Two-dimensional DOA Estimation for Low-angle Target Based on ADMM
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摘要: 针对面阵米波(VHF)雷达低仰角目标2维DOA估计问题，该文提出一种基于交替乘子法(ADMM)的快速2维DOA估计算法。该方法首先利用均匀面阵条件下方位、俯仰角无耦合的特性，将2维角度估计问题转化为两个1维角度估计问题，通过方位、俯仰维波束合成实现对目标信息提取；其次根据信号模型建立信号空域超完备表达式，利用ADMM方法完成对方位、俯仰角估计。该方法避免了2维联合估计复杂计算量，复杂度大大降低，且运算过程无需特征分解，进一步提高了运算效率。仿真结果表明了该算法的优越性。Abstract: For the two-dimensional DOA estimation problem of low elevation target of Very High Frequency (VHF) array radar, a fast two-dimensional algorithm based on Alternating Direction Method of Multipliers (ADMM) is proposed. Firstly, the two-dimensional DOA estimation problem is transformed into two one-dimensional DOA problems by using the uncoupled characteristics of azimuth and elevation under uniformed planar array, and the target information is extracted by azimuth and elevation dimensional digital beamforming, and then based on signal mode, the over-complete expression in the signal space domain is established. Finally, the ADMM algorithm is used to estimate azimuth and elevation. ADMM algorithm avoids the complicated calculation of two-dimension joint estimation, reduces greatly the complexity, and the algorithm process does not need the eigenvalue decomposition, which improves further the operation efficiency. Simulation results show the superiority of the algorithm.
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[1] 郑轶松. 米波阵列雷达低仰角测高若干问题研究[D]. [博士论文], 西安电子科技大学, 2017.ZHENG Yisong. Study on some issues of low-angle altitude measurement for VHF array radar[D]. [Ph. D. dissertation], Xidian University, 2017. [2] 朱伟. 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, 2013.ZHU Wei. Study on low-angle altitude measurement in VHF radar[D]. [Ph. D. dissertation], Xidian University, 2013. [3] 刘源. 米波阵列雷达低仰角目标测高方法研究[D]. [博士论文], 西安电子科技大学, 2018.LIU Yuan. Research on some issues of low-angle target height measurement for VHF array radar[D]. [Ph. D. dissertation], Xidian University, 2018. [4] LAVATE T B, KOKATE V K, and SAPKAL A M. Performance analysis of MUSIC and ESPRIT DOA estimation algorithms for adaptive array smart antenna in mobile communication[C]. The 2010 Second International Conference on Computer and Network Technology, Bangkok, Thailand, 2010: 308-311. [5] 蒋驰, 张小飞, 张立岑. 基于级联MUSIC的面阵中的二维DOA估计算法[J]. 系统工程与电子技术, 2016, 38(2): 251–258. doi: 10.3969/j.issn.1001-506X.2016.02.02JIANG Chi, ZHANG Xiaofei, and ZHANG Licen. Two-dimensional DOA estimation algorithm for planar array via successive MUSIC[J]. Systems Engineering and Electronics, 2016, 38(2): 251–258. doi: 10.3969/j.issn.1001-506X.2016.02.02 [6] 董玫, 张守宏, 吴向东, 等. 一种改进的空间平滑算法[J]. 电子与信息学报, 2008, 30(4): 859–862. doi: 10.3724/SP.J.1146.2006.01519DONG Mei, ZHANG Shouhong, WU Xiangdong, et al. An improved spatial smoothing technique[J]. Journal of Electronics &Information Technology, 2008, 30(4): 859–862. doi: 10.3724/SP.J.1146.2006.01519 [7] 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): 2362–2375. doi: 10.1109/JSTARS.2018.2835448 [8] 赵永波, 张守宏. 雷达低角跟踪环境下的最大似然波达方向估计方法[J]. 电子学报, 2004, 32(9): 1520–1523. doi: 10.3321/j.issn:0372-2112.2004.09.028ZHAO Yongbo and ZHANG Shouhong. Maximum likelihood DOA estimation in radar low-angle tracking environment[J]. Acta Electronica Sinica, 2004, 32(9): 1520–1523. doi: 10.3321/j.issn:0372-2112.2004.09.028 [9] LI Cunxu, CHEN Baixiao, ZHENG Yisong, et al. Altitude measurement of low elevation target in complex terrain based on orthogonal matching pursuit[J]. IET Radar, Sonar & Navigation, 2016, 11(5): 745–751. doi: 10.1049/iet-rsn.2016.0468 [10] 刘俊, 刘峥, 刘韵佛. 米波雷达仰角和多径衰减系数联合估计算法[J]. 电子与信息学报, 2011, 33(1): 33–37. doi: 10.3724/SP.J.1146.2010.00251LIU Jun, LIU Zheng, and LIU Yunfo. Elevation angle and multipath fading coefficient joint estimation algorithm in VHF radar[J]. Journal of Electronics &Information Technology, 2011, 33(1): 33–37. doi: 10.3724/SP.J.1146.2010.00251 [11] ZHU Wei and CHEN Baixiao. Novel methods of DOA estimation based on compressed sensing[J]. Multidimensional Systems and Signal Processing, 2015, 26(1): 113–123. doi: 10.1007/s11045-013-0239-2 [12] LIU He, DUAN Shouwu, and SONG Wangqing. Improved ADMM for sparse reconstruction of bearing vibration signal[C]. 2020 Global Reliability and Prognostics and Health Management, Shanghai, China, 2020: 1–5. [13] HRYHORENKO V, KLYUSHIN D, and LYASHKO S. Multiblock ADMM in machine learning[C]. 2019 IEEE International Conference on Advanced Trends in Information Theory, Kyiv, Ukraine, 2019: 461–464. [14] WANG Qianli, ZHAO Zhiqin, and CHEN Zhumi. Fast compressive sensing DOA estimation via ADMM solver[C]. 2017 IEEE International Conference on Information and Automation, Macau, China, 2017: 53–57. [15] LIU Qinghua, SHEN Xinyue, and GU Yuantao. Linearized ADMM for nonconvex nonsmooth optimization with convergence analysis[J]. IEEE Access, 2019, 7: 76131–76144. doi: 10.1109/ACCESS.2019.2914461 [16] 刘红亮, 周生华, 刘宏伟, 等. 一种航迹恒虚警的目标检测跟踪一体化算法[J]. 电子与信息学报, 2016, 38(5): 1072–1078. doi: 10.11999/JEIT150638LIU Hongliang, ZHOU Shenghua, LIU Hongwei, et al. An integrated target detection and tracking algorithm with constant track false alarm rate[J]. Journal of Electronics &Information Technology, 2016, 38(5): 1072–1078. doi: 10.11999/JEIT150638 [17] YANG Junfeng and ZHANG Yin. Alternating direction algorithms for l1-problems in compressive sensing[J]. SIAM Journal on Scientific Computing, 2011, 33(1): 250–278. doi: 10.1137/090777761 [18] HE Bingsheng, TAO Min, and YUAN Xiaoming. Alternating direction method with Gaussian back substitution for separable convex programming[J]. SIAM Journal on Optimization, 2012, 22(2): 313–340. doi: 10.1137/110822347 -
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