低信噪比下非冗余阵列的无网格DOA估计

doi:10.12305/j.issn.1001-506X.2023.02.04

Abstract

Abstract:

Direction of arrival (DOA) is a nonlinear parameter in the array signal processing model, and its estimation deviates from the true value when the signal-to-noise ratio is low. In order to lower the threshold of this problem in gridless DOA estimation method, a method based on gridless sparse iterative covariance-based estimation (SPICE) is introduced. A maximum likelihood root multiple signal classification (ML-Root-MUSIC) is introduced to calculate DOA, which uses ML criterion to select roots and can lower the threshold and get better resolution characteristic. A negative entropy term is added to the optimization problem in the original gridless SPICE, so that the root mean square error curve of gridless SPICE is closer to Cramer-Rao lower bound in large-snapshot case. Finally, Monte Carlo simulation experiments verify that the proposed method is better than the competing methods for non-redundant arrays at low signal-to-noise ratio.

Key words: direction of arrival (DOA) estimation, non-redundant array, low signal to noise ratio (SNR), gridless

CLC Number:

TN911.72

Ning WANG, Xiaode LYU, Miaomiao LI. Gridless DOA estimation for non-redundant array at low SNR[J]. Systems Engineering and Electronics, 2023, 45(2): 352-359.

Figures/Tables 5

References 30

1	TREES H L V . Optimum array processing: part Ⅳ of detection, estimation, and modulation theory[M]. New York: Wiley, 2002.
2	WANG Y , ZHANG Y , TIAN Z , et al. Super-resolution channel estimation for arbitrary arrays in hybrid millimeter-wave massive MIMO systems[J]. IEEE Journal of Selected Topics in Signal Processing, 2019, 13 (5): 947- 960. doi: 10.1109/JSTSP.2019.2937632
3	WANG M J , GAO F F , JIN S , et al. An overview of enhanced massive MIMO with array signal processing techniques[J]. IEEE Journal of Selected Topics in Signal Processing, 2019, 13 (5): 886- 901. doi: 10.1109/JSTSP.2019.2934931
4	STOICA P , BABU P , LI J . SPICE: a sparse covariance-based estimation method for array processing[J]. IEEE Trans.on Signal Processing, 2011, 59 (2): 629- 638. doi: 10.1109/TSP.2010.2090525
5	KAY S M . Fundamentals of statistical signal processing[M]. Englewood Cliffs: Prentice-Hall, 1993.
6	STOICA P , MOSES R L . Spectral analysis of signals[M]. Upper Saddle River: Pearson/Prentice-Hall, 2005.
7	YANG Z, LI J, STOICA P, et al. Sparse methods for direction-of-arrival estimation[M]//CHELLAPPA R, THEODORIDIS S. Academic Press Library in Signal Processing, Volume 7: Array, Radar and Communications Engineering. Oxford: Academic Press, 2018.
8	BELLONI A , CHERNOZHUKOV V , WANG L . Square-root lasso: pivotal recovery of sparse signals via conic programming[J]. Bio-metrika, 2011, 98 (4): 791- 806.
9	TAN T , ROBERTS W , LI J , et al. Sparse learning via iterative minimization with application to MIMO radar imaging[J]. IEEE Trans.on Signal Processing, 2011, 59 (3): 1088- 1101. doi: 10.1109/TSP.2010.2096218
10	JI S H , XUE Y , CARIN L . Bayesian compressive sensing[J]. IEEE Trans.on Signal Processing, 2008, 56 (6): 2346- 2356. doi: 10.1109/TSP.2007.914345
11	STOICA P , BABU P , LI J . New method of sparse parameter estimation in separable models and its use for spectral analysis of irregularly sampled data[J]. IEEE Trans.on Signal Processing, 2011, 59 (1): 35- 47. doi: 10.1109/TSP.2010.2086452
12	ZHANG Q , ABEIDA H , XUE M , et al. Fast implementation of sparse iterative covariance-based estimation for source localization[J]. The Journal of the Acoustical Society of America, 2012, 131 (2): 1249- 1259. doi: 10.1121/1.3672656
13	STOICA P , ZACHARIAH D , LI J . Weighted SPICE: a uni-fying approach for hyperparameter-free sparse estimation[J]. Digital Signal Processing, 2014, 33, 1- 12. doi: 10.1016/j.dsp.2014.06.010
14	ZHU H , LEUS G , GIANNAKIS G . Sparsity-cognizant total least-squares for perturbed compressive sampling[J]. IEEE Trans.on Signal Processing, 2011, 59 (5): 2002- 2016. doi: 10.1109/TSP.2011.2109956
15	YANG Z , XIE L H , ZHANG C S . Off-grid direction of arrival estimation using sparse Bayesian inference[J]. IEEE Trans.on Signal Processing, 2013, 61 (1): 38- 43. doi: 10.1109/TSP.2012.2222378
16	WANG Q L , ZHAO Z Q , CHEN Z , et al. Grid evolution method for DOA estimation[J]. IEEE Trans.on Signal Processing, 2018, 66 (9): 2374- 2383. doi: 10.1109/TSP.2018.2814998
17	MA Y N , CAO X B , WANG X R , et al. Multi-source off-grid DOA estimation with single snapshot using non-uniform linear arrays[J]. Signal Processing, 2021, 189, 108- 238.
18	YANG Z , XIE L H . Enhancing sparsity and resolution via reweighted atomic norm minimization[J]. IEEE Trans.on Signal Processing, 2016, 64 (4): 995- 1006. doi: 10.1109/TSP.2015.2493987
19	WAGNER M, GERSTOFT P, PARK Y. Gridless DOA estimation via alternating projections[C]//Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing, 2019: 4215-4219.
20	MAHATA K , HYDER M M . Frequency estimation from arbitrary time samples[J]. IEEE Trans.on Signal Processing, 2016, 64 (21): 5634- 5643. doi: 10.1109/TSP.2016.2600507
21	WAGNER M , PARK Y , GERSTOFT P . Gridless DOA estimation and Root-MUSIC for non-uniform linear arrays[J]. IEEE Trans.on Signal Processing, 2021, 69, 2144- 2157. doi: 10.1109/TSP.2021.3068353
22	YANG Z , XIE L H , ZHANG C S . A discretization-free sparse and parametric approach for linear array signal processing[J]. IEEE Trans.on Signal Processing, 2014, 62 (19): 4959- 4973. doi: 10.1109/TSP.2014.2339792
23	YANG Z , XIE L H . On gridless sparse methods for line spectral estimation from complete and incomplete data[J]. IEEE Trans.on Signal Processing, 2015, 63 (12): 3139- 3153. doi: 10.1109/TSP.2015.2420541
24	CHEN T , SHI L , YU Y Z . Gridless DOA estimation with finite rate of innovation reconstruction based on symmetric Toe-plitz covariance matrix[J]. EURASIP Journal on Advances in Signal Processing, 2020, 2020 (1): 44- 59. doi: 10.1186/s13634-020-00701-7
25	ABRAMOVICH Y I , SPENCER N K , GOROKHOV A Y . Positive-definite toeplitz completion in DOA estimation for nonuniform linear antenna arrays. Ⅱ. partially augmentable arrays[J]. IEEE Trans.on Signal Processing, 1999, 47 (6): 1502- 1521. doi: 10.1109/78.765119
26	BOYD S , VANDENBERGHE L . Convex optimization[M]. Cambridge: Cambridge University Press, 2004.
27	GRANT M, BOYD S. CVX: Matlab software for disciplined convex programming, Version 2.0[EB/OL]. [2022-02-24]. http://cvxr.com/cvx.
28	COVER T M , THOMAS J A . Elements of information theory[M]. Hoboken: Wiley, 2006.
29	ADALI T , SCHREIER P J , SCHARF L L . Complex-valued signal processing: the proper way to deal with impropriety[J]. IEEE Trans.on Signal Processing, 2011, 59 (11): 5101- 5125. doi: 10.1109/TSP.2011.2162954
30	ADALI T , HAYKIN S . Adaptive signal processing: next gene-ration solutions[M]. Hoboken: Wiley, 2010.

[1]	Xuecheng ZHAO, Xiangdong HUANG, Jinying MA. Joint carrier frequency and DOA estimation for multiple target sourcesusing L-shaped unfolded co-prime array [J]. Systems Engineering and Electronics, 2023, 45(2): 336-342.
[2]	Geng WANG, Hao LI, Yi HE, Mingyue FENG, Changxiao CHEN. Underdetermined DOA estimation of optimal redundancy array via double reconstruction [J]. Systems Engineering and Electronics, 2023, 45(1): 49-55.
[3]	Jialei LIU, Jiazhi MA, Longfei SHI. DOA estimation algorithm based on fourth-order cumulant using virtual beam forming [J]. Systems Engineering and Electronics, 2022, 44(7): 2134-2142.
[4]	Zhiyu QU, Meng SUN, Huanyao DAI. Joint estimation algorithm of DOA and polarization information based on conformal array [J]. Systems Engineering and Electronics, 2022, 44(6): 1798-1804.
[5]	Juan WEI, Shian YAN, Fangli NING. DOA estimation method for coherent signals based on coprime array virtual array spatial smoothing [J]. Systems Engineering and Electronics, 2022, 44(4): 1069-1077.
[6]	Baohua FAN, Le ZUO, Yong TANG, Zehua HU. DOA estimation of multiple time-varying signals with expectation-maximization algorithm [J]. Systems Engineering and Electronics, 2022, 44(2): 420-426.
[7]	Tao CHEN, Lin SHI, Mengyu SHEN. Gridless DOA estimation algorithm based on M-FIPM [J]. Systems Engineering and Electronics, 2022, 44(2): 427-433.
[8]	Yili HU, Yongbo ZHAO, Sheng CHEN, Chenghu CAO. Blind polarization DOA estimation of parabolic conformal array based on interpolation fitting [J]. Systems Engineering and Electronics, 2021, 43(8): 2037-2044.
[9]	Junpeng SHI, Fangqing WEN, Lin AI, Gong ZHANG, Zhenghui GONG. Angle estimation for bistatic MIMO radar with spatially colored noise [J]. Systems Engineering and Electronics, 2021, 43(6): 1477-1485.
[10]	Zixin ZHANG, Guoping HU, Hao ZHOU, Chenghong ZHAN. Low elevation angle estimation algorithm for MIMO radar based on sparse reconstruction of cross-covariance [J]. Systems Engineering and Electronics, 2021, 43(5): 1218-1223.
[11]	Silei CAO, Weigui ZENG, Huiqi XU. Broadband DOA estimation method based on eigenvector space focusing [J]. Systems Engineering and Electronics, 2021, 43(2): 294-299.
[12]	Yule ZHANG, Guoping HU, Hao ZHOU, Shijie YUE, Feilong ZHAO. DOA estimation of generalized two-level nested MIMO radar with high degree of freedom and low mutual coupling [J]. Systems Engineering and Electronics, 2021, 43(10): 2819-2827.
[13]	Xiaoqiang LI, Jianfeng CHEN, Weijie TAN, Yang WEN, Rongrong ZHANG. Gridless DOA estimation method for monostatic MIMO array based on covariance matrix reconstruction [J]. Systems Engineering and Electronics, 2020, 42(5): 969-977.
[14]	Shanhong HE, Mengqian JI, Liangyu XIE, Jin FAN. Two-dimensional DOA estimation for multi-beam reflector antenna based on focal-plane field [J]. Systems Engineering and Electronics, 2020, 42(1): 23-29.
[15]	TAN Weijie, FENG Xi’an. Sparsity-based two dimensional direction-finding method for parallel co-prime arrays [J]. Systems Engineering and Electronics, 2019, 41(5): 937-943.

Gridless DOA estimation for non-redundant array at low SNR

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 5

References 30

Related Articles 15

Recommended Articles

Metrics

Comments