Robust Sidelobe Suppression Method for Cognitive Radar Based on Sequential Optimization

Songpo JIN; Shanna ZHUANG

doi:10.11999/JEIT181091

Volume 41 Issue 9

Sep. 2019

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2019 > 41(9): 2131-2136

Songpo JIN, Shanna ZHUANG. Robust Sidelobe Suppression Method for Cognitive Radar Based on Sequential Optimization[J]. Journal of Electronics & Information Technology, 2019, 41(9): 2131-2136. doi: 10.11999/JEIT181091

Citation:

Songpo JIN, Shanna ZHUANG. Robust Sidelobe Suppression Method for Cognitive Radar Based on Sequential Optimization[J]. Journal of Electronics & Information Technology, 2019, 41(9): 2131-2136. doi: 10.11999/JEIT181091

Citation:

PDF( 1255 KB)

Robust Sidelobe Suppression Method for Cognitive Radar Based on Sequential Optimization

doi: 10.11999/JEIT181091

Songpo JIN^{1
,
,},
Shanna ZHUANG²

1.
The 54th Research Institute of CETC, Shijiazhuang 050081, China
2.
School of Information Science and Technology, Shijiazhuang Tiedao University, Shijiazhuang 050043, China

Received Date: 2018-11-26
Rev Recd Date: 2019-04-11

Available Online: 2019-04-25

Publish Date: 2019-09-10

Abstract

Abstract

Range sidelobes may lead to weak targets masked by strong targets and false alarm. This paper proposes a sequential optimization method for the sidelobe suppression of cognitive radar. First, the region to detect is divided according to range cell. Second, the transmit waveform and receive filter are optimized jointly based on the principle of minimum mean square error against one range cell. The optimized transmit and receive systems are used in Radar Cross Section (RCS) estimation for the scatter in the current range cell. The above process is carried out in each range cell in the scene sequentially. The acquired RCS estimate is used in the sidelobe suprresion for the following range cells. The RCS estimation for all the range cells in the scene is obtained in a bootstrapping way successively and updated circularly. The proposed method forms a closed loop detection system. The transmitting and receiving systems are adjusted according to the feedback scene information in real time. The sensing ability about the environment can be enhanced. The detection performance and robustness against noise can be improved. The efficiency and validity are verified by the simulation results.
- Cognitive radar,
- Sidelobe suppression,
- Robust,
- Sequential optimization

FullText(HTML)

References(19)

References

CUI Guolong, YU Xianxiang, YANG Ya, et al. Cognitive phase-only sequence design with desired correlation and stopband properties[J]. IEEE Transactions on Aerospace and Electronic Systems, 2017, 53(6): 2924–2935. doi: 10.1109/TAES.2017.2721238

DENG Hai. Effective CLEAN algorithms for performance-enhanced detection of binary coding radar signals[J]. IEEE Transactions on Signal Processing, 2004, 52(1): 72–78. doi: 10.1109/TSP.2003.820075

BLUNT S D and GERLACH K. Adaptive pulse compression via MMSE estimation[J]. IEEE Transactions on Aerospace and Electronic Systems, 2006, 42(2): 572–584. doi: 10.1109/TAES.2006.1642573

李秀友, 董云龙, 黄勇, 等. 基于迭代线性约束最小方差的稳健自适应脉冲压缩方法[J]. 电子与信息学报, 2015, 37(10): 2300–2306. doi: 10.11999/JEIT141631

LI Xiuyou, DONG Yunlong, HUANG Yong, et al. Robust adaptive pulse compression algorithm based on reiterative linearly constrained minimum variance[J]. Journal of Electronics &Information Technology, 2015, 37(10): 2300–2306. doi: 10.11999/JEIT141631

XU Xiaojian and NARAYANAN R M. Range sidelobe suppression technique for coherent ultra wide-band random noise radar imaging[J]. IEEE Transactions on Antennas and Propagation, 2001, 49(12): 1836–1842. doi: 10.1109/8.982467

HE Hao, LI Jian, and STOICA P. Waveform Design for Active Sensing Systems: A Computational Approach[M]. Cambridge, New York, USA: Cambridge University Press, 2012: 29–65.

李风从, 赵宜楠, 乔晓林. 抑制特定区间距离旁瓣的恒模波形设计方法[J]. 电子与信息学报, 2013, 35(3): 532–536. doi: 10.3724/SP.J.1146.2012.00857

LI Fengcong, ZHAO Yinan, and QIAO Xiaolin. Constant modular waveform design method for suppressing range sidelobes in specified intervals[J]. Journal of Electronics &Information Technology, 2013, 35(3): 532–536. doi: 10.3724/SP.J.1146.2012.00857

HAYKIN S. Cognitive radar: A way of the future[J]. IEEE Signal Processing Magazine, 2006, 23(1): 30–40. doi: 10.1109/MSP.2006.1593335

GUI Ronghua, WANG Wenqin, PAN Ye, et al. Cognitive target tracking via angle-range-Doppler estimation with transmit subaperturing FDA radar[J]. IEEE Journal of Selected Topics in Signal Processing, 2018, 12(1): 76–89. doi: 10.1109/JSTSP.2018.2793761

邹鲲, 骆艳卜, 李伟, 等. 频谱拥挤环境中峰均功率比约束的认知雷达发射波形设计[J]. 电子与信息学报, 2018, 40(7): 1774–1778. doi: 10.11999/JEIT170834

ZOU Kun, LUO Yanbo, LI Wei, et al. Cognitive radar waveform design with a peak to average power ration constraint for spectrally dense environments[J]. Journal of Electronics &Information Technology, 2018, 40(7): 1774–1778. doi: 10.11999/JEIT170834

CHEN Peng and WU Lenan. Waveform design for multiple extended targets in temporally correlated cognitive radar system[J]. IET Radar, Sonar & Navigation, 2016, 10(2): 398–410. doi: 10.1049/iet-rsn.2015.0295

GUIMARÃES D A and LIM C H. Sliding-window-based detection for spectrum sensing in radar bands[J]. IEEE Communications Letters, 2018, 22(7): 1418–1421. doi: 10.1109/LCOMM.2018.2834932

SHARAGA N, TABRIKIAN J, and MESSER H. Optimal cognitive beamforming for target tracking in MIMO radar/sonar[J]. IEEE Journal of Selected Topics in Signal Processing, 2015, 9(8): 1440–1450. doi: 10.1109/JSTSP.2015.2467354

郝天铎, 周青松, 孙从易, 等. 非准确先验知识下认知雷达低峰均比稳健波形设计[J]. 电子与信息学报, 2018, 40(3): 532–540. doi: 10.11999/JEIT170560

HAO Tianduo, ZHOU Qingsong, SUN Congyi, et al. Low-PAR robust waveform design for cognitive radar with imprecise prior knowledge[J]. Journal of Electronics &Information Technology, 2018, 40(3): 532–540. doi: 10.11999/JEIT170560

XIONG Jie, WANG Wenqin, CUI Can, et al. Cognitive FDA-MIMO radar for LPI transmit beamforming[J]. IET Radar, Sonar & Navigation, 2017, 11(10): 1574–1580. doi: 10.1049/iet-rsn.2016.0551

GARREN D A, OSBORN M K, ODOM A C, et al. Enhanced target detection and identification via optimised radar transmission pulse shape[J]. IEE Proceedings - Radar, Sonar and Navigation, 2001, 148(3): 130–138. doi: 10.1049/ip-rsn:20010324

ZHANG X and CUI Can. Signal detection for cognitive radar[J]. Electronics Letters, 2013, 49(8): 559–560. doi: 10.1049/el.2012.3345

冯翔, 陈志坤, 赵宜楠, 等. 基于联合优化松弛交替投影的组网雷达恒模波形设计[J]. 电子与信息学报, 2016, 38(7): 1745–1751. doi: 10.11999/JEIT151152

FENG Xiang, CHEN Zhikun, ZHAO Yinan, et al. Unimodular waveforms design for netted radar system via joint optimization relaxed alternating projection[J]. Journal of Electronics &Information Technology, 2016, 38(7): 1745–1751. doi: 10.11999/JEIT151152

ZHUANG Shanna, WANG Zhengyou, and WANG Hui. Waveform optimization to improve MIMO radar range-angle imaging performance[C]. 2015 IEEE Radar Conference, Arlington, USA, 2015: 56–61. doi: 10.1109/RADAR.2015.7130970.

Relative Articles

Supplements(0)

Cited By

Proportional views