基于稀疏采样阵列优化的APG-MUSIC算法

宋虎; 蒋迺倜; 刘溶; 李洪涛

doi:10.11999/JEIT170807

基于稀疏采样阵列优化的APG-MUSIC算法

doi: 10.11999/JEIT170807

2.
(南京理工大学电子工程与光电技术学院南京 210094) ②(中国船舶重工集团公司南京船舶雷达研究所南京 210000)

基金项目:

国家自然科学基金(61401204)，中国博士后科学基金项目(2016M601813)，江苏省科技计划支撑类项目(BY2015004-03)

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出版历程
- 收稿日期: 2017-08-14
- 修回日期: 2018-01-22
- 刊出日期: 2018-06-19

APG-MUSIC Algorithm Based on Sparse Sampling Array Optimization

2.
(School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China)

Funds:

The National Natural Science Foundation of China (61401204), The Postdoctoral Science Foundation (2016M601813), The Science and Technology Project of Jiangsu Province (BY2015004-03)

摘要

摘要: 针对稀疏阵列下2维波达方向(DOA)估计问题，该文提出一种基于稀疏采样阵列优化的加速逼近梯度(APG)算法与多重信号分类(MUSIC)算法相结合的2D-DOA估计方法。首先，建立稀疏阵列下的2D-DOA估计信号模型，并证明其具备低秩特征，满足零空间性质(NSP)。其次，为提高稀疏阵列下矩阵填充方法重构接收信号矩阵性能和以此为基础的2D-DOA估计精度，提出基于遗传算法(GA)的稀疏采样阵列优化方法。最后，将APG和MUSIC算法相结合，在重构完整平面阵列接收信号矩阵的基础上完成2维波达方向估计。计算机仿真结果表明，该方法在保证2维波达方向估计精度前提下，大幅提高阵元利用率，有效降低空间谱平均旁瓣，与常规2D-DOA估计方法相比具有优势。
- 稀疏采样阵列优化 /
- 矩阵填充 /
- 2维波达方向估计 /
- 遗传算法
Abstract: A novel Two Dimension Direction Of Arrive (2D-DOA) estimation method based on sparse sampling array optimization is proposed, which is combined with Accelerated Proximal Gradient (APG) and MUltiple SIgnal Classification (MUSIC). First, a 2D-DOA estimation signal model for sparse array is established, and its low rank feature and Null Space Property (NSP) are analyzed. Then, a sparse sampling array optimization method based on Genetic Algorithm (GA) is studied to enhance the performance of Matrix Completion (MC) and DOA. Finally, APG and MUSIC are employed to reconstruct the received signal matrix and estimate the direction of wave arrived, respectively. Computer simulation results show that the proposed method improves the utilization rate of array and reduces the average side lobe of spatial spectrum effectively, compared with the conventional 2D-DOA methods.
- Sparse sampling array optimization /
- Matrix Completion (MC) /
- Two-Dimension DOA (2D-DOA) /
- Genetic Algorithm (GA)

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参考文献(22)

张光义. 相控阵雷达技术[M]. 北京: 电子工业出版社, 2006: 68-75.

HARRY L and VAN T. Optimum Array Processing [M]. New York: John Wiley Sons, 2002: 870-875.

SKOLINK M. Introduction to Radar Systems [M]. New York: McGraw-Hill Education, 2002: 491-493.

YAO Bobin, ZHANG Weile, and WU Qisheng. Weighted subspace fitting for two-dimension DOA estimation in massive MIMO systems[J]. IEEE Access, 2017, 5: 14020-14027. doi: 10.1109/ACCESS.2017.2731379.

ZHANG Tian, ZHANG Zhe, and WANG Yue. Low- complexity optimization for two-dimensional direction-of- arrival estimation via decoupled atomic norm minimization [C]. IEEE International Conference on Acoustics, Speech and Signal Processing, New Orleans, 2017: 3071-3075. doi: 10.1109/ICASSP.2017.7952721.

WALID M and HASSAN M. A novel approach for 2D-DOA estimation using cross-shaped arrays[C]. IEEE Antennas and Propagation Society International Symposium, San Diego, 2008: 1-4. doi: 10.1109/APS.2008.4619295.

ZHANG Yanhong, LIN Qi, MU Xiaomin, et al. 2-D DOA estimation of wideband LFM signal in fractional fourier domain[C]. First International Conference on Innovative Computing, Information and Control, Beijing, 2006: 6-9. doi: 10.1109/ICICIC.2006.376.

LUCAS C, SYMEON C, and MOEZ D. An efficient online adaptive sampling strategy for matrix completion[C]. IEEE International Conference on Acoustics, Speech and Signal Processing, New Orleans, 2017: 3969-3973. doi: 10.1109/ ICASSP.2017.7952901.

KONSTANTIN U and PIERRE C. Hankel low-rank matrix completion: Performance of the nuclear norm relaxation[J]. IEEE Journal of Selected Topics in Signal Processing, 2016, 10(4): 637-646. doi: 10.1109/JSTSP.2016.2535182.

RUCHI T, BODA M, and KETAN R. Adaptive low-rank matrix completion[J]. IEEE Transactions on Signal Processing, 2017, 65(14): 3603-3616. doi: 10.1109/TSP.2017. 2695450.

SEYED M and ALI M. Array interpolation using covariance matrix completion of minimum-size virtual array[J]. IEEE Signal Processing Letters, 2017, 24(7): 1063-1067. doi: 10.1109/LSP.2017.2708750.

PAL P and VAIDYANATHAN P. A grid-less approach to underdetermined direction of arrival estimation via low rank matrix denoising[J]. IEEE Signal Processing Letters, 2014, 21(6): 737-741. doi: 10.1109/LSP.2014.2314175.

DONOHO D. Compressed sensing[J]. IEEE Transactions on Information Theory, 2006, 52(4): 1289-1306. doi: 10.1109/ TIT.2006.871582.

ZENG Wenhao, LI Hongtao, ZHU Xiaohua, et al. A FPC- ROOT algorithm for 2D-DOA estimation in sparse array[J]. International Journal of Antennas and Propagation, 2016, 2016: 1-6. doi: 10.1155/2016.5951717.

SUN S, WAHEED U, and PETROPULU A. MIMO-MC radar: A mimo radar approach based on matrix completion[J]. IEEE Transactions on Aerospace and Electronic Systems, 2015, 51(3): 1839-1852. doi: 10.1109/TAES.2015.140452.

SUN Shuqiao, and PETROPULU A. On transmit beamforming in MIMO radar with matrix completion[C]. IEEE International Conference on Acoustics, Speech and Signal Processing, Brisbane, 2015: 2774-2778. doi: 10.1109/ ICASSP.2015.7178476.

LI Bo, PETROPULU A, and WADE T. Optimum co-design for Spectrum sharing between matrix completion based MIMO radars and a MIMO communication system[J]. IEEE Transactions on Signal Processing, 2016, 64(17): 4562-4575. doi: 10.1109/TSP.2016.2569479.

ZENG Wenhao, LI Hongtao, ZHU Xiaohua, et al. A 2D adaptive beamforming method in sparse array[J]. International Journal of Electronics and Communications, 2017, 77: 100-104. doi: 10.1016/j.aeue.2017.04.015.

WENG Zhiyuan and WANG Xin. Low-rank matrix completion for array signal processing[C]. IEEE International Conference on Acoustics, Speech and Signal Processing, Kyoto, 2012: 2697-2700. doi: 10.1109/ICASSP.2012.6288473.

TOH K and YUN S. An accelerated proximal gradient algorithm for nuclear norm regularized linear least squares problems[J]. Pacific Journal of Optimization, 2010, 6(3): 615-40.

HU Yao, ZHANG Debing, YE Jieping, et al. Fast and accurate matrix completion via truncated nuclear norm regularization [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(9): 2117-2130. doi: 10.1109/TPAMI.2012.271.

RECHT B, XU Weiyu, and HASSIBI B. Necessary and sufficient conditions for success of the nuclear norm heuristic for rank minimization[C]. IEEE Conference on Decision and Control, Cancun, 2008: 3065-3070. doi: 10.1109/CDC.2008. 4739332.

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