集中式多输入多输出雷达多功能波形优化设计

陈志坤; 李风从; 乔晓林; 赵宜楠

doi:10.11999/JEIT141079

集中式多输入多输出雷达多功能波形优化设计

doi: 10.11999/JEIT141079

基金项目:

国家自然科学基金(61371181)资助课题

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- 被引次数: 30
出版历程
- 收稿日期: 2014-08-14
- 修回日期: 2015-02-09
- 刊出日期: 2015-06-19

Optimal Multi-function Waveform Design for MIMO Radar with Collocated Antennas

摘要

摘要: 针对集中式多输入多输出(MIMO)雷达波形设计中多个设计目标同时优化的问题，基于交替投影的思想，该文提出一种以任意维迭代谱逼近算法(ADISAA)为基础的波形设计框架，通过可调的权重来协调发射方向图匹配、良好的相关特性和频谱凹口等多种功能的波形设计目标，最终实现恒模波形设计。仿真结果表明，相对于已有的算法，在发射方向图匹配的基础上，该算法改善了发射波形在指定区间的相关特性，同时通过频谱凹口的设计避开了受到色噪声和有源干扰污染的频段，算法的计算复杂度更低。
- 多输入多输出雷达 /
- 波形设计 /
- 发射方向图匹配 /
- 相关特性
Abstract: This paper addresses the simultaneous optimization problem of the multi-objective waveform design for MIMO radar with collocated antennas. Inspired from the idea of alternating projection, a waveform design framework is presented based on the Arbitrary-Dimensional Iterative Spectral Approximation Algorithm (ADISAA). Multi-objective of waveform design such as transmit beampattern match, good correlation, spectrum notch can be controlled by the adjustable weights. Finally, the constant modulus signal is designed. Simulation results show: the proposed algorithm improves the correlation performance of waveform at a specified lag intervals after transmit beampattern matching, the spectrum notch is designed to avoid the spectrum band which is polluted by active jamming and color noise, and it has lower computational complexity.
- MIMO radar /
- Waveform design /
- Transmit beampattern match /
- Correlation performance

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参考文献(19)

Daum F and Huang J. MIMO radar: snake oil or good idea? [J]. IEEE Aerospace and Electronic Systems Magazine, 2009, 24(5): 8-12.

Li Jian and Stoica P. MIMO radar with colocated antennas [J]. IEEE Signal Processing Magazine, 2007, 24(5): 106-114.

Li Jian, Stoica P, and Zheng Xia-yu. Signal synthesis and receiver design for MIMO radar imaging[J]. IEEE Transactions on Signal Processing, 2008, 56(8): 3959-3968.

Fuhrmann D R and San Antonio G S. Transmit beamforming for MIMO radar systems using signal cross-correlation[J]. IEEE Transactions on Aerospace and Electronic Systems, 2008, 44(1): 171-186.

汤永浩, 马晓峰, 盛卫星, 等. 集中式MIMO雷达部分相关波形设计与处理[J]. 电子与信息学报, 2013, 35(6): 1471-1476.

Tang Yong-hao, Ma Xiao-feng, Sheng Wei-xing, et al.. Partially correlation waveform design and processing for co-located MIMO radar[J]. Journal of Electronics Information Technology, 2013, 35(6): 1471-1476.

He Hao, Stoica P, and Li Jian. Designing unimodular sequences sets with good correlations-including and application to MIMO radar[J]. IEEE Transactions on Signal Processing, 2009, 57(11): 4391-4405.

Fuhrmann D and Antonio S G. Transmit beamforming for MIMO radar systems using partial signal correlation[C]. Proceedings of the 38th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, USA, 2004: 295-299.

Li Jian and Stoica P. On probing signal design for MIMO radar[J]. IEEE Transactions on Signal Processing, 2007, 55(8): 4151-4161.

He Hao, Li Jian, and Stoica P. Waveform Design for Active Sensing Systems[M]. New York: Cambridge University Press, 2012: 214-221.

Xu Lu-zhou, Li Jian, and Stoica P. Target detection and parameter estimation for MIMO radar systems[J]. IEEE Transactions on Aerospace and Electronic Systems, 2008, 44(3): 927-939.

Sibui L H and Titlebaum E L. Signal design for detection of targets in clutter[J]. Proceedings of the IEEE, 1981, 69(4): 481-482.

He Hao, Stoica P, and Li Jian. Waveform design with stopband and correlation constraints for cognitive radar[C]. Proceedings of the IEEE International Workshop on the Cognitive, Information Proceseing(CIP), Elba, USA, 2010: 344-349

Zhao Yi-nan, Li Feng-cong, and Zhang Tao. Computational design of optimal waveforms for MIMO radar via multi-dimensional iterative spectral approximation[J]. Multidimensional Systems and Signal Processing, 2014, 46(22): 1456-1473.

赵宜楠, 张涛, 李风从, 等. 基于交替投影的MIMO雷达最优波形设计[J]. 电子与信息学报, 2014, 36(6): 1368-1373.

Zhao Yi-nan, Zhang Tao, Li Feng-cong, et al.. Optimal waveform design for MIMO radar via alternating projection[J]. Journal of Electronics Information Technology, 2014, 36(6): 1368-1373.

Cui Guo-long, Li Hong-bin, and Rangaswamy Muralidhar. MIMO radar waveform design with constant modulus and similarity constraints[J]. IEEE Transactions on Signal Processing, 2014, 62(2): 343-353.

胡亮兵, 刘宏伟, 杨晓超. 集中式MIMO雷达发射方向图快速设计方法[J]. 电子与信息学报, 2010, 32(2): 481-484.

Hu Liang-bing, Liu Hong-wei, and Yang Xiao-chao. Fast transmit beampattern synthesis for MIMO radar with colocated antennas[J]. Journal of Electronics Information Technology, 2010, 32(2): 481-484.

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