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Sensors 2014, 14(6), 10829-10845; doi:10.3390/s140610829

Detection and Tracking of a Moving Target Using SAR Images with the Particle Filter-Based Track-Before-Detect Algorithm

School of Electronic and Information Engineering, Beihang University, Beijing 100191, China
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Received: 15 May 2014 / Revised: 5 June 2014 / Accepted: 12 June 2014 / Published: 19 June 2014
(This article belongs to the Section Remote Sensors)
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Abstract

A novel approach to detecting and tracking a moving target using synthetic aperture radar (SAR) images is proposed in this paper. Achieved with the particle filter (PF) based track-before-detect (TBD) algorithm, the approach is capable of detecting and tracking the low signal-to-noise ratio (SNR) moving target with SAR systems, which the traditional track-after-detect (TAD) approach is inadequate for. By incorporating the signal model of the SAR moving target into the algorithm, the ambiguity in target azimuth position and radial velocity is resolved while tracking, which leads directly to the true estimation. With the sub-area substituted for the whole area to calculate the likelihood ratio and a pertinent choice of the number of particles, the computational efficiency is improved with little loss in the detection and tracking performance. The feasibility of the approach is validated and the performance is evaluated with Monte Carlo trials. It is demonstrated that the proposed approach is capable to detect and track a moving target with SNR as low as 7 dB, and outperforms the traditional TAD approach when the SNR is below 14 dB. View Full-Text
Keywords: particle filter (PF); track-before-detect (TBD); detection; tracking; synthetic aperture radar (SAR) particle filter (PF); track-before-detect (TBD); detection; tracking; synthetic aperture radar (SAR)
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Gao, H.; Li, J. Detection and Tracking of a Moving Target Using SAR Images with the Particle Filter-Based Track-Before-Detect Algorithm. Sensors 2014, 14, 10829-10845.

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