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Sensors 2014, 14(4), 7505-7523; doi:10.3390/s140407505

Model Parameter Adaption-Based Multi-Model Algorithm for Extended Object Tracking Using a Random Matrix

1
Department of Automation, Tsinghua University, Beijing 100084, China
2
Navy Armament Academy, Beijing 100036, China
3
National Meteorological Information Center, Beijing 100081, China
*
Author to whom correspondence should be addressed.
Received: 20 January 2014 / Revised: 31 March 2014 / Accepted: 21 April 2014 / Published: 24 April 2014
(This article belongs to the Section Physical Sensors)
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Abstract

Traditional object tracking technology usually regards the target as a point source object. However, this approximation is no longer appropriate for tracking extended objects such as large targets and closely spaced group objects. Bayesian extended object tracking (EOT) using a random symmetrical positive definite (SPD) matrix is a very effective method to jointly estimate the kinematic state and physical extension of the target. The key issue in the application of this random matrix-based EOT approach is to model the physical extension and measurement noise accurately. Model parameter adaptive approaches for both extension dynamic and measurement noise are proposed in this study based on the properties of the SPD matrix to improve the performance of extension estimation. An interacting multi-model algorithm based on model parameter adaptive filter using random matrix is also presented. Simulation results demonstrate the effectiveness of the proposed adaptive approaches and multi-model algorithm. The estimation performance of physical extension is better than the other algorithms, especially when the target maneuvers. The kinematic state estimation error is lower than the others as well. View Full-Text
Keywords: extended object tracking; Bayesian approach; random matrix; interacting multi-model algorithm; model parameter adaption extended object tracking; Bayesian approach; random matrix; interacting multi-model algorithm; model parameter adaption
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Li, B.; Mu, C.; Han, S.; Bai, T. Model Parameter Adaption-Based Multi-Model Algorithm for Extended Object Tracking Using a Random Matrix. Sensors 2014, 14, 7505-7523.

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