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Auxiliary particle Bernoulli filter for target tracking

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  • Control Theory and Applications
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Abstract

Target tracking is a popular topic in various surveillance systems. As a data association free method, the Bernoulli filter can directly estimate target state from plenty of uncertain measurements. However, it is not obvious for existing Bernoulli filters to select proposal distribution with small variance of weights. To address this problem, a novel auxiliary particle (AP) Bernoulli filter and its implementation are proposed in this paper. We employ the AP method in the Bernoulli filtering framework in order to choose robust particles from a discrete distribution defined by an additional set of weights, which reflect the ability to represent measurements with high probability. Limitation to the number of particles, the promising particles are used to propagate by extracting indices. On the other hand, the particles without significant contribution to approximation are discarded. In such case, the computational complexity of this filter is reduced. With the unscented transform (UT), the dynamics of maneuvering target are effectively estimated. The simulation results show advantages in comparison to the standard Bernoulli filter for general target tracking.

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Authors and Affiliations

  1. School of Electronics and Information Engineering, Liaoning University of Technology, No. 169, Shiying Street, Guta District, Jinzhou, 121001, China

    Bo Li & Jianli Zhao

Authors
  1. Bo Li
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  2. Jianli Zhao
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Corresponding author

Correspondence to Bo Li.

Additional information

Recommended by Associate Editor Young Soo Suh under the direction of Editor Duk-Sun Shim. This journal was supported by the National Natural Science Foundation of China (No. 51679116), the Doctoral Scientific Research Foundation Guidance Project of Liaoning Province (No. 201601343), and the Scientific Research Project of Education Department of Liaoning Province (No. L2015230).

Bo Li received the B.S. and Ph.D degrees in Communication and Information System from Liaoning University of Technology and Dalian Maritime University, China, in 2005 and 2015, respectively. He is an associate professor in Liaoning University of Technology, China. His research interests include information fusion, state estimate, target tracking, and digital signal processing.

Jianli Zhao is currently a B.S. candidate in Communication and Information System from Liaoning University of Technology, China. His research interests include target tracking, and state estimate, information fusion.

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Li, B., Zhao, J. Auxiliary particle Bernoulli filter for target tracking. Int. J. Control Autom. Syst. 15, 1249–1258 (2017). https://doi.org/10.1007/s12555-016-0010-1

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  • DOI: https://doi.org/10.1007/s12555-016-0010-1

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