Optimal Measurement Budget Allocation For Particle Filtering
(2020) IEEE International Conference on Image Processing — Location: Abu Dhabi (United Arab Emirates) (25.October.2020)
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- Authors
Aspeel, Antoine 
- Abstract
- Particle filtering is a powerful tool for target tracking. When the budget for observations is restricted, it is necessary to reduce the measurements to a limited amount of samples carefully selected. A discrete stochastic nonlinear dynamical system is studied over a finite time horizon. The problem of selecting the optimal measurement times for particle filtering is formalized as a combinatorial optimization problem. We propose an approximated solution based on the nesting of a genetic algorithm, a Monte Carlo algorithm and a particle filter. Firstly, an example demonstrates that the genetic algorithm outperforms a random trial optimization. Then, the interest of non-regular measurements versus measurements performed at regular time intervals is illustrated and the efficiency of our proposed solution is quantified: better filtering performances are obtained in 87.5% of the cases and on average, the relative improvement is 27.7%.
- Affiliations
Citations
Aspeel, A., Gouverneur, A., Jungers, R., & Macq, B. (2020). Optimal Measurement Budget Allocation For Particle Filtering. IEEE International Conference on Image Processing, Abu Dhabi (United Arab Emirates). https://doi.org/10.1109/ICIP40778.2020.9190702