A method based on Chinese remainder theorem with all phase DFT for DOA estimation in sparse array

doi:10.21629/JSEE.2020.01.01

Journal of Systems Engineering and Electronics ›› 2020, Vol. 31 ›› Issue (1): 1-11.doi: 10.21629/JSEE.2020.01.01

• • 下一篇

收稿日期:2019-01-21 出版日期:2020-02-20 发布日期:2020-02-25

A method based on Chinese remainder theorem with all phase DFT for DOA estimation in sparse array

Chenghu CAO¹(), Yongbo ZHAO^1,^2,*(), Xiaojiao PANG¹(), Baoqing XU¹(), Sheng CHEN¹()

¹ National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China
² Information Sensing and Understanding, Xidian University, Xi'an 710071, China

Received:2019-01-21 Online:2020-02-20 Published:2020-02-25
Contact: Yongbo ZHAO E-mail:764161366@qq.com;ybzhao@xidian.edu.cn;1964230291@qq.com;835569607@qq.com;842561535@qq.com
About author:CAO Chenghu was born in 1987. He received his M.E. degree in signal processing from Fuzhou University, Fuzhou, China in 2015. He is currently working towards his Ph.D. degree with the Department of Electrical Engineering, Xidian University. His research interests are parameter estimation and multi-target detect and tracking. E-mail: 764161366@qq.com|ZHAO Yongbo was born in 1972. He received his M.E. and Ph.D degrees in electrical engineering from Xidian University, Xi'an, China, in 1997 and 2000, respectively. He is currently a professor with the National Laboratory of Radar Signal Processing, Xidian University. His research interests include adaptive signal processing, array signal processing, MIMO radars, and target tracking. E-mail: ybzhao@xidian.edu.cn|PANG Xiaojiao was born in 1993. She received her B.S. degree from Xidian University, Xi'an, China. She is currently pursuing her Ph.D. degree with Department of Electrical Engineering, Xidian University. Her research interests are space time adaptive processing and compress scene. E-mail: 1964230291@qq.com|XU Baoqing was born in 1992. He received his B.S. degree from Qingdao Technological University, Qingdao, China, in 2014. He is currently pursuing his Ph.D. degree with signal processing in Department of Electrical Engineering, Xidian University. His research interests include parameter estimation and adaptive signal processing. E-mail: 835569607@qq.com|CHEN Sheng was born in 1993. He received his B.E. degree from Xidian University, Xi'an, China, in 2017. Currently he is pursuing his Ph.D. degree in electrical engineering at Xidian University. His current research interests include measure height on Mibo radar. E-mail: 842561535@qq.com
Supported by:
the Fund for Foreign Scholars in University Research and Teaching Programs (the 111 Project)(B18039);This work was supported by the Fund for Foreign Scholars in University Research and Teaching Programs (the 111 Project) (B18039)

摘要/Abstract

Abstract:

This paper takes further insight into the sparse geometry which offers a larger array aperture than uniform linear array (ULA) with the same number of physical sensors. An efficient method based on closed-form robust Chinese remainder theorem (CFRCRT) is presented to estimate the direction of arrival (DOA) from their wrapped phase with permissible errors. The proposed algorithm has significantly less computational complexity than the searching method while maintaining similar estimation precision. Furthermore, we combine all phase discrete Fourier transfer (APDFT) and the CFRCRT algorithm to achieve a considerably high DOA estimation precision. Both the theoretical analysis and simulation results demonstrate that the proposed algorithm has a higher estimation precision as well as lower computation complexity.

Key words: direction of arrival (DOA), wrapped phase, closed-form robust Chinese remainder theorem (CFRCRT), all phase discrete Fourier transfer (APDFT)

. [J]. Journal of Systems Engineering and Electronics, 2020, 31(1): 1-11.

Chenghu CAO, Yongbo ZHAO, Xiaojiao PANG, Baoqing XU, Sheng CHEN. A method based on Chinese remainder theorem with all phase DFT for DOA estimation in sparse array[J]. Journal of Systems Engineering and Electronics, 2020, 31(1): 1-11.

图/表 11

参考文献 35

1	BRUNO S, GUSTAVO F. Performance analysis of the classic and robust Chinese remainder theorems in pulsed Doppler radars. IEEE Trans. on Signal Processing, 2018, 66 (18): 4898- 4903. doi: 10.1109/TSP.2018.2863667
2	XU B Q, ZHAO Y B. Joint transmit-receive B-PARAFAC method for angle estimation in bistatic MIMO radar. Digital Signal Processing, 2019, 92, 54- 61. doi: 10.1016/j.dsp.2019.03.001
3	XU B Q, ZHAO Y B. Transmit beamspace-based DOD and DOA estimation method for bistatic MIMO radar. Signal Processing, 2019, 157, 88- 96. doi: 10.1016/j.sigpro.2018.11.016
4	XU B Q, ZHAO Y B, CHENG Z F, et al. A novel unitary PARAFAC method for DOD and DOA estimation in bistatic MIMO radar. Signal Processing, 2017, 138, 273- 279. doi: 10.1016/j.sigpro.2017.03.016
5	BASIKOLO T, ICHIGE K, ARAI H. Underdetermined DOA estimation in presence of mutual coupling for sparse circular array. Proc. of the IEEE International Symposium on Antennas and Propagation, 2017, 985- 991.
6	VAIDYANATHAN P P, PIYA P. Theory of sparse coprime sensing in multiple dimensions. IEEE Trans. on Signal Processing, 2011, 59 (8): 3592- 3608. doi: 10.1109/TSP.2011.2135348
7	LI S, CHEN H. A novel method of DOA estimation on sparse uniform circular array. Proc. of the International Conference on Radar, 2016, 488- 496.
8	PAL P, VAIDYANATHAN P P. A novel approach to array processing with enhanced degrees of freedom. IEEE Trans. on Signal Processing, 2010, 58 (8): 4167- 4181. doi: 10.1109/TSP.2010.2049264
9	SCHMICT R. Multiple emitter location and signal parameter estimation. IEEE Trans. on Antennas and Propagation, 1986, 34 (3): 276- 280. doi: 10.1109/TAP.1986.1143830
10	STOICA P, NEHORAI A. Music, maximum likelihood, and Cramer-Rao bound. IEEE Trans. on Acoustics, Speech, and Signal Processing, 1989, 37 (5): 720- 741. doi: 10.1109/29.17564
11	ROY R, KAILATH T. ESPRIT estimation of signal parameter via rotational invariance techniques. IEEE Trans. on Acoustics, Speech, and Signal Processing, 1989, 37 (7): 984- 995. doi: 10.1109/29.32276
12	DAI J S, WU Z, TANG Z. Real-valued sparse representation method for the DOA estimation with uniform linear array. Proc. of the 31st Chinese Control Conference, 2012, 25- 27.
13	TANG B, MO L, WU H G. DOA estimation approach using sparse representation for sparse line array. Proc. of the IEEE International Conference on Communication Software and Networks, 2015, 654- 659.
14	LIU H Q, ZHAO L M, LI Y, et al. A sparse-based approach for DOA estimation and array calibration in uniform linear array. IEEE Sensors Journal, 2016, 16 (15): 6018- 6027. doi: 10.1109/JSEN.2016.2577712
15	LI X P, CAO Y H. Robust generalized Chinese-remainder-theorem-based DOA estimation for a coprime array. IEEE Access, 2018, 6, 60361- 60368. doi: 10.1109/ACCESS.2018.2875402
16	WENG Z Y, PETAR M D. A search-free DOA estimation algorithm for coprime arrays. Digital Signal Processing, 2014, 24, 27- 33. doi: 10.1016/j.dsp.2013.10.005
17	YE C C, LIANG H, LIU H F. An effective method for joint estimation of chirp rates, initial frequencies and DOAs of multiple LFM signals with sub-Nyquist spatial-temporal sampling. Proc. of the IEEE International Conference on Signal Processing, Communications and Computing, 2015, 1- 4.
18	QIN G D, MOENESS G, ZHANG Y D. DOA estimation exploiting sparse array motions. IEEE Trans. on Signal Processing, 2019, 67 (11): 3013- 3027. doi: 10.1109/TSP.2019.2911261
19	GUO M R, ZHANG Y D, CEHN T. DOA estimation using compressed sparse array. IEEE Trans. on Signal Processing, 2018, 66 (15): 4133- 4145. doi: 10.1109/TSP.2018.2847645
20	SHEN F F, LIU Y M, ZHAO G H, et al. Sparsity-based off-grid DOA estimation with uniform rectangular arrays. IEEE Sensors Journal, 2018, 18 (8): 3384- 3390. doi: 10.1109/JSEN.2018.2800906
21	CHEN P, CAO Z X, CHEN Z M, et al. Off-grid DOA estimation using sparse Bayesian learning in MIMO radar with unknown mutual coupling. IEEE Trans. on Signal Processing, 2019, 67 (1): 208- 220. doi: 10.1109/TSP.2018.2881663
22	LIU L, WEI P. Joint DOA and frequency estimation with sub-Nyquist sampling in the sparse array system. IEEE Signal Processing Letters, 2018, 25 (9): 1285- 1289. doi: 10.1109/LSP.2018.2848838
23	HE C, CHEN J F, LIANG X L. High-accuracy DOA estimation based on time-modulated array with long and short baselines. IEEE Antennas and Wireless Propagation Letters, 2018, 17 (8): 1391- 1395. doi: 10.1109/LAWP.2018.2846805
24	WANG Z, ZHANG X F, GONG P, et al. DOA estimation for coprime liner arrays: an ambiguity-free method involving full DOFs. IEEE Communitions Letters, 2018, 22 (3): 562- 565. doi: 10.1109/LCOMM.2017.2787698
25	LI Q, SU T, WU K. Accurate DOA estimation for large-scale uniform circular array using a single snapshot. IEEE Communications Letters, 2019, 23 (2): 302- 305.
26	XU L Y, WEN F Q, ZHANG X F. A novel unitary PARAFAC algorithm for joint DOA and frequency estimation. IEEE Communications Letters, 2019, 23 (4): 660- 663. doi: 10.1109/LCOMM.2019.2896593
27	YANG X P, WU X C, LI S, et al. A fast and robust DOA estimation method based on JSVD for co-prime array. IEEE Access, 2018, 6, 41697- 41705. doi: 10.1109/ACCESS.2018.2860680
28	LIU J Z, HOU Z X, WANG C Y. Windowed all-phase DFT modulated in time domain and its application in spectrum analysis. Proc. of the International Conference on Wireless Communications, Networking and Mobile, 2009, 1- 4.
29	LIX W, LIANG H, XIA X G. A robust Chinese remainder theorem with its application in frequency estimation from under-sampled waveforms. IEEE Trans. on Signal Processing, 2009, 57 (11): 4314- 4322. doi: 10.1109/TSP.2009.2025079
30	WANG W J, XIA X G. A closed-form robust Chinese remainder theorem and its performance analysis. IEEE Trans. on Signal Proessing, 2010, 58 (11): 5655- 5666. doi: 10.1109/TSP.2010.2066974
31	PAPI F, KYOVTOROV V, GIULIANI R, et al. Bernoulli filter for track-before-detect using MIMO radar. IEEE Signal Processing Letters, 2014, 21 (9): 1145- 1149. doi: 10.1109/LSP.2014.2325566
32	HABTEMARIAM B K, THARMARASA R, KIRUBARAJAN T. PHD filter based track-before-detect for MIMO radars. Signal Processing, 2012, 92 (1): 667- 678.
33	Li S Q, YI W, WANG B L. Multi-object tracking for generic observation model using labeled random finite sets. IEEE Trans. on Signal Processing, 2018, 66 (2): 368- 383. doi: 10.1109/TSP.2017.2764864
34	FRANCESCO P, VO B N, VO B T. Generalized labeled multi-Bernoulli approximation of multi-object densities. IEEE Trans. on Signal Processing, 2015, 63 (20): 5487- 5497. doi: 10.1109/TSP.2015.2454478
35	VO B N, VO B T, PHAM N T, et al. Joint detection and estimation of multiple objects from image observations. IEEE Trans. on Signal Processing, 2010, 58 (10): 5129- 5141. doi: 10.1109/TSP.2010.2050482

A method based on Chinese remainder theorem with all phase DFT for DOA estimation in sparse array

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