean Then the signal after combining the M channels is expressed as: Perform range Fourier transform and range pulse compression to obtain the range frequency domain-azimuth time domain signal, which is expressed as: The matching function of range pulse compression is: Using time scale transformation, the non-uniform time basis m+γ' m Transformed to uniform time basis m', the expression is: (f r +f c )(m+γ' m )=f c ·m' Where m'=1,2,…,M', M' represents the number of effective points after time scale transformation; γ' m represents the offset basis, 0≤γ' m <1;f r represents the distance frequency domain; t a Indicates the azimuth time; τ m represents the uniform azimuth time; γ m Indicates the azimuth time offset; PRI mean represents the average pulse repetition interval; A0 represents the signal amplitude after the distance pulse is compressed; R(t a ) represents the slant range history; A1 represents the signal amplitude in the range frequency domain-azimuth time domain; B represents the signal bandwidth; T a represents the aperture time; 2γ+1 represents the fuzzy number; f dc Indicates the Doppler center frequency.

4. The synthetic aperture radar imaging system based on agile pulse repetition frequency according to claim 3, characterized in that: The distance frequency domain-azimuth time domain signal after the reconstruction and time scale transformation is: Also taking into account: Therefore, the distance frequency domain-azimuth time domain signal after time scale transformation is written as: Set the decoupling matched filter to: After decoupling, the SPECAN or RD algorithm is used to perform azimuth compression to obtain the final imaging result; Among them, A2 represents the range frequency domain-azimuth time domain signal amplitude after time scale transformation.

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