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Sensors 2007, 7(1), 144-156; doi:10.3390/s7010144

An Improved Particle Filter for Target Tracking in Sensor Systems

* ,
State Key Laboratory of Precision Measurement Technology and Instrument, Tsinghua University, Beijing 100084, P. R. China
* Author to whom correspondence should be addressed.
Received: 23 December 2006 / Accepted: 27 January 2007 / Published: 29 January 2007
(This article belongs to the Special Issue Intelligent Sensors)
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Sensor systems are not always equipped with the ability to track targets. Sudden maneuvers of a target can have a great impact on the sensor system, which will increase the miss rate and rate of false target detection. The use of the generic particle filter (PF) algorithm is well known for target tracking, but it can not overcome the degeneracy of particles and cumulation of estimation errors. In this paper, we propose an improved PF algorithm called PF-RBF. This algorithm uses the radial-basis function network (RBFN) in the sampling step for dynamically constructing the process model from observations and updating the value of each particle. With the RBFN sampling step, PF-RBF can give an accurate proposal distribution and maintain the convergence of a sensor system. Simulation results verify that PF-RBF performs better than the Unscented Kalman Filter (UKF), PF and Unscented Particle Filter (UPF) in both robustness and accuracy whether the observation model used for the sensor system is linear or nonlinear. Moreover, the intrinsic property of PF-RBF determines that, when the particle number exceeds a certain amount, the execution time of PF-RBF is less than UPF. This makes PF-RBF a better candidate for the sensor systems which need many particles for target tracking.
Keywords: Particle filter; radial-basis function network; target tracking; sensor system Particle filter; radial-basis function network; target tracking; sensor system
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.

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Wang, X.; Wang, S.; Ma, J.-J. An Improved Particle Filter for Target Tracking in Sensor Systems. Sensors 2007, 7, 144-156.

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