一种新的无人机载雷达非均匀杂波抑制方法

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

无人机; 空时自适应处理; 地面运动目标检测; 杂波抑制; 样本筛选; 非均匀环境; 无人机载雷达; 恒虚警

A novel heterogeneous clutter suppression method for UAV airborne radar based on the CFAR strategy
CHEN Hongmeng1, LIU Jing1, LI Ming2, YI Xiaoli1, MU Heqiang1, and LU Yaobing1

1)Beijing Institute of Radio Measurement, Beijing 100854, P.R.China2)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)

DOI: 10.3724/SP.J.1249.2019.05489

备注

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.

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