CHEN Hongmeng,LIU Jing,LI Ming,et al.A novel heterogeneous clutter suppression method for UAV airborne radar based on the CFAR strategy[J].Journal of Shenzhen University Science and Engineering,2019,36(5):489-496.[doi:10.3724/SP.J.1249.2019.05489]





A novel heterogeneous clutter suppression method for UAV airborne radar based on the CFAR strategy
1)北京无线电测量研究所,北京 100854
2)西安电子科技大学雷达信号处理国家重点实验室,陕西西安 710071
CHEN Hongmeng1 LIU Jing1 LI Ming2 YI Xiaoli1 MU Heqiang1 and LU Yaobing1
1)Beijing Institute of Radio Measurement, Beijing 100854, P.R.China
2) National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, Shaanxi Province, P.R.China
unmanned aerial vehicle space time adaptive processing (STAP) ground moving target indication (GMTI) clutter suppression sample selection heterogeneous environment UAV airborne radar constant false alarm rate (CFAR)
无人机载雷达可以对感兴趣的重点区域和目标进行持续跟踪,在军用和民用领域都有广泛应用前景.然而载机平台的运动会带来地杂波谱的展宽,致使潜在的低速微弱目标淹没在强地杂波中.为了解决无人机机载雷达非均匀环境下的地面杂波抑制问题,提出一种基于恒虚警样本选择策略的非均匀下视杂波抑制方法.通过距离分块策略解决距离空变带来的非均匀样本的差异,通过低门限恒虚警(constant false alarm rate, CFAR)策略剔除孤立的强杂波散射点和疑似运动目标对训练样本的影响,降低非均匀样本单元对协方差矩阵估计的干扰,从而提高非均匀环境下对杂波的抑制性能.结合一组实测挂飞数据,对比了不同杂波抑制方法对运动目标检测的影响.实测数据验证所提方法有效.
UAV-airborne radar can continuously track key areas and targets of interests, so it has broad application prospects in both military and civilian fields. However, the movement of the platform will lead to broadening of the ground clutter spectrum, resulting in submergence of potential slow-speed weak targets in the strong ground clutter. To solve this problem, a new space-time adaptive processing (STAP) algorithm based on constant false-alarm rate (CFAR) sample selection techniques is proposed. Firstly, the blocked sample selection strategy in range is utilized to decrease the effect of range-variance. Then, the low threshold CFAR strategy is exploited to eliminate the influence of strong singular scatters and suspected moving targets on training samples, which is useful to improve the accuracy of covariance matrix estimation. Thus, the clutter suppression performance in heterogeneous environment can be enhanced. Finally, the performance of different clutter suppression methods in moving targets detection is analyzed by resorting to the airborne experimental results, which further confirms the effectiveness of the proposed algorithm.


[1] MAKHOUL E, BROQUETAS A, RUIZ RODON J, et al. A performance evaluation of SAR-GMTI missions for maritime applications[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(5): 2496-2509.
[2] ENTZMINGER J, FOWLER C, KENNEALLY W. JointSTARS and GMTI: past, present and future[J]. IEEE Transactions on Aerospace and Electronic Systems, 1999, 35(2):748-761.
[3] HEPBURN J S A, DOYLE C P. Motion compensation for ASTOR long range SAR[C]// IEEE Position Location and Navigation Symposium. Las Vegas, USA: IEEE, 1990:205-211.
[4] ANGENOORTH P, CHABOD L, HOOGEBOOM P. The SOSTAR-X program achievements[C]// Proceedings of the 38th European Microwave Conference. Amsterdam, The Netherlands: IEEE, 2008: 1648-1650.
[5] CERUTTI-MAORI D, KLARE J, BRENNER A R,et al. Wide-area traffic monitoring with the SAR/GMTI system PAMIR[J]. IEEE Transactions on Geoscience Remote Sensing, 2008, 46(10): 3019-3030.
[6] GRACHEVA V, ENDER J. Multichannel analysis and suppression of sea clutter for airborne microwave radar systems[J]. IEEE Transactions on Geoscience Remote Sensing, 2016, 54(4): 2385-2399.
[7] TOPORKOV J V. Analytical study of along-track InSAR imaging of a distributed evolving target with application to phase and coherence signatures of breakers and whitecaps[J]. IEEE Geoscience Remote Sensing Letters,2014,11(8):1385-1389.
[8] LI Jie, HUANG Yan, LIAO Guisheng, et al. Moving target detection via efficient ATI-GoDecapproach for multichannel SAR system[J].IEEE Geoscience Remote Sensing Letters,2016,13(9): 1320-1324.
[9] TANELLI S, DURDEN S L, JOHNSON M P. Airborne demonstration of DPCA for velocity measurements of distributed targets[J]. IEEE Geoscience Remote Sensing Letters, 2016, 13(10): 1415-1419.
[10] TONG Yalong, WANG Tong, WU Jianxin. Improving EFA-STAP performance using persymmetric covariance matrix estimation[J]. IEEE Transaction Actions on Aerospace and Electronic Systems, 2015, 51(2): 924-936.
[11] YANG Xiaopeng, SUN Yuze, ZENG Tao, et al. Fast STAP method based on PAST with sparse constraint for airborne phased array radar[J]. IEEE Transactions on Signal Processing, 2016, 64(17): 4550-4561.
[12] YANG Zhaocheng. Sparsity-based space-time adaptive processing using complex-valued Homotopy technique for airborne radar[J]. IET Signal Processing, 2014, 8(5): 552-564.
[13] SEN S. Low-rank matrix decomposition and spatio-temporal sparse recovery for STAP radar[J]. IEEE Journal of Selected Topics in Signal Processing, 2015, 9(8): 1510-1523.
[14] 谢文冲,段克清,王永良.机载雷达空时自适应处理技术研究综述[J].雷达学报,2017,6(6):575-586.
XIE Wenchong, DUAN Keqing, WANG Yongliang. Space time adaptive processing technique for airborne radar: an overview of its development and prospects[J]. Journal of Radars, 2017, 6(6): 575-586.(in Chinese)
[15] HAN Sudan, FAN Chongyi, HUANG Xiaotao. A novel STAP based on spectrum-aided reduced-dimension clutter sparse recovery[J]. IEEE Geoscience and Remote Sensing Letters, 2017, 14(2): 213-217.
[16] 李真芳,保铮,王彤,等.基于实测数据的地面慢速动目标检测[J].电子学报,2003,31(9):1437-1440.
LI Zhenfang, BAO Zheng, WANG Tong, et al. Slowly moving ground target detection based on measured data[J]. ACTA Electronica Sinica, 2003, 31(9): 1437-1440.(in Chinese)
[17] ZHANG Xuepan, LIAO Guisheng, ZHU Shengqi, et al. Geometry-information-aided efficient radial velocity estimation for moving target imaging and location based on radon transform[J]. IEEE Transaction on Geoscience Remote Sensing,2015, 53(2):1105-1117.
[18] WANG Zeyu, LI Ming, LU Yunlong, et al. Efficient TR-TBD algorithm for slow-moving weak multi-targets in heavy clutter environment[J]. IET Signal Processing, 2017, 11(4):422-428.
[19] WANG Chenghao, LIAO Guisheng, ZHANG Qingjun. First space borne SAR-GMTI experimental results for the Chinese gaofen-3 dual-channel SAR sensor[J]. Sensors, 2017, 17(11): 2683.
[20] YAN He, WANG R Y, GAO Canguan, et al. Channel balancing algorithm in multichannel wide-area surveillance systems[J]. IET Radar, Sonar Navigation, 2014, 8(1): 27-36.


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Foundation:National Natural Science Foundation of China (61272281); Postdoctoral Science Foundation of China (2017M610966)
Corresponding author:Professor LU Yaobing.E-mail: luyaobing65@163.com
Citation:CHEN Hongmeng, LIU Jing, LI Ming, et al. A novel heterogeneous clutter suppression method for UAV airborne radar based on the CFAR strategy[J]. Journal of Shenzhen University Science and Engineering, 2019, 36(5): 489-496.(in Chinese)
引文:陈洪猛,刘京,李明,等.一种新的无人机载雷达非均匀杂波抑制方法[J]. 深圳大学学报理工版,2019,36(5):489-496.
更新日期/Last Update: 2019-09-30