CN113514830B - Synthetic aperture radar imaging method and system - Google Patents

Synthetic aperture radar imaging method and system Download PDF

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CN113514830B
CN113514830B CN202110785469.0A CN202110785469A CN113514830B CN 113514830 B CN113514830 B CN 113514830B CN 202110785469 A CN202110785469 A CN 202110785469A CN 113514830 B CN113514830 B CN 113514830B
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黄鹤
黄鹏辉
刘兴钊
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Shanghai Jiaotong University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
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    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques

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Abstract

The invention provides a synthetic aperture radar imaging method and a synthetic aperture radar imaging system, which comprise the following steps: step S1: determining the height H, velocity v and range modulation frequency K of the radarrAnd the emitted agility PRF waveform, and solving the instantaneous slope distance of the ground scattering point; step S2: establishing an echo signal model of the radar according to the solved instantaneous slope distance and the transmitted agile pulse repetition frequency signal; step S3: performing range pulse compression on radar signals; step S4: carrying out generalized scale transformation operation on the distance pulse compressed signal, and restoring the non-uniform signal into a uniform sampling grid signal; step S5: and performing range migration correction and azimuth compression on the recovered signals to obtain an imaging result. The invention considers the influence of range envelope migration, can accurately recover non-uniform sampling signals and perform SAR imaging, and has higher signal-to-noise ratio of the output of the method.

Description

Synthetic aperture radar imaging method and system
Technical Field
The invention relates to the field of synthetic aperture radar imaging, in particular to a synthetic aperture radar imaging method and a synthetic aperture radar imaging system, and especially relates to a synthetic aperture radar imaging method and a synthetic aperture radar imaging system based on a generalized scale transformation and in a agile pulse repetition frequency mode.
Background
The pulse repetition interval of conventional radar imaging systems is seen to be fixed, resulting in fixed range blind zones, causing discontinuities in the observation region. The fixed distance blind area can be effectively disturbed by the agile pulse repetition frequency sampling technology, and the method is an effective means for solving the fixed distance blind area. However, the varying pulse repetition interval causes non-uniform sampling signals, and if the radar imaging processing is directly performed, a doppler fuzzy phenomenon exists, so that the radar imaging quality is reduced. Therefore, before the radar data sampled by the agile pulse repetition frequency is subjected to the traditional radar imaging processing, data recovery processing is required.
In the chinese patent application publication CN112834992A, a signal processing method, device and storage medium for a pulse doppler radar are disclosed, the method includes cyclically transmitting a pulse group, where the pulse group includes a plurality of transmission pulses with different frequency codes; receiving echo signals returned by the response pulse group; sequentially performing matched filtering on echo signals by using a matched filter group, and separating fuzzy areas with different distances; correcting distance walking of each distance fuzzy area by using a Keystone transformation method; traversing Doppler fuzzy numbers in a preset range to compensate the Doppler fuzzy numbers; and determining the corresponding Doppler fuzzy number according to the peak value of the coherent accumulation result after the Doppler fuzzy number compensation, and completing Doppler ambiguity resolution.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a synthetic aperture radar imaging method and a synthetic aperture radar imaging system.
The synthetic aperture radar imaging method provided by the invention comprises the following steps:
step S1: determining the height H, velocity v and range modulation frequency K of the radarrAnd the emitted agility PRF waveform, and solving the instantaneous slope distance of the ground scattering point;
step S2: establishing an echo signal model of the radar according to the solved instantaneous slope distance and the transmitted agile pulse repetition frequency signal;
step S3: performing range pulse compression on radar signals;
step S4: carrying out generalized scale transformation operation on the distance pulse compressed signal, and restoring the non-uniform signal into a uniform sampling grid signal;
step S5: and performing range migration correction on the recovered signal by using a range migration correction function, and performing azimuth compression by using an RD algorithm to obtain an imaging result.
Preferably, the instantaneous slope distance expression in step S1 is specifically:
Figure BDA0003158568600000021
wherein v, H,
Figure BDA0003158568600000022
θ0Respectively representing radar speed, radar height, beam center downward viewing angle and beam center azimuth angle,
Figure BDA0003158568600000023
representing the closest slope of the target from the flight path, tmSlow time, indicating non-uniform azimuth, is a uniform time baseIn combination with the offset, i.e.:
tm＝τm+γm=mPRImean+γ'mPRImean
wherein M =1,2, …, M; m represents a uniform time base, M is the number of azimuth pulses, and is not less than 0 and gamma'm< 1 denotes the base of the offset of the mth pulse, τmAzimuthal slow time, γ, of the m-th pulse representing uniform samplingmRepresenting the random offset time, PRI, of the m-th pulsemeanRepresenting the average pulse repetition interval.
Preferably, the echo signal model of the radar in step S2 is specifically:
Figure BDA0003158568600000024
in the formula, s0(t,tm) Representing the received echo signal after down-modulation, where t, tmRespectively representing distance time and azimuth time, A0、fc、c、KrB respectively represents signal amplitude, central carrier frequency, light speed, signal modulation frequency and signal bandwidth, rect () represents a rectangular window function, j represents an imaginary unit, T represents distance fast time, T represents distance fast timeaRepresents the accumulation time, frRepresenting the distance frequency variation.
Preferably, the matching function of the distance compression in step S3 is:
Figure BDA0003158568600000025
in the formula, H1(fr,tm) A matching function representing distance compression.
Preferably, the generalized scale transformation operation in step S4 is specifically:
S2(fr，t′m(i))＝∑j∈zS1(fr，tm(j))φ(fcf′m(i)/(fr+fc)-tm(j))
in the formula, S2(fr，t′m(i) Denotes a generalized scaled signal, where t'm(i) Denotes the ith time of the azimuth after the generalized scale change, phi (-) denotes a one-dimensional Gaussian kernel function, Z denotes the action range of the kernel function, t'm＝m′PRImean，m′＝1，2，...，Mnew，MnewRepresenting the number of azimuth points, t 'after generalized scale transformation'm() I represents the azimuth uniform time sequence after the generalized scale change, i represents the sequence number of the azimuth uniform time after the generalized scale change, tm(j) Representing the original j-th azimuth time.
The invention provides a synthetic aperture radar imaging system, which comprises the following modules:
module M1: determining the height H, velocity v and range modulation frequency K of the radarrAnd the emitted agility PRF waveform, and solving the instantaneous slope distance of the ground scattering point;
module M2: establishing an echo signal model of the radar according to the solved instantaneous slope distance and the transmitted agile pulse repetition frequency signal;
module M3: performing range pulse compression on radar signals;
module M4: carrying out generalized scale transformation operation on the distance pulse compressed signal, and restoring the non-uniform signal into a uniform sampling grid signal;
module M5: and performing range migration correction on the recovered signal by using a range migration correction function, and performing azimuth compression by using an RD algorithm to obtain an imaging result.
Preferably, the instantaneous slope distance expression in the module M1 is specifically:
Figure BDA0003158568600000031
wherein v, H,
Figure BDA0003158568600000032
θ0Respectively indicating radar speed and radarAltitude, beam center down-view angle, beam center azimuth angle,
Figure BDA0003158568600000033
representing the closest slope of the target from the flight path, tmSlow time, which represents non-uniform azimuth, is a combination of a uniform time base and an offset, i.e.:
tm＝τm+γm＝mPRImean+γ′mPRImean
wherein M is 1,2, …, M; m represents a uniform time base, M is the number of azimuth pulses, and is not less than 0 and gamma'm< 1 denotes the base of the offset of the mth pulse, τmAzimuthal slow time, γ, of the m-th pulse representing uniform samplingmRepresenting the random offset time, PRI, of the m-th pulsemeanRepresenting the average pulse repetition interval.
Preferably, the echo signal model of the radar in the module M2 is specifically:
Figure BDA0003158568600000041
in the formula, s0(t，tm) Representing the received echo signal after down-modulation, where t, tmRespectively representing distance time and azimuth time, A0、fc、c、KrB respectively represents signal amplitude, central carrier frequency, light speed, signal modulation frequency and signal bandwidth, rect () represents a rectangular window function, j represents an imaginary unit, T represents distance fast time, T represents distance fast timeaRepresents the accumulation time, frRepresenting the distance frequency variation.
Preferably, the matching function of the distance compression in the module M3 is:
Figure BDA0003158568600000042
in the formula, H1(fr，tm) A matching function representing distance compression.
Preferably, the generalized scale transformation operation in the module M4 is specifically:
S2(fr，t′m(i))＝∑j∈zS1(fr，tm(j))φ(fcf′m(i)/(fr+fc)-tm(j))
in the formula, S2(fr，t′m(i) Denotes a generalized scaled signal, where t'm(i) Denotes the ith time of the azimuth after the generalized scale change, phi (-) denotes a one-dimensional Gaussian kernel function, Z denotes the action range of the kernel function, t'm＝m′PRImean，m′＝1，2，...，Mnew，MnewRepresenting the number of azimuth points, t 'after generalized scale transformation'm() I represents the azimuth uniform time sequence after the generalized scale change, i represents the sequence number of the azimuth uniform time after the generalized scale change, tm(j) Representing the original j-th azimuth time.
Compared with the prior art, the invention has the following beneficial effects:
1. the method considers the influence of range envelope migration.
2. The invention can accurately recover the non-uniform sampling signal and perform SAR imaging.
3. The output of the inventive method has a higher signal-to-noise ratio.
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Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
FIG. 1 is a flow chart of a synthetic aperture radar imaging method according to an embodiment of the present invention;
FIG. 2 is a graph of imaging results without performing a non-uniform recovery algorithm in an embodiment of the present invention;
FIG. 3 is a one-dimensional slice of FIG. 2;
FIG. 4 is a diagram of SAR imaging results after non-uniform signal recovery using a non-uniform fast Fourier transform algorithm;
FIG. 5 is a one-dimensional slice of FIG. 4;
FIG. 6 is a SAR imaging result graph after non-uniform signal recovery by cubic spline interpolation algorithm;
FIG. 7 is a one-dimensional slice of FIG. 6;
FIG. 8 is a diagram of SAR imaging results after non-uniform signal recovery using an optimal linear interpolation algorithm;
FIG. 9 is a one-dimensional slice of FIG. 8;
FIG. 10 is a graph of SAR imaging results after processing by the method of the present invention;
fig. 11 is a one-dimensional slice of fig. 10.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that it would be obvious to those skilled in the art that various changes and modifications can be made without departing from the spirit of the invention. All falling within the scope of the present invention.
The embodiment provides a synthetic aperture radar imaging method, which comprises the following steps:
step S1: determining the height H, velocity v and range modulation frequency K of the radarrAnd the emitted agile PRF waveform, and solving the instantaneous slope distance of the ground scattering point.
The instantaneous slope distance expression is specifically as follows:
Figure BDA0003158568600000051
in the formula, v, H,
Figure BDA0003158568600000052
θ0Respectively representing radar speed, radar height, beam center downward viewing angle and beam center azimuth angle,
Figure BDA0003158568600000053
representing the closest slope of the target from the flight path, tmSlow time, which represents non-uniform azimuth, is a combination of a uniform time base and an offset, i.e.:
tm＝τm+γm＝mPRImean+γmPRImean
wherein M is 1,2, …, M; m represents a uniform time base, M is the number of azimuth pulses, and is not less than 0 and gamma'm< 1 denotes the base of the offset of the mth pulse, τmAzimuthal slow time, γ, of the m-th pulse representing uniform samplingmRepresenting the random offset time, PRI, of the m-th pulsemeanRepresenting the average pulse repetition interval.
Step S2: and establishing an echo signal model of the radar according to the solved instantaneous slope distance and the transmitted agile pulse repetition frequency signal.
The echo signal model of the radar specifically comprises:
Figure BDA0003158568600000061
in the formula, s0(t，tm) Representing the received echo signal after down-modulation, where t, tmRespectively representing distance time and azimuth time, A0、fc、c、KrB respectively represents signal amplitude, central carrier frequency, light speed, signal modulation frequency and signal bandwidth, rect () represents a rectangular window function, j represents an imaginary unit, T represents distance fast time, T represents distance fast timeaRepresents the accumulation time, frRepresenting the distance frequency variation.
Step S3: and performing range pulse compression on the radar signal.
The matching function for distance compression is:
Figure BDA0003158568600000062
in the formula, H1(fr，tm) A matching function representing distance compression.
Step S4: and carrying out generalized scale transformation operation on the distance pulse compressed signal, and restoring the non-uniform signal into a uniform sampling grid signal.
The generalized scale transformation operation is specifically as follows:
S2(fr，t′m(i))＝∑j∈zS1(fr，tm(j))φ(fct′m(i)/(fr+fc)-tm(j)) (5)
in the formula, S2(fr，t′m(i) Denotes a generalized scaled signal, where t'm(i) Denotes the ith time of the azimuth after the generalized scale change, phi (-) denotes a one-dimensional Gaussian kernel function, Z denotes the action range of the kernel function, t'm＝m′PRImean，m′＝1，2，...，Mnew，MnewRepresenting the number of azimuth points, t 'after generalized scale transformation'm() I represents the azimuth uniform time sequence after the generalized scale change, i represents the sequence number of the azimuth uniform time after the generalized scale change, tm(j) Representing the original j-th azimuth time.
Step S5: and performing range migration correction and azimuth compression on the recovered signals to obtain an imaging result.
The effects of the present invention can be further illustrated by the following simulations:
(1) simulation conditions
Simulation experiment platform parameters are given in table 1, and the various implementation steps of this example were performed on the MATLAB2018B simulation platform.
TABLE 1 simulation System parameters
Figure BDA0003158568600000063
Figure BDA0003158568600000071
(2) Emulated content
Firstly, the influence of each non-uniform signal reconstruction algorithm on multi-point target imaging in a periodic slow-varying PRF mode is given. The simulation results are shown below. Figure 2 shows the imaging results without performing the non-uniform recovery algorithm. Fig. 3 is a slice view of fig. 2, from which it can be seen that a SAR image without signal recovery is subject to doppler blurring effects due to non-uniform sampling. Fig. 4, 6, and 8 are SAR imaging results after non-uniform signal recovery by using a non-uniform fast fourier transform algorithm, a cubic spline interpolation algorithm, and an optimal linear interpolation algorithm, respectively, and fig. 5, 7, and 9 are one-dimensional slice images corresponding to fig. 4, 6, and 8, respectively. Fig. 10 and fig. 11 are the SAR imaging result and its one-dimensional slice after the processing by the method of the present invention, respectively. As can be seen from the figure, the method has the highest output signal-to-noise ratio, and the effectiveness of the algorithm is verified.
Those skilled in the art will appreciate that, in addition to implementing the system and its various devices, modules, units provided by the present invention as pure computer readable program code, the system and its various devices, modules, units provided by the present invention can be fully implemented by logically programming method steps in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Therefore, the system and various devices, modules and units thereof provided by the invention can be regarded as a hardware component, and the devices, modules and units included in the system for realizing various functions can also be regarded as structures in the hardware component; means, modules, units for performing the various functions may also be regarded as structures within both software modules and hardware components for performing the method.
The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.

Claims (8)

1. A synthetic aperture radar imaging method, comprising the steps of:
step S1: determining the height H, velocity v and range modulation frequency K of the radarrAnd the emitted agility PRF waveform, and solving the instantaneous slope distance of the ground scattering point;
step S2: establishing an echo signal model of the radar according to the solved instantaneous slope distance and the transmitted agile pulse repetition frequency signal;
step S3: performing range pulse compression on radar signals;
step S4: carrying out generalized scale transformation operation on the distance pulse compressed signal, and restoring the non-uniform signal into a uniform sampling grid signal;
step S5: performing range migration correction on the recovered signal by using a range migration correction function, and performing azimuth compression by using an RD algorithm to obtain an imaging result;
the generalized scale transformation operation in step S4 specifically includes:
S2(fr,t′m(i))＝∑j∈zS1(fr,tm(j))φ(fct′m(i)/(fr+fc)-tm(j))
in the formula, S2(fr,t′m(i) Denotes a generalized scaled signal, where t'm(i) Denotes the ith time of the azimuth after the generalized scale change, phi (-) denotes a one-dimensional Gaussian kernel function, Z denotes the action range of the kernel function, t'm＝m′PRImean,m′＝1,2,...,Mnew，MnewRepresenting the number of azimuth points, t 'after generalized scale transformation'm() I represents the azimuth uniform time sequence after the generalized scale change, i represents the sequence number of the azimuth uniform time after the generalized scale change, tm(j) Representing the original j-th azimuth time.
2. The synthetic aperture radar imaging method of claim 1, wherein: the instantaneous slope distance expression in step S1 is specifically:
Figure FDA0003497665670000011
wherein v, H,
Figure FDA0003497665670000012
θ0Respectively representing radar speed, radar height, beam center downward viewing angle and beam center azimuth angle,
Figure FDA0003497665670000013
representing the closest slope of the target from the flight path, tmSlow time, which represents non-uniform azimuth, is a combination of a uniform time base and an offset, i.e.:
tm＝τm+γm＝mPRImean+γ′mPRImean
wherein M is 1,2, …, M; m represents a uniform time base, M is the number of azimuth pulses, and is not less than 0 and gamma'm< 1 denotes the base of the offset of the mth pulse, τmAzimuthal slow time, γ, of the m-th pulse representing uniform samplingmRepresenting the random offset time, PRI, of the m-th pulsemeanRepresenting the average pulse repetition interval.
3. The synthetic aperture radar imaging method of claim 1, wherein: the echo signal model of the radar in step S2 is specifically:
Figure FDA0003497665670000021
in the formula, s0(t,tm) Representing the received echo signal after down-modulation, where t, tmRespectively representing distance time and azimuth time, A0、fc、c、KrB respectively represents signal amplitude, central carrier frequency, light speed, signal modulation frequency and signal bandwidth, rect () represents a rectangular window function, j represents an imaginary unit, T represents distance fast time, T represents distance fast timeaRepresents the accumulation time, frRepresenting the distance frequency variation.
4. The synthetic aperture radar imaging method of claim 1, wherein: the matching function of the distance compression in step S3 is:
Figure FDA0003497665670000022
in the formula, H1(fr,tm) A matching function representing distance compression.
5. A synthetic aperture radar imaging system, comprising the following modules:
module M1: determining the height H, velocity v and range modulation frequency K of the radarrAnd the emitted agility PRF waveform, and solving the instantaneous slope distance of the ground scattering point;
module M2: establishing an echo signal model of the radar according to the solved instantaneous slope distance and the transmitted agile pulse repetition frequency signal;
module M3: performing range pulse compression on radar signals;
module M4: carrying out generalized scale transformation operation on the distance pulse compressed signal, and restoring the non-uniform signal into a uniform sampling grid signal;
module M5: performing range migration correction on the recovered signal by using a range migration correction function, and performing azimuth compression by using an RD algorithm to obtain an imaging result;
the generalized scale transformation operation in the module M4 is specifically:
S2(fr,t′m(i))＝∑j∈zS1(fr,tm(j))φ(fct′m(i)/(fr+fc)-tm(j))
in the formula, S2(fr,t′m(i) Denotes a generalized scaled signal, where t'm(i) Shows the ith time of the azimuth after the generalized scale change, phi (-) tableIs a one-dimensional Gaussian kernel function, Z is the range of action of the kernel function, t'm＝m′PRImean,m′＝1,2,...,Mnew，MnewRepresenting the number of azimuth points, t 'after generalized scale transformation'm() I represents the azimuth uniform time sequence after the generalized scale change, i represents the sequence number of the azimuth uniform time after the generalized scale change, tm(j) Representing the original j-th azimuth time.
6. The synthetic aperture radar imaging system of claim 5, wherein: the instantaneous slope distance expression in the module M1 is specifically:
Figure FDA0003497665670000031
wherein v, H,
Figure FDA0003497665670000032
θ0Respectively representing radar speed, radar height, beam center downward viewing angle and beam center azimuth angle,
Figure FDA0003497665670000033
representing the closest slope of the target from the flight path, tmSlow time, which represents non-uniform azimuth, is a combination of a uniform time base and an offset, i.e.:
tm＝τm+γm＝mPRImean+γ′mPRImean
wherein M is 1,2, …, M; m represents a uniform time base, M is the number of azimuth pulses, and is not less than 0 and gamma'm< 1 denotes the base of the offset of the mth pulse, τmAzimuthal slow time, γ, of the m-th pulse representing uniform samplingmRepresenting the random offset time, PRI, of the m-th pulsemeanIndicating the average pulse repetition interval.
7. A synthetic aperture radar imaging system according to claim 5, wherein: the echo signal model of the radar in the module M2 is specifically:
Figure FDA0003497665670000034
in the formula, s0(t,tm) Representing the received echo signal after down-modulation, where t, tmRespectively representing distance time and azimuth time, A0、fc、c、KrB respectively represents signal amplitude, central carrier frequency, light speed, signal modulation frequency and signal bandwidth, rect () represents a rectangular window function, j represents an imaginary unit, T represents distance fast time, T represents distance fast timeaRepresents the accumulation time, frRepresenting the distance frequency variation.
8. The synthetic aperture radar imaging system of claim 5, wherein: the matching function for distance compression in the module M3 is:
Figure FDA0003497665670000035
in the formula, H1(fr,tm) A matching function representing distance compression.
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