|Auxiliary Particle Bernoulli Filter for Target Tracking
Bo Li* and Jianli Zhao
International Journal of Control, Automation, and Systems, vol. 15, no. 3, pp.1249-1258, 2017
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."
Auxiliary particle, Bernoulli filter, target tracking, weight.
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