A Modified Range Migration Algorithm for FMCW SAR Signal Processing

The range migration algorithm (RMA) is an accurate imaging method for processing synthetic aperture radar (SAR) signals. However, this algorithm requires a big amount of computation when performing Stolt mapping. In high squint and wide beamwidth imaging, this operation also requires big memory size to store the result spectrum after Stolt mapping because the spectrum will be significantly expanded. A modified Stolt mapping that does not expand the signal spectrum while still maintains the processing accuracy is proposed in this paper to improve the efficiency of the RMA when processing frequency modulated continuous wave (FMCW) SAR signals. The modified RMA has roughly the same computational load and required memory size as the range Doppler algorithm (RDA) when processing FMCW SAR data. In extreme cases when the original spectrum is significantly modified by the Stolt mapping, the modified RMA achieves better focusing quality than the traditional RMA. Simulation and real data are used to verify the performance of the proposed RMA.

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A Modified Range Migration Algorithm for FMCW SAR Signal Processing

Remote Sensing ◽

10.18282/rs.v8i1.517 ◽

2019 ◽

Vol 8 (1) ◽

Author(s):

Li Yake ◽

Siu O’ Young

Keyword(s):

Signal Processing ◽

Continuous Wave ◽

Real Data ◽

Synthetic Aperture ◽

Signal Spectrum ◽

Imaging Method ◽

Memory Size ◽

Processing Accuracy ◽

Range Migration ◽

Accurate Imaging

The range migration algorithm (RMA) is an accurate imaging method for processing synthetic aperture radar (SAR) signals. However, this algorithm requires a big amount of computation when performing Stolt mapping. In high squint and wide beamwidth imaging, this operation also requires big memory size to store the result spectrum after Stolt mapping because the spectrum will be significantly expanded. A modified Stolt mapping that does not expand the signal spectrum while still maintains the processing accuracy is proposed in this paper to improve the efficiency of the RMA when processing frequency modulated continuous wave (FMCW) SAR signals. The modified RMA has roughly the same computational load and required memory size as the range Doppler algorithm (RDA) when processing FMCW SAR data. In extreme cases when the original spectrum is significantly modified by the Stolt mapping, the modified RMA achieves better focusing quality than the traditional RMA. Simulation and real data are used to verify the performance of the proposed RMA.

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Verification of Imaging Algorithm for Signal Processing Software within Synthetic Aperture Radar (SAR) System

Scientific Programming ◽

10.1155/2019/7105281 ◽

2019 ◽

Vol 2019 ◽

pp. 1-12 ◽

Cited By ~ 1

Author(s):

Le-tian Zeng ◽

Chun-hui Yang ◽

Mao-sheng Huang ◽

Yue-long Zhao

Keyword(s):

Signal Processing ◽

Data Processing ◽

Synthetic Aperture Radar ◽

Software Testing ◽

Real Data ◽

Synthetic Aperture ◽

Data Simulation ◽

Motion Error ◽

Processing Software ◽

Aperture Radar

In the signal processing software testing for synthetic aperture radar (SAR), the verification for algorithms is professional and has a very high proportion. However, existing methods can only perform a degree of validation for algorithms, exerting an adverse effect on the effectiveness of the software testing. This paper proposes a procedure-based approach for algorithm validation. Firstly, it describes the processing procedures of polar format algorithm (PFA) under the motion-error circumstance, based on which it analyzes the possible questions that may exist in the actual situation. By data simulation, the SAR echoes are generated flexibly and efficiently. Then, algorithm simulation is utilized to focus on the demonstrations for the approximations adopted in the algorithm. Combined with real data processing, the bugs concealed are excavated further, implementing a comprehensive validation for PFA. Simulated experiments and real data processing validate the correctness and effectiveness of the proposed algorithm.

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Signal Processing for Digital Beamforming FMCW SAR

Mathematical Problems in Engineering ◽

10.1155/2014/859890 ◽

2014 ◽

Vol 2014 ◽

pp. 1-10 ◽

Cited By ~ 6

Author(s):

Qin Xin ◽

Zhihong Jiang ◽

Pu Cheng ◽

Mi He

Keyword(s):

Signal Processing ◽

Continuous Wave ◽

Single Channel ◽

Pulse Repetition Frequency ◽

Sampling Frequency ◽

Synthetic Aperture ◽

Signal Model ◽

Digital Beamforming ◽

Processing Gain ◽

Detailed Imaging

According to the limitations of single channel Frequency Modulation Continuous Wave (FMCW) Synthetic Aperture Radar (SAR), Digital Beamforming (DBF) technology is introduced to improve system performance. Combined with multiple receive apertures, DBF FMCW SAR can obtain high resolution in low pulse repetition frequency, which can increase the processing gain and decrease the sampling frequency. The received signal model of DBF FMCW SAR is derived. The continuous antenna motion which is the main characteristic of FMCW SAR received signal is taken into account in the whole signal processing. The detailed imaging diagram of DBF FMCW SAR is given. A reference system is also demonstrated in the paper by comparing with a single channel FMCW SAR. The validity of the presented diagram is demonstrated with a point target simulation results.

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Signal Processing for a Multiple-Input, Multiple-Output (MIMO) Video Synthetic Aperture Radar (SAR) with Beat Frequency Division Frequency-Modulated Continuous Wave (FMCW)

Remote Sensing ◽

10.3390/rs9050491 ◽

2017 ◽

Vol 9 (5) ◽

pp. 491 ◽

Cited By ~ 7

Author(s):

Seok Kim ◽

Jiwoong Yu ◽

Se-Yeon Jeon ◽

Aulia Dewantari ◽

Min-Ho Ka

Keyword(s):

Signal Processing ◽

Synthetic Aperture Radar ◽

Continuous Wave ◽

Beat Frequency ◽

Multiple Input Multiple Output ◽

Synthetic Aperture ◽

Frequency Division ◽

Multiple Input ◽

Input Multiple Output ◽

Division Frequency

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Model and signal processing of bistatic frequency-modulated continuous wave synthetic aperture radar

IET Radar Sonar & Navigation ◽

10.1049/iet-rsn.2011.0276 ◽

2012 ◽

Vol 6 (6) ◽

pp. 472-482 ◽

Cited By ~ 4

Author(s):

Y. Liu ◽

Y. Kai Deng ◽

R. Wang ◽

O. Loffeld ◽

X. Wang

Keyword(s):

Signal Processing ◽

Synthetic Aperture Radar ◽

Continuous Wave ◽

Synthetic Aperture ◽

Aperture Radar

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Interferometric DEM-Assisted High Precision Imaging Method for ArcSAR

Sensors ◽

10.3390/s19132921 ◽

2019 ◽

Vol 19 (13) ◽

pp. 2921 ◽

Cited By ~ 2

Author(s):

Yanping Wang ◽

Yang Song ◽

Yun Lin ◽

Yang Li ◽

Yuan Zhang ◽

...

Keyword(s):

Synthetic Aperture Radar ◽

High Precision ◽

Deformation Monitoring ◽

Synthetic Aperture ◽

Reference Plane ◽

Imaging Method ◽

Range Migration ◽

Dem Accuracy ◽

Actual Height ◽

Aperture Radar

Ground-based arc-scanning synthetic aperture radar (ArcSAR) is the novel ground-based synthetic aperture radar (GBSAR). It scans 360-degree surrounding scenes by the antenna attached to rotating boom. Therefore, compared with linear scanning GBSAR, ArcSAR has larger field of view. Although the feasibility of ArcSAR has been verified in recent years, its imaging algorithm still presents difficulties. The imaging accuracy of ArcSAR is affected by terrain fluctuation. For rotating scanning ArcSAR, even if targets in scenes have the same range and Doppler with antenna, if the heights of targets are different, their range migration will be different. Traditional ArcSAR imaging algorithms achieve imaging on reference plane. The height difference between reference plane and target in scenes will cause the decrease of imaging quality or even image defocusing because the range migration cannot be compensated correctly. For obtaining high-precision ArcSAR image, we propose interferometric DEM (digital elevation model)-assisted high precision imaging method for ArcSAR. The interferometric ArcSAR is utilized to acquire DEM. With the assist of DEM, target in scenes can be imaged on its actual height. In this paper, we analyze the error caused by ArcSAR imaging on reference plane. The method of extracting DEM on ground range for assisted ArcSAR imaging is also given. Besides, DEM accuracy and deformation monitoring accuracy of proposed method are analyzed. The effectiveness of the proposed method was verified by experiments.

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A Novel Ship Imaging Method with Multiple Sinusoidal Functions to Match Rotation Effects in Geosynchronous SAR

Remote Sensing ◽

10.3390/rs12142249 ◽

2020 ◽

Vol 12 (14) ◽

pp. 2249

Author(s):

Wei Xiong ◽

Ying Zhang ◽

Xichao Dong ◽

Chang Cui ◽

Zheng Liu ◽

...

Keyword(s):

Rotational Motion ◽

Numerical Experiments ◽

Projection Algorithm ◽

Synthetic Aperture ◽

Imaging Method ◽

Back Projection ◽

Rotation Effect ◽

Signal Model ◽

Range Migration ◽

Sinusoidal Functions

Geosynchronous Synthetic Aperture Radar (GEO SAR) has a very long Coherent Processing Interval (in the order of hundreds of seconds) compared with other SAR platforms. Thus, the current methods of rotation effect matching and ship imaging that operate within a relatively short Coherent Processing Interval (in the order of seconds) are obviously not applicable. To address this problem, a novel ship imaging method with multiple sinusoidal functions matching for rotation effects is proposed for GEO SAR. Firstly, the influence of the rotational motion of a ship on the slant range is analyzed. It can be matched with the sum of multiple sinusoidal functions, and the signal model of a ship with rotational motion is given. Then, multiple sinusoidal functions for the matching-based ship imaging method are proposed, and their procedures are presented as follows: (1) The Generalized Keystone Transform and Generalized Dechirp Process (GKTGDP) is modified to compensate for the range migration and phase caused by the motion of GEO SAR. Then, the signal is focused at the frequencies of sinusoidal functions, and the frequencies can be matched. (2) From the matched frequencies, the other parameters of sinusoidal functions can be matched by parameter searching. (3) Based on the matched results, the Back Projection Algorithm (BPA) is used to take an image of the ship with rotational motion. Finally, the effectiveness of the proposed method is verified by numerical experiments.

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Accurate Wide Angle SAR Imaging Based on LS-CS-Residual

Sensors ◽

10.3390/s19030490 ◽

2019 ◽

Vol 19 (3) ◽

pp. 490 ◽

Cited By ~ 3

Author(s):

Zhonghao Wei ◽

Bingchen Zhang ◽

Yirong Wu

Keyword(s):

Compressed Sensing ◽

Least Squares ◽

Large Angle ◽

Real Data ◽

Synthetic Aperture ◽

Sparse Signals ◽

Imaging Method ◽

Wide Angle ◽

Support Set ◽

Prior Estimate

Wide angle synthetic aperture radar (WASAR) receives data from a large angle, which causes the problem of aspect dependent scattering. L 1 regularization is a common compressed sensing (CS) model. The L 1 regularization based WASAR imaging method divides the whole aperture into subapertures and reconstructs the subaperture images individually. However, the aspect dependent scattering recovery of it is not accurate. The subaperture images of WASAR can be regarded as the SAR video. The support set among the different frames of SAR video are highly overlapped. Least squares on compressed sensing residuals (LS-CS-Residuals) can reconstruct the time sequences of sparse signals which change slowly with time. This is to replace CS on the observation by CS on the least squares (LS) residual computed using the prior estimate of the support. In this paper, we introduce LS-CS-Residual into WASAR imaging. In the iteration of LS-CS-Residual, the azimuth-range decoupled operators are used to avoid the huge memory cost. Real data processing results show that LS-CS-Residual can estimate the aspect dependent scatterings of the targets more accurately than CS based methods.

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