Topographic implementation of particle filters on cellular processor arrays

Particle filters are a state-of-the-art method for the state estimation of non-linear stochastic systems. Recent many-core architectures and cellular processor arrays offer a new paradigm for algorithm development, which provides not only high performance, but also theoretical advances for parallel implementations. We have developed a new variant of the particle filter algorithm, which suits ideally implementation on a cellular processor array. The new algorithm often performs better than the classical one and a significant gain in running time can be achieved, especially when there is a large number of particles to be simulated.

► We introduce a new variant of the particle filter algorithm. ► Our method suits ideally implementation on cellular processor arrays. ► We show the usability of the parallelised method with case studies. ► We reason our method with simulations and with implementation on a cellular chip.