基于压缩感知的认知雷达多目标跟踪方法
该文提出了一种基于压缩感知的认知雷达跟踪方法,该方法将压缩感知理论引入到认知雷达跟踪的问题中。通过对回波信号的稀疏表示,完成稀疏变换矩阵和观测矩阵的设计,实现了降采样条件下量测信号的重构。在系统的接收端,考虑到传统的粒子滤波容易陷入局部最优,对粒子数目要求大等问题,采用了粒子群优化的粒子滤波来对目标状态进行实时估计。在系统的发射端,采用优化后验克拉美罗界(Posterior Cramer-Rao Bounds,PCRB)设计了雷达发射波形参数,降低了对目标跟踪精度的PCRB。仿真表明,相比于传统跟踪方法,该文所提跟踪方法不仅有效地减少了雷达的数据量,而且较大地提高了目标的跟踪性能。...
Saved in:
Published in | 雷达学报 Vol. 5; no. 1; pp. 90 - 98 |
---|---|
Main Author | |
Format | Journal Article |
Language | Chinese |
Published |
空军工程大学信息与导航学院西安 710077%空军工程大学信息与导航学院西安 710077
2016
复旦大学电磁波信息科学教育部重点实验室上海 200433 |
Subjects | |
Online Access | Get full text |
ISSN | 2095-283X |
DOI | 10.12000/JR14107 |
Cover
Summary: | 该文提出了一种基于压缩感知的认知雷达跟踪方法,该方法将压缩感知理论引入到认知雷达跟踪的问题中。通过对回波信号的稀疏表示,完成稀疏变换矩阵和观测矩阵的设计,实现了降采样条件下量测信号的重构。在系统的接收端,考虑到传统的粒子滤波容易陷入局部最优,对粒子数目要求大等问题,采用了粒子群优化的粒子滤波来对目标状态进行实时估计。在系统的发射端,采用优化后验克拉美罗界(Posterior Cramer-Rao Bounds,PCRB)设计了雷达发射波形参数,降低了对目标跟踪精度的PCRB。仿真表明,相比于传统跟踪方法,该文所提跟踪方法不仅有效地减少了雷达的数据量,而且较大地提高了目标的跟踪性能。 |
---|---|
Bibliography: | 10-1030/TN Yang Jun,Zhang Qun,Luo Ying,Deng Donghu(1.Information and Navigation Institute, Air Force Engineering University, Xi'an 710077, China;2.Key Laboratory for Information Science of Electromagnetic Waves(Ministry of Education), Fudan University, Shanghai 200433, China) Cognitive radar;Compressed Sensing(CS);Multiple target tracking;Waveform design;Particle Filter(PF) A multiple targets cognitive radar tracking method based on Compressed Sensing(CS) is proposed.In this method,the theory of CS is introduced to the case of cognitive radar tracking process in multiple targets scenario.The echo signal is sparsely expressed.The designs of sparse matrix and measurement matrix are accomplished by expressing the echo signal sparsely,and subsequently,the restruction of measurement signal under the down-sampling condition is realized.On the receiving end,after considering that the problems that traditional particle filter suffers from degeneracy,and require a large number of particles,the particle swarm optimization |
ISSN: | 2095-283X |
DOI: | 10.12000/JR14107 |