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A novel resampling algorithm based on the knapsack problem
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DOI：10.1016/j.sigpro.2019.107436.png)
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Abstract
En 中文
The problem of accurate tracking of targets is important both in military and civilian applications. There are different approaches to precise tracking of targets. Particle filters have been used frequently for this purpose in recent years. Different resampling algorithms have been proposed to reduce the estimation error in the particle filters. In this study, a new resampling algorithm is proposed by solving the knapsack problem. We compare the performance of the proposed algorithm with that of other resampling algorithms for target tracking problems. Simulation results show that the proposed algorithm has a better performance under various conditions such as the small number of particles, measurement noise levels and different target motion models. (C) 2019 Elsevier B.V. All rights reserved.
Keywords:
Target tracking
Particle filters
Resampling
Knapsack problem
Dynamic programming
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