CN113203998A - ISAR translation compensation and imaging method, system, medium and device - Google Patents

ISAR translation compensation and imaging method, system, medium and device Download PDF

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CN113203998A
CN113203998A CN202110442921.3A CN202110442921A CN113203998A CN 113203998 A CN113203998 A CN 113203998A CN 202110442921 A CN202110442921 A CN 202110442921A CN 113203998 A CN113203998 A CN 113203998A
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isar
compensation
doppler
imaging
distance
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CN113203998B (en
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占木杨
黄鹏辉
刘兴钊
王波兰
王萌
陆晴
林欣
孙永岩
万向成
刘艳阳
陈国忠
陈筠力
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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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/418—Theoretical aspects
    • 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
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • 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
    • G01S13/9021—SAR image post-processing techniques

Abstract

The invention provides an ISAR (inverse synthetic aperture radar) translation compensation and imaging method, a system, a medium and equipment, which comprise the following steps: step 1: distance compression and lower frequency modulation processing are carried out on radar echoes, and the radar echoes are converted into baseband signals; step 2: performing linear distance walk correction and non-uniform signal reconstruction on the baseband signals by adopting generalized keystone transformation; and step 3: constructing a Doppler fuzzy compensation function, and compensating the Doppler fuzzy term; and 4, step 4: constructing an acceleration phase function to compensate the residual distance bending and the quadratic Doppler phase; and 5: and finishing the final ISAR imaging result by utilizing two-dimensional Fourier transform. The invention can process translation compensation and ISAR imaging under random PRF, thereby obtaining high-resolution ISAR images, and the proposed algorithm does not involve any nonlinear operation, and can obtain near-optimal performance under the environment of low signal-to-noise ratio.

Description

ISAR translation compensation and imaging method, system, medium and device
Technical Field
The invention relates to the technical field of radar signal processing, in particular to an ISAR (inverse synthetic aperture radar) translation compensation and imaging method, system, medium and equipment. And more particularly, to an ISAR translational compensation and imaging method based on random pulse repetition frequency.
Background
Compared with a Synthetic Aperture Radar (SAR) system which has the main task of acquiring two-dimensional high-resolution imaging of a static scene, the Inverse Synthetic Aperture Radar (ISAR) system can complete two-dimensional high-resolution imaging of a non-cooperative target so as to acquire detailed information of an interested moving target, including motion information, shape, structure, size and the like, and is one of important means for effective target observation and national defense construction.
The relative motion between the target and the radar can be divided into a translation part and a rotation part, wherein the translation part does not contribute to imaging and needs to be accurately compensated; the latter is the basis for imaging and also needs to be properly processed to obtain well focused ISAR images. Therefore, in order to acquire a two-dimensional high-resolution image of a non-cooperative target, ISAR (inverse synthetic aperture radar) translational compensation is firstly required to be completed, and the ISAR translational compensation comprises two steps of envelope alignment and initial phase correction, and envelope walking and phase walking caused by translational motion between the target and a radar are respectively solved. For envelope alignment, a related scholar has proposed a plurality of schemes, and typical methods include an envelope correlation method, a minimum entropy method, a global envelope alignment method and the like; these methods have high performance at high signal-to-noise ratios (SNR), but are susceptible to noise and envelope hopping. For initial phase correction, typical methods include phase gradient self-focusing, eigen-point method, etc.; the algorithm can effectively remove phase errors caused by the translation part, and also has higher requirement on SNR. In order to improve stability, methods of joint envelope alignment and initial phase correction are proposed, such as a full-dimensional search scheme based on a particle swarm algorithm, and the like. This class is robust to noise but has a high computational complexity.
Although the conventional ISAR technology based on the uniform Pulse Repetition Frequency (PRF) is relatively mature, with the development of the electromagnetic interference technology, the requirements of the actual system for interference resistance, resolution and the like are further improved. The random/agile PRF signal is used as a transmitting signal, which is beneficial to solving the problem of distance ambiguity, improving the azimuth resolution, enhancing the anti-interference performance and the like. However, in the PRF-agile radar system, for non-cooperative target ISAR imaging, the target may be defocused seriously by imaging using the conventional translation compensation algorithm and imaging algorithm. For the problem, the traditional non-uniform sampling theory can perform signal reconstruction processing along the slow time dimension at each distance frequency point by using a traditional non-uniform signal reconstruction method, but the method needs to perform non-uniform signal reconstruction at each distance frequency point, so the calculation complexity is relatively high. In addition, if the target is a fast target, doppler blurring of the target occurs, further increasing the difficulty of signal processing. Therefore, under the condition that the target signal sampling is not uniform, the ISAR imaging of the target with Doppler blurring and low SNR is a key problem with relatively small computational complexity.
Disclosure of Invention
In view of the shortcomings in the prior art, it is an object of the present invention to provide an ISAR translational compensation and imaging method, system, medium, and device.
The ISAR translation compensation and imaging method provided by the invention comprises the following steps:
step 1: distance compression and lower frequency modulation processing are carried out on radar echoes, and the radar echoes are converted into baseband signals;
step 2: performing linear distance walk correction and non-uniform signal reconstruction on the baseband signals by adopting generalized keystone transformation;
and step 3: constructing a Doppler fuzzy compensation function, and compensating the Doppler fuzzy term;
and 4, step 4: constructing an acceleration phase function to compensate the residual distance bending and the quadratic Doppler phase;
and 5: and finishing the final ISAR imaging result by utilizing two-dimensional Fourier transform.
Preferably, the expression of the generalized keystone transformation in step 2 is:
(fr+fc)(m+rm)＝fcm′
in the formula: f. ofr、fc、m、rmAnd m' is distance frequency variable, carrier frequency, uniform dispersion slow time indication, rmA random slow time indication and a new uniform slow time indication.
Preferably, the doppler blur compensation function in step 3 is:
Figure BDA0003035651500000021
in the formula: mambRepresents a Doppler ambiguity number; j is an imaginary unit.
Preferably, the acceleration phase compensation function in step 4 is:
Figure BDA0003035651500000022
wherein the content of the first and second substances,
Figure BDA0003035651500000023
represents the searched acceleration; c is the speed of light; t is the pulse repetition period of the geometric mean.
According to the ISAR translation compensation and imaging system provided by the invention, the ISAR translation compensation and imaging system comprises:
module M1: distance compression and lower frequency modulation processing are carried out on radar echoes, and the radar echoes are converted into baseband signals;
module M2: performing linear distance walk correction and non-uniform signal reconstruction on the baseband signals by adopting generalized keystone transformation;
module M3: constructing a Doppler fuzzy compensation function, and compensating the Doppler fuzzy term;
module M4: constructing an acceleration phase function to compensate the residual distance bending and the quadratic Doppler phase;
module M5: and finishing the final ISAR imaging result by utilizing two-dimensional Fourier transform.
Preferably, the expression of the generalized keystone transformation in the module M2 is:
(fr+fc)(m+rm)＝fcm′
in the formula: f. ofr、fc、m、rmAnd m' is distance frequency variable, carrier frequency, uniform dispersion slow time indication, rmA random slow time indication and a new uniform slow time indication.
Preferably, the doppler blur compensation function in the module M3 is:
Figure BDA0003035651500000031
in the formula: mambRepresents a Doppler ambiguity number; j is an imaginary unit.
Preferably, the acceleration phase compensation function in the module M4 is:
Figure BDA0003035651500000032
wherein the content of the first and second substances,
Figure BDA0003035651500000033
represents the searched acceleration; c is the speed of light; t is the pulse repetition period of the geometric mean.
According to the present invention, a computer-readable storage medium is provided, in which a computer program is stored, which, when being executed by a processor, carries out the steps of the method as described above.
According to the invention, the ISAR translation compensation and imaging device comprises: a controller;
the controller comprises the computer readable storage medium storing a computer program which, when executed by a processor, performs the steps of the ISAR translational compensation and imaging method; or, the controller comprises the ISAR translation compensation and imaging system.
Compared with the prior art, the invention has the following beneficial effects:
(1) the invention can process translation compensation and ISAR imaging under random PRF, thereby obtaining high-resolution ISAR images;
(2) compared with the traditional non-uniform signal reconstruction algorithm, the calculation amount of the algorithm is small;
(3) the GKT and the matched filtering processing of the algorithm belong to linear transformation and do not involve any nonlinear operation, so that near-optimal performance can be obtained in a low signal-to-noise ratio (SNR) environment.
Drawings
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 an ISAR translational compensation and imaging method at a random Pulse Repetition Frequency (PRF) according to the present invention;
FIG. 2 is a diagram of an ISAR observation geometric model;
FIG. 3 is a diagram of a simulated model of scattering points of an aircraft;
FIG. 4 is a diagram of imaging results of a conventional ISAR translational compensation method;
fig. 5 is a diagram of an imaging result of the proposed ISAR translation compensation method.
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.
Example (b):
the invention provides an ISAR (inverse synthetic aperture radar) translation compensation and imaging method under random pulse repetition frequency, as shown in figure 1, which specifically comprises the following steps:
the method comprises the following steps: ISAR echo modeling under random PRF.
For a radar system with random PRF sampling, the non-uniform sampling slow time is expressed as:
tm＝(m+rm)T…………(1)
in the formula, tm＝mT+rmT represents a slow time variable, m is a discrete slow time indicator, rmRepresenting a random slow time indication, T is the pulse repetition period of the geometric mean.
According to the ISAR observation model shown in FIG. 2, any scattering point P (x) on the targetk,yk) The instantaneous slope to the radar is:
Figure BDA0003035651500000041
in the formula (I), the compound is shown in the specification,
Figure BDA0003035651500000042
representing the slant of the translation part, R0、vrAnd arRespectively, initial slope distance, radial speed and radial acceleration; r iskAnd theta0Respectively representing the polar diameter and the polar angle of the scattering point;ω represents the rotational angular velocity. Considering that the ISAR rotation angle of the target is relatively small during the coherent integration time, equation (2) can be approximated according to a first-order Taylor expansion
Figure BDA0003035651500000051
After distance compression, the distance frequency domain signal corresponding to the kth scattering point of the target is as follows:
Figure BDA0003035651500000052
in the formula (f)rRepresenting a frequency variable, fcIs the spur frequency and B is the signal bandwidth.
Step two: the proposed ISAR translation compensation and imaging scheme based on generalized KT and matched filtering.
(1) For Doppler blurred echo signals, and formula (1) is brought into formula (4), which can be simplified as follows:
Figure BDA0003035651500000053
in the formula, v0Representing the base band velocity, MambIndicating the doppler ambiguity number and lambda the signal wavelength. Further simplifying the formula (5), we can obtain:
Figure BDA0003035651500000054
(2) utilizing Generalized KT (GKT) transformation to simultaneously complete azimuth non-uniform signal reconstruction and eliminate linear coupling between distance and azimuth, wherein the GKT is defined as the following form:
(fr+fc)(m+rm)＝fcm′…………(7)
in the formula, m' is a transformed uniform sampling slow time variable. By bringing formula (7) into formula (6), it is possible to obtain:
Figure BDA0003035651500000061
the generalized KT transformation operation can be realized by sinc interpolation, and can also be realized by adopting rapid algorithms such as cubic spline interpolation or scale transformation. It should be noted that this step may be performed simultaneously for linear distance ambulatory correction and for off-range unit correction.
(3) And constructing a Doppler fuzzy compensation term to eliminate the influence of Doppler fuzzy.
To eliminate r in formula (8)mThe influence caused by the method needs to estimate the Doppler fuzzy number; from the derivation result in equation (8), the following matched filter function is set, namely:
Figure BDA0003035651500000062
in the formula (I), the compound is shown in the specification,
Figure BDA0003035651500000063
representing the number of doppler ambiguities searched. Multiplying formula (8) by formula (9) when
Figure BDA0003035651500000064
Then, therefore, equation (8) becomes:
Figure BDA0003035651500000065
as can be seen, the Doppler ambiguity term is effectively removed.
(4) And constructing a phase compensation term and eliminating the phase term related to the translational acceleration.
From the results of equation (10), the following compensation function is constructed:
Figure BDA0003035651500000066
in the formula (I), the compound is shown in the specification,
Figure BDA0003035651500000067
is the searched radial acceleration. Multiplying formula (10) by formula (11) when
Figure BDA0003035651500000068
The result after compensation is:
Figure BDA0003035651500000069
it can be observed that the coupling of the range frequency domain and the azimuth time has been completely solved after the acceleration effect compensation in the translational component.
(5) Range-doppler (RD) imaging processing.
After compensating the acceleration influence in the translation component, firstly performing Inverse Fast Fourier Transform (IFFT) along the distance dimension to obtain:
Figure BDA0003035651500000071
in the formula, trIndicating the distance fast time, TpIs the signal pulse width. At the moment, the signals positioned in the same distance unit are completely corrected; then the whole imaging process can be completed by the azimuth FFT:
Figure BDA0003035651500000072
the whole imaging process can be summarized in the following form:
Figure BDA0003035651500000073
wherein, FFTm′And
Figure BDA0003035651500000074
respectively representing the fast Fourier transform along the azimuth time and the inverse fast Fourier transform along the distance frequency domain;
Figure BDA0003035651500000075
the GKT transformation of equation (7) is shown.
The effects of the present invention can be further illustrated by the following simulations:
(1) simulation conditions
The simulation experiment platform parameters are given in table 1, and the implementation steps of this example were performed on a MATLAB2016 simulation platform.
TABLE 1 simulation parameters Table
Parameter(s) Numerical value
Carrier frequency 10GHz
Mean value of pulse repetition frequency 571.4Hz
Distance bandwidth 200MHz
Distance sampling frequency 300MHz
Duration of pulse 40μs
Accumulation time 0.512s
Number of distance sampling points 256
Number of azimuth sampling points 256
(2) Emulated content
This section presents the results of the simulation process to verify the proposed algorithm. The rotation angular speed of the airplane target is 0.06rad/s, the translation speed is 25m/s, and the translation acceleration is 5m/s2SNR was set to 10dB and the scattering point model is shown in FIG. 3.
FIG. 3 is a simulated model of the scattering points of an aircraft target. FIG. 4(a) is a distance envelope after a distance pulse pressure; FIG. 4(b) is the result of RD imaging without translational compensation; FIG. 4(c) is a diagram illustrating the envelope alignment result of the conventional envelope correlation method; FIG. 4(d) is the result of RD imaging after translational compensation based on the envelope correlation method and the feature point;
FIG. 4(e) is the result of distance walk correction of conventional KT; fig. 4(f) is an imaging result based on a conventional RD algorithm; FIG. 5(a) is a distance envelope graph of GKT, and FIG. 5(b) is a search graph of search Doppler ambiguity number and search translational acceleration; fig. 5(c) is an RD imaging result of the proposed method.
Fig. 4(a) and (b) show the distance envelope and RD imaging results, respectively, without translational compensation, and a significant envelope walk phenomenon can be observed, in which case the RD imaging results are also almost completely defocused; FIG. 4(e) shows a conventional KT with envelope walk-corrected, where the envelope is mostly aligned but some migration is still present; and 4(f) is an imaging result based on a traditional RD imaging algorithm on the basis of traditional KT, at the moment, FT is directly adopted for the non-uniformly sampled echo signals, the scattering points of the target cannot be effectively focused, and only a rough outline of the band can be observed. FIG. 5 is the processing result of the proposed method, and it can be observed from FIG. 5(a) that the validity of the proposed GKT (the translational acceleration has been compensated), FIG. 5(b) is the curves of the searched acceleration and Doppler ambiguity number, the Doppler ambiguity number is 3 from the point of minimum entropy value, and the searched acceleration is 4.99m/s2(ii) a Drawing (A)And 5(c) solving the final imaging result after translational compensation by the proposed method, and observing an ISAR imaging result with good focusing.
In conclusion, the simulation experiment verifies the correctness, the effectiveness and the reliability of the method.
Those skilled in the art will appreciate that, in addition to implementing the systems, apparatus, and various modules thereof provided by the present invention in purely computer readable program code, the same procedures can be implemented entirely by logically programming method steps such that the systems, apparatus, and various modules thereof are provided in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Therefore, the system, the device and the modules thereof provided by the present invention can be considered as a hardware component, and the modules included in the system, the device and the modules thereof for implementing various programs can also be considered as structures in the hardware component; modules for performing various functions may also be considered to be both software programs for performing the methods and structures within hardware components.
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 (10)

1. An ISAR translation compensation and imaging method, comprising:
step 1: distance compression and lower frequency modulation processing are carried out on radar echoes, and the radar echoes are converted into baseband signals;
step 2: performing linear distance walk correction and non-uniform signal reconstruction on the baseband signals by adopting generalized keystone transformation;
and step 3: constructing a Doppler fuzzy compensation function, and compensating the Doppler fuzzy term;
and 4, step 4: constructing an acceleration phase function to compensate the residual distance bending and the quadratic Doppler phase;
and 5: and finishing the final ISAR imaging result by utilizing two-dimensional Fourier transform.
2. The ISAR translational compensation and imaging method according to claim 1, wherein the expression of the generalized keystone transform in step 2 is:
(fr+fc)(m+rm)＝fcm′
in the formula: f. ofr、fc、m、rmAnd m' is distance frequency variable, carrier frequency, uniform dispersion slow time indication, rmA random slow time indication and a new uniform slow time indication.
3. The ISAR translational compensation and imaging method of claim 2, wherein the doppler blur compensation function in step 3 is:
Figure FDA0003035651490000011
in the formula: mambRepresents a Doppler ambiguity number; j is an imaginary unit.
4. The ISAR translational compensation and imaging method according to claim 3, wherein the acceleration phase compensation function in step 4 is:
Figure FDA0003035651490000012
wherein the content of the first and second substances,
Figure FDA0003035651490000013
represents the searched acceleration; c is the speed of light; t is the pulse repetition period of the geometric mean.
5. An ISAR translational compensation and imaging system, comprising:
module M1: distance compression and lower frequency modulation processing are carried out on radar echoes, and the radar echoes are converted into baseband signals;
module M2: performing linear distance walk correction and non-uniform signal reconstruction on the baseband signals by adopting generalized keystone transformation;
module M3: constructing a Doppler fuzzy compensation function, and compensating the Doppler fuzzy term;
module M4: constructing an acceleration phase function to compensate the residual distance bending and the quadratic Doppler phase;
module M5: and finishing the final ISAR imaging result by utilizing two-dimensional Fourier transform.
6. The ISAR translational compensation and imaging system of claim 5, wherein the expression of the generalized keystone transform in module M2 is:
(fr+fc)(m+rm)＝fcm′
in the formula: f. ofr、fc、m、rmAnd m' is distance frequency variable, carrier frequency, uniform dispersion slow time indication, rmA random slow time indication and a new uniform slow time indication.
7. The ISAR translational compensation and imaging system according to claim 6, wherein the Doppler blur compensation function in module M3 is:
Figure FDA0003035651490000021
in the formula: mambRepresents a Doppler ambiguity number; j is an imaginary unit.
8. The ISAR translational compensation and imaging system of claim 7, wherein the acceleration phase compensation function in module M4 is:
Figure FDA0003035651490000022
wherein the content of the first and second substances,
Figure FDA0003035651490000023
represents the searched acceleration; c is the speed of light; t is the pulse repetition period of the geometric mean.
9. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 4.
10. An ISAR translational compensation and imaging device, comprising: a controller;
the controller comprising a computer readable storage medium of claim 9 having a computer program stored thereon which, when executed by a processor, performs the steps of the ISAR translational compensation and imaging method of any one of claims 1 to 4; alternatively, the controller comprises the ISAR translation compensation and imaging system of any of claims 5 to 8.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102628937A (en) * 2012-04-20 2012-08-08 西安电子科技大学 Radar detection method based on generalized keystone transformation and non-coherent accumulation
CN110501706A (en) * 2019-08-20 2019-11-26 中国人民解放军国防科技大学 ISAR (inverse synthetic aperture radar) imaging method for large-angle non-uniform rotation space target
CN111736128A (en) * 2020-06-22 2020-10-02 西安电子科技大学 Coherent accumulation method based on SKT-SIAF-MSCFT

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102628937A (en) * 2012-04-20 2012-08-08 西安电子科技大学 Radar detection method based on generalized keystone transformation and non-coherent accumulation
CN110501706A (en) * 2019-08-20 2019-11-26 中国人民解放军国防科技大学 ISAR (inverse synthetic aperture radar) imaging method for large-angle non-uniform rotation space target
CN111736128A (en) * 2020-06-22 2020-10-02 西安电子科技大学 Coherent accumulation method based on SKT-SIAF-MSCFT

Non-Patent Citations (7)

* Cited by examiner, † Cited by third party
Title
DONG LI等: "A Robust Translational Motion Compensation Method for ISAR Imaging Based on Keystone Transform and Fractional Fourier Transform Under Low SNR Environment", 《IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS》 *
JIBIN ZHENG等: "ISAR Imaging of Targets With Complex Motion Based on the Chirp Rate–Quadratic Chirp Rate Distribution", 《IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING》 *
JIBIN ZHENG等: "ISAR_Imaging_of_Nonuniformly_Rotating_Targets_Based_on_Generalized_Decoupling_Technique", 《IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING》 *
吴晓芳等: "合成孔径雷达干扰对抗仿真系统研究", 《系统仿真学报》 *
李东等: "一种低信噪比下稳健的ISAR平动补偿方法", 《电子学报》 *
李渝等: "雷达系统高机动目标检测的能量积累方法研究", 《高技术通讯》 *
王泽玉等: "基于频域校正的快速长时间积累算法", 《航空兵器》 *

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