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Sensors 2016, 16(9), 1456; doi:10.3390/s16091456

Target Tracking Using SePDAF under Ambiguous Angles for Distributed Array Radar

1
Beijing Key Laboratory of Embedded Real-time Information Processing Technology, Radar Research Laboratory, School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China
2
Electrical Engineering Department, Columbia University, New York, NY 10027, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Changzhi Li
Received: 31 May 2016 / Revised: 17 August 2016 / Accepted: 2 September 2016 / Published: 9 September 2016
(This article belongs to the Special Issue Non-Contact Sensing)
View Full-Text   |   Download PDF [2059 KB, uploaded 9 September 2016]   |  

Abstract

Distributed array radar can improve radar detection capability and measurement accuracy. However, it will suffer cyclic ambiguity in its angle estimates according to the spatial Nyquist sampling theorem since the large sparse array is undersampling. Consequently, the state estimation accuracy and track validity probability degrades when the ambiguous angles are directly used for target tracking. This paper proposes a second probability data association filter (SePDAF)-based tracking method for distributed array radar. Firstly, the target motion model and radar measurement model is built. Secondly, the fusion result of each radar’s estimation is employed to the extended Kalman filter (EKF) to finish the first filtering. Thirdly, taking this result as prior knowledge, and associating with the array-processed ambiguous angles, the SePDAF is applied to accomplish the second filtering, and then achieving a high accuracy and stable trajectory with relatively low computational complexity. Moreover, the azimuth filtering accuracy will be promoted dramatically and the position filtering accuracy will also improve. Finally, simulations illustrate the effectiveness of the proposed method. View Full-Text
Keywords: distributed array radar; direction-of-arrival (DOA) estimation; ambiguous angles; tracking; probability data association filter (PDAF) distributed array radar; direction-of-arrival (DOA) estimation; ambiguous angles; tracking; probability data association filter (PDAF)
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MDPI and ACS Style

Long, T.; Zhang, H.; Zeng, T.; Chen, X.; Liu, Q.; Zheng, L. Target Tracking Using SePDAF under Ambiguous Angles for Distributed Array Radar. Sensors 2016, 16, 1456.

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