An improved resampling approach for particle filters in tracking

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Date

2017-11-06, 2017-08-01, 2019-03-27

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IEEE

Abstract

Resampling is an essential step in particle filtering (PF) methods in order to avoid degeneracy. Systematic resampling is one of a number of resampling techniques commonly used due to some of its desirable properties such as ease of implementation and low computational complexity. However, it has a tendency of resampling very low weight particles especially when a large number of resampled particles are required which may affect state estimation. In this paper, we propose an improved version of the systematic resampling technique which addresses this problem and demonstrate performance improvement.

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Systematics, Target tracking, Approximation algorithms, Monte Carlo methods, Random number generation, Computational complexity, State-space methods

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