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| Citation: | ZHENG Guimei, SONG Yuwei, HU Guoping, et al. Height measurement for meter-wave MIMO radar based on block orthogonal matching pursuit preprocessing[J]. Journal of Radars, 2020, 9(5): 908–915. doi: 10.12000/JR20042
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Height Measurement for Meter-wave MIMO Radar Based on Block Orthogonal Matching Pursuit Preprocessing
DOI: 10.12000/JR20042
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Abstract
Meter-wave radar has good anti-stealth performance. The waveform diversity of Multiple-Input Multiple-Output (MIMO) radar can result in a higher degree of freedom, which makes MIMO radar more advantageous in detection and parameter estimation. Therefore, meter-wave MIMO radar has been widely studied. The radar height measurement is one of the most important research problems of the meter-wave MIMO radar. The maximum likelihood and generalized multiple signal classification algorithms are effective for measuring the radar height. However, they feature heavy computation complexity. In this paper, a preprocessing method based on Block Orthogonal Matching Pursuit (BOMP) is proposed to reduce the computation. First, the received data of MIMO array are sparse-processed, and then, using a mathematical operation, they are transformed into a signal model suitable for the BOMP algorithm; then coarse angle estimation is obtained using a large search grid. The coarse angle estimation is taken as the initial value, and the MIMO radar beam width as the search range. The simulation results show that the proposed algorithm can effectively reduce the computation of the search-type height measurement algorithm. -
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References
[1] KUSCHEL H. VHF/UHF radar. 1. Characteristics[J]. Electronics & Communication Engineering Journal, 2002, 14(2): 61–72.[2] KUSCHEL H. VHF/UHF radar Part 2: Operational aspects and applications[J]. Electronics & Communication Engineering Journal, 2002, 14(3): 101–111.[3] LIU Yuan, LIU Hongwei, XIA Xianggen, et al. Projection techniques for altitude estimation over complex multipath condition-based VHF radar[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 11(7): 2362–2374. doi: 10.1109/JSTARS.2018.2835448[4] 王胜华. 雷达低仰角目标检测与测高关键技术研究[D]. [博士论文], 西安电子科技大学, 2019.WANG Shenghua. Research on key technology of low angle radar target detection and elevation measurement[D]. [Ph. D. dissertation], Xidian University, 2019.[5] 谭俊. 米波雷达低仰角测角中多径效应影响抑制及关键技术研究[D]. [博士论文], 电子科技大学, 2019.TAN Jun. Research on multipath effect suppression and key technologies in low-angle measurement of meter wave radar[D]. [Ph. D. dissertation], University of Electronic Science and Technology of China, 2019.[6] XIANG Houhong, CHEN Baixiao, YANG Minglei, et al. Altitude measurement based on characteristics reversal by deep neural network for VHF radar[J]. IET Radar, Sonar & Navigation, 2019, 13(1): 98–103.[7] 陆鹏程, 吴剑旗. 米波MIMO雷达系统设计的几个问题[J]. 雷达科学与技术, 2017, 15(3): 236–240, 246.LU Pengcheng and WU Jianqi. Some issues on VHF MIMO radar system design[J]. Radar Science and Technology, 2017, 15(3): 236–240, 246.[8] 刘俊, 刘峥, 谢荣, 等. 基于波束空间的米波MIMO雷达角度估计算法[J]. 电子学报, 2011, 39(9): 1961–1966.LIU Jun, LIU Zheng, XIE Rong, et al. Beam-space domain angle estimation algorithm in VHF MIMO radar[J]. Acta Electronica Sinica, 2011, 39(9): 1961–1966.[9] 谢荣, 刘铮, 刘俊. 基于矩阵束的MIMO雷达低仰角快速估计方法[J]. 电子与信息学报, 2011, 33(8): 1833–1838. doi: 10.3724/SP.J.1146.2010.01242XIE Rong, LIU Zheng, and LIU Jun. Fast algorithm for low elevation estimation based on matrix pencil in MIMO radar[J]. Journal of Electronics &Information Technology, 2011, 33(8): 1833–1838. doi: 10.3724/SP.J.1146.2010.01242[10] 刘源, 王洪先, 纠博, 等. 米波MIMO雷达低空目标波达方向估计新方法[J]. 电子与信息学报, 2016, 38(3): 622–628. doi: 10.11999/JEIT150555LIU Yuan, WANG Hongxian, JIU Bo, et al. A new method for DOA estimation for VHF MIMO radar in low-angle tracking environment[J]. Journal of Electronics &Information Technology, 2016, 38(3): 622–628. doi: 10.11999/JEIT150555[11] LIU Yuan, JIU Bo, XIA Xianggen, et al. Height measurement of low-angle target using MIMO radar under multipath interference[J]. IEEE Transactions on Aerospace and Electronic Systems, 2018, 54(2): 808–818. doi: 10.1109/TAES.2017.2767919[12] 吴向东, 赵永波, 张守宏, 等. 一种MIMO雷达低角跟踪环境下的波达方向估计新方法[J]. 西安电子科技大学学报: 自然科学版, 2008, 35(5): 793–798.WU Xiangdong, ZHAO Yongbo, ZHANG Shouhong, et al. New method for DOA estimation for the MIMO radar in low-angle tracking environment[J]. Journal of Xidian University:Natural Science, 2008, 35(5): 793–798.[13] LIU J, LIU Z, and XIE R. Low angle estimation in MIMO radar[J]. Electronics Letters, 2010, 46(23): 1565–1566. doi: 10.1049/el.2010.2579[14] TAN Jun and NIE Zaiping. Polarisation smoothing generalised MUSIC algorithm with PSA monostatic MIMO radar for low angle estimation[J]. Electronics Letters, 2018, 54(8): 527–529. doi: 10.1049/el.2017.4378[15] ELDAR Y C, KUPPINGER P, and BOLCSKEI H. Block-sparse signals: Uncertainty relations and efficient recovery[J]. IEEE Transactions on Signal Processing, 2010, 58(6): 3042–3054. doi: 10.1109/TSP.2010.2044837[16] 王永良, 陈辉, 彭应宁, 等. 空间谱估计理论与算法[M]. 北京: 清华大学出版社, 2004.WANG Yongliang, CHEN Hui, PENG Yingning, et al. Theory and Methods of Spatial Spectrum Estimation[M]. Beijing: Tsinghua University Press, 2004.[17] 刘源. 米波数字阵列雷达低仰角测高方法研究[D]. [博士论文], 西安电子科技大学, 2018.LIU Yuan. Study on low-angle altitude measurement in VHF radar[D]. [Ph. D. dissertation], Xidian University, 2018. -
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- Figure 1. Schematic diagram of height measurement of low elevation target with meter wave MIMO radar under specular reflection model
- Figure 2. Support position estimation results based on BOMP sparse recovery algorithm
- Figure 3. Estimation results of maximum likelihood and generalized MUSIC under whole airspace searching
- Figure 4. 10 independent experiments results based on maximum likelihood after BOMP preprocessing
- Figure 5. 10 independent experiments results based on generalized MUSIC after BOMP preprocessing
- Figure 6. RMSE of angle estimation with maximum likelihood and generalized MUSIC algorithms
- Figure 7. RMSE of height measurement with maximum likelihood and generalized MUSIC algorithms
- Figure 8. Comparison results of run time of preprocessing and non-preprocessing algorithms