计算机科学 ›› 2019, Vol. 46 ›› Issue (6A): 287-290.

• 网络与通信 • 上一篇    下一篇

基于仿真的合成孔径雷达(SAR)成像算法验证

曾乐天1,2, 杨春晖1, 李强1, 陈平1   

  1. 工业和信息化部电子第五研究所 广州5106101;
    华南理工大学计算机科学与工程学院 广州5106402
  • 出版日期:2019-06-14 发布日期:2019-07-02
  • 通讯作者: 曾乐天(1988-),男,博士,工程师,主要研究方向为雷达成像、雷达软件测试、质量与可靠性,E-mail:zengletian@ceprei.com
  • 作者简介:杨春晖(1965-),女,博士,研究员级高级工程师,主要研究方向为质量与可靠性;李 强(1990-),男,硕士,工程师,主要研究方向为质量与可靠性;陈 平(1985-),男,硕士,高级工程师,主要研究方向为质量与可靠性。
  • 基金资助:
    本文受中国博士后科学基金资助项目(2017M622621)资助。

Validation of Synthetic Aperture Radar(SAR) Imaging Algorithm Based on Simulation

ZENG Le-tian1,2, YANG Chun-hui1, LI Qiang1, CHEN Ping1   

  1. The Fifth Electronic Research Institute of MIIT,Software Quality Engineering Research Center,Guangzhou 510610,China1;
    School of Computer Science and Engineering,South China University of Technology,Guangzhou 510640,China2
  • Online:2019-06-14 Published:2019-07-02

摘要: 成像算法是影响合成孔径雷达(SAR)成像性能的关键因素。现有测试方法须借助实际设备、雷达数据和测试环境,且缺乏对成像效果的合理评估,严重影响了测试工作的效率和有效性。针对上述问题,提出了一种基于仿真的SAR成像算法验证方法。首先,采用改进的同心圆法独立生成回波数据,摆脱对实际雷达回波数据的依赖性;然后,结合点目标成像和分布式场景目标成像,采用量化的指标科学评估成像算法的正确性与适用性,提高了算法测试工作的有效性;最后,利用仿真实验证明了所提方法的正确性和有效性。

关键词: 成像算法验证, 仿真, 合成孔径雷达(SAR)

Abstract: Imaging algorithm is crucial to the performance of the synthetic aperture radar (SAR).Existing testing methodnot only needs to use real equipment,radar data and testing environment,but also lacks a reasonable evaluation for the imaging result,which greatly affect the efficiency and effectiveness of the software testing.To solve these problems,this paper presented a novel testing method based on simulation for the validation of SAR imaging algorithms.Firstly,the echo data are generated independently via improved concentric circle method,eliminating the real echo data constraint.Then,the correctness and feasibility of imaging algorithms are evaluated scientifically by quantitative indicators combined with point target imaging as well as distributed scene target imaging.The proposed method greatly improves the effectiveness of the testing work.Finally,the correctness and the effectiveness of the proposed method were verified by simulation experiments.

Key words: Simulation, Synthetic aperture radar(SAR), Validation of imaging algorithm

中图分类号: 

  • TP311
[1]CUMMING I G,WONG F H.Digital Processing of Synthetic Aperture Radar Data:Algorithm and Implementation [M].Boston,MA:Artech House,2005:113-168.
[2]CARRARA W G,GOODMAN R S,MAJEWSKI R M.Spotlight Synthetic Aperture Radar:Signal Processing Algorithm [M].Boston,MA:Artech House,1995:13-80.
[3]曾乐天.机载高分辨聚束SAR成像及运动补偿算法研究[D].西安:西安电子科技大学,2016.
[4]GAROUSI V,FELDERER M,HACALOGLU T.What We Know about Software Test Maturity and Test Process Improvement [J].IEEE Software,2018,35(1):84-92.
[5]PAUL C J.Software Testing:A Craftsman’s Approach(4th Edition)[M].Boca Raton,CRC Press,2013:221-228.
[6]TARLINDER A.Developer Testing:Building Quality into Software [M].Boston,MA:,Addison-Wesley Professional,2016:21-36.
[7]KASSAB M,DEFRANCO J F,LAPLANTE P A.Software Tes-ting:The State of The Practice [J].IEEE Software,2017,34(5):46-52.
[8]JIANG H,TANG K,PETKE J,et al.Search Based Software Engineering [J].IEEE Computational Intelligence Magazine,2017,12(2):23-71.
[9]BIANCHI F,MARGARA A,PEZZE M.A Survey of Recent Trends in Testing Concurrent Software Systems [J].IEEE Transactions on Software Engineeringm,2017,PP(99):1-40.
[10]ITKONEN J,MANTYLA M V,LASSENIUS C.The Role of The Tester’s Knowledge in Exploratory Software Testing [J].IEEE Transactions on Software Engineering,2013,39(5):707-724.
[11]SPINELLIS D.State-of-The-Art Software Testing [J].IEEE Software,2017,34(5):4-6.
[12]景国彬,张云骥,李震宇,等.基于GPU的SAR回波仿真高效实现方法 [J].系统工程与电子技术,2016,38(11):2493-2498.
[13]王伯岭,孙进平,吴双力,等.扩展场景的SAR回波信号快速仿真算法 [J].遥测遥控,2005,26(6):33-38.
[14]RANEY R K,RUNGE H,BAMLER R,et al.Precision SAR Processing Using Chirp Scaling [J].IEEE Geoscience and Remote Sensing Letters,1994,32(4):786-799.
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