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Sensors 2017, 17(7), 1688; https://doi.org/10.3390/s17071688

Double-Layer Compressive Sensing Based Efficient DOA Estimation in WSAN with Block Data Loss

1
State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China
2
Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
*
Author to whom correspondence should be addressed.
Received: 20 June 2017 / Revised: 14 July 2017 / Accepted: 18 July 2017 / Published: 22 July 2017
(This article belongs to the Section Sensor Networks)

Abstract

Accurate information acquisition is of vital importance for wireless sensor array network (WSAN) direction of arrival (DOA) estimation. However, due to the lossy nature of low-power wireless links, data loss, especially block data loss induced by adopting a large packet size, has a catastrophic effect on DOA estimation performance in WSAN. In this paper, we propose a double-layer compressive sensing (CS) framework to eliminate the hazards of block data loss, to achieve high accuracy and efficient DOA estimation. In addition to modeling the random packet loss during transmission as a passive CS process, an active CS procedure is introduced at each array sensor to further enhance the robustness of transmission. Furthermore, to avoid the error propagation from signal recovery to DOA estimation in conventional methods, we propose a direct DOA estimation technique under the double-layer CS framework. Leveraging a joint frequency and spatial domain sparse representation of the sensor array data, the fusion center (FC) can directly obtain the DOA estimation results according to the received data packets, skipping the phase of signal recovery. Extensive simulations demonstrate that the double-layer CS framework can eliminate the adverse effects induced by block data loss and yield a superior DOA estimation performance in WSAN. View Full-Text
Keywords: double-layer compressive sensing; direction of arrival; block data loss; packet size; joint sparse representation double-layer compressive sensing; direction of arrival; block data loss; packet size; joint sparse representation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Sun, P.; Wu, L.; Yu, K.; Shao, H.; Wang, Z. Double-Layer Compressive Sensing Based Efficient DOA Estimation in WSAN with Block Data Loss. Sensors 2017, 17, 1688.

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