罗迎^1,,,
龚逸帅^1,2,,
陈怡君^3,,
张群^1,
①.空军工程大学信息与导航学院 ??西安 ??710077
②.中国人民解放军95561部队 ??拉萨 ??850000
③.武警工程大学信息工程学院 ??西安 ??710086
基金项目:国家自然科学基金（61571457，61631019）

详细信息

作者简介:陈怡君(1989–)，女，陕西西安人，现为武警工程大学信息工程学院讲师，研究方向为认知成像与目标识别。E-mail: chenyijun519@126.com

通讯作者:罗迎　 luoying2002521@163.com

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出版历程

收稿日期:2018-04-25
修回日期:2018-06-02

Multi-target Micro-motion Feature Extraction Based on Tracking Pulses in MIMO Radar

Luo Ying^1,,,
Gong Yishuai^1,2,,
Chen Yijun^3,,
Zhang Qun^1,
①. Institute of Information and Navigation, Air Force Engineering University, Xi’an 710077, China
②. Troop of No. 95561, PLA, Lasa 850000, China
③. College of Information Engineering, Engineering University of CAPF, Xi’an 710086, China
Funds:The National Natural Science Foundation of China (61571457, 61631019)


摘要
摘要:微动特征是空间目标识别的重要特征信息之一。然而，现有的多功能多输入多输出(Multi-Input Multi-Output, MIMO)雷达通常需要在完成目标搜索和跟踪任务之后为目标微动特征提取分配大量连续的时间资源，导致目标识别实时性能和雷达系统整体工作性能均不高。针对该问题，该文提出了一种基于跟踪脉冲的MIMO雷达多目标微动特征提取方法。首先依据各目标的方位信息对MIMO雷达发射波形进行设计，为不同方向目标同时发射跟踪脉冲；在此基础上，综合考虑目标微动特征提取性能以及目标跟踪性能的需求，对跟踪脉冲的发射时间序列进行优化设计；最后，直接利用窄带跟踪脉冲实现对不同方向目标微动特征的同时提取，无需再为目标微动特征提取分配额外的时间资源，有效提升目标识别实时性和雷达工作效率。仿真实验表明，在信噪比大于–10 dB时，所提方法能够实现多目标微动特征的准确提取，具有良好的有效性和鲁棒性。
关键词:MIMO雷达/
微动特征/
多目标/
跟踪脉冲
Abstract:The micro-motion feature is one of the important characteristic information of spatial target recognition. However, the existing multifunctional Multi-Input Multi-Output (MIMO) radar usually has to allocate a large number of continuous time resources for target micro-motion feature extraction after target searching and tracking, which leads to a low real-time performance of target recognition and poor overall performance of radar system. To solve this problem, this paper presents a multi-target micro-motion feature extraction method for MIMO radar based on tracking pulses. First, according to the azimuth information of each target, the MIMO radar transmitting waveform is designed, and the tracking pulses are transmitted simultaneously for targets with different directions. On this basis, by considering the micro-motion feature extraction performance and the target tracking performance synthetically, the transmission time series of the tracking pulses are optimized. Finally, the narrowband tracking pulses are directly used to simultaneously extract the micro-motion features of the targets in different directions, which makes it no longer necessary to allocate additional radar resources for target feature extraction. Consequently, the real-time recognition performance and the working efficiency of radar are improved significantly. Simulations demonstrate that when the signal-to-noise ratio is larger than –10 dB, the micro-motion features of multi-targets can be extracted accurately, which verifies the effectiveness and robustness of the proposed method.
Key words:Multi-Input Multi-Output (MIMO) radar/
Micro-motion feature/
Multi-target/
Tracking pulses



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