Computer Science ›› 2022, Vol. 49 ›› Issue (8): 178-183.doi: 10.11896/jsjkx.210600066

• Computer Graphics & Multimedia • Previous Articles     Next Articles

Study on Acceleration Algorithm for Raw Data Simulation of High Resolution Squint Spotlight SAR

GUO Zheng-wei, FU Ze-wen, LI Ning, BAI Lan   

  1. College of Computer and Information Engineering,Henan University,Kaifeng,Henan 475004,China
    Henan Engineering Research Center of Intelligent Technology and Application,Henan University,Kaifeng,Henan 475004,China
    Key Laboratory of Analysis and Processing on Big Data of Henan Province,Henan University,Kaifeng,Henan 475004,China
  • Received:2021-06-04 Revised:2021-09-06 Published:2022-08-02
  • About author:GUO Zheng-wei,born in 1963,bachelor,professor,master supervisor.is a member of China Computer Federation.Her main research interests include SAR image processing techniques,and SAR image application of ecological environment.
    LI Ning,born in 1987,Ph.D,professor,Ph.D supervisor,is a member of China Computer Federation.His main research interests include multi-mode SAR imaging and SAR application.
  • Supported by:
    National Natural Science Foundation of China(61871175),College Key Research Project of Henan Province(19A420005,21A520004),Plan of Science and Technology of Henan Province(202102210175,212102210093 ,212102210101) and Key Laboratory of Land Satellite Remote Sensing Application,Ministry of Natural Resources of the People’s Republic of China(KLSMNR-202102).

Abstract: Raw data simulation is the front-end work of synthetic aperture radar(SAR) system development,which is of great significance.For high resolution squint spotlight SAR,time-domain raw data simulation is usually used,but its simulation efficiency is very low.In order to realize the raw data simulation of high resolution squint spotlight SAR efficiently,an effective acceleration algorithm is proposed.To reduce the redundant computation and save memory,this algorithm combines the time-domain raw data simulation model and its signal characteristics to compensate the range cell migration(RCM) in the raw data simulation process of squint spotlight SAR.An adaptive data partitioning algorithm is adopted to compute the partitioned data in graphic processing unit(GPU), and the powerful computing capabilities of GPU is used to improve efficiency.Then the sub data blocks are transmitted and spliced in memory.The proposed algorithm improves the computational efficiency of time-domain raw data simulation,and solves the problems of huge volume of raw data,limited GPU memory and data transmission between video memory and memory.Experimental results of point targets and distributed targets show that the speedup ratio of this algorithm reaches 219.8,which verifies the effectiveness of the proposed method.

Key words: GPU, High resolution, Range cell migration, Synthetic aperture radar, Time-domain raw data simulation

CLC Number: 

  • TP702
[1]LI N,NIU S L.High-precision water segmentation from syn-thetic aperture radar images based on local super-resolution restoration technology[J].Journal of Radars,2020,9(1):174-184.
[2]ZHOU Y Y,CHENG J H,LIU T,et al.Review of Road Extraction for High-resolution SAR Images[J].Computer Science,2020,47(1):124-135.
[3]WANG B Q,QI X Y,ZHOU S B.An Improved Echo Simulation Method of GEO SAR[J].Radar Science and Technology,2019,17(2):198-207.
[4]ZENG L T,YANG C H,LI Q,et al.Vaildation of SyntheticAperture Radar(SAR) Image Algorithm Based on Simulation[J].Computer Science,2019,46(S1):287-290.
[5]FAN W,ZHANG M,LI J,et al.Modified Range-Doppler Algorithm for High Squint SAR Echo Processing[J].IEEE Geoence and Remote Sensing Letters(S1545-598X),2019,16(3):422-426.
[6]LI G,MA Y H,HOU J Q,et al.Sub-aperture Keystone Transform Based Echo Simulation Method for High-squint SAR with a Curve Trajectory[J].Journal of Electronics & Information Technology,2020,42(9):2261-2268.
[7]ZUO X Y,ZHANG Z,SU Y H,et al.Extraction Algorithm of NDVI Based on GPU Multi-stream Parallel Model[J].Computer Science, 2020,47(4):25-29.
[8]MENG D D,HU Y X,SHI T,et al.Airborne SAR Real-time Imaging Algorithm Design and Implementation with CUDA on NVIDIA GPU[J].Journal of Radars,2013,2(4):481-491.
[9]ZHOU F,LI J.Research on Multi-core DSP Based Parallel Access for SAR Data[J].Modern Electronics Technique,2018,41(15):26-30.
[10]CHEN Q,ZHU M B,ZOU X H,et al.Fast Realization of Bista-tic SAR Echo Simulation Based on GPU Acceleration[J].Computer Simulation,2017,34(4):1-4.
[11]WIJAYASIRI A,BANERJEE T,RANKA S,et al.Dynamic Data-Driven SAR Image Reconstruction Using Multiple GPUs[J].IEEE Journal of Selected Topics in Applied Earth Observations &Remote Sensing(S1939-1404),2018,11(11):4326-4338.
[12]LIU Y,XING M D,SUN G C,et al.Echo Model Analyses and Imaging Algorithm for High-Resolution SAR on High-Speed Platform[J].IEEE Transactions on Geoscience and Remote Sensing(S0196-2892),2012,50(3):933-950.
[13]CHENG D,WANG W H.Application of OpenMP in SAR Image Processing[J].Computer Science,2017,44(S1):161-163,187.
[14]HU C,ZHANG F,LI G J,et al.Computation Reduction Oriented Circular Scanning SAR Raw Data Simulation on Multi-GPUs[J].Journal of Radars,2016,5(4):434-443.
[15]LIU Y B,ZHOU Y C,ZHOU Y S,et al.Accelerating SARImage Registration Using Swarm-Intelligent GPU Parallelization[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2020,13(1):5694-5703.
[16]YANG W D,WANG H T,ZHANG Y F,et al.Survey of Hete-rogeneous Hybrid Parallel Computing[J].Computer Science,2020,47(5):5-16,3.
[17]ZAMBRE R,SAHASRABUDHE D,ZHOU H,et al.Logically Parallel Communication for Fast MPI+Threads Applications[J].IEEE Transactions on Parallel and Distributed Systems,2021,32(12):3038-3052.
[18]ZHANG Y R,CHEN L,AN X Z,et al.Study on PerformaceOptimization of Reduction Algorithm Targeting GPU Computing Platform[J].Computer Science,2019,46(2):306-314.
[19]LIU S,ZOU B,ZHANG L M,et al.A Multi-GPU Accelerated Parallel Domain Decomposition One-Step Leapfrog ADI-FDTD[J].IEEE Antennas and Wireless Propagation Letters,2020,19(5):816-820.
[20]KIM M,LIU L,CHOI W,et al.Multi-GPU Efficient Indexing for Maximizing Parallelism of High Dimensional Range Query Services[J/OL].IEEE Transactions on Services Computing,2021.https://ieeexplore.ieee.org/document/9430517.
[21]FARIBORZ M,XIAO X,FOTOUHI P,et al.Silicon Photonic Flex-LIONS for Reconfigurable Multi-GPU Systems[J].Journal of Lightwave Technology,2021,39(4):1212-1220.
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