Particle state compression scheme for centralized memory-efficient particle filters

In this paper, particle state compression scheme is proposed together with its architecture for centralized implementation of particle filters. In the scheme, state values are processed in original bit-width, stored in a compressed way and recovered before sampling of next iteration. The advantage of the scheme is that particle states memory requirement can be greatly reduced while the trade-off is the deviations between original and recovered states introduced by the process. A case study in Nearly Constant Turn (NCT) scenario shows that while achieving the same level of filtering accuracy, proposed scheme can save up to 49.69% memory overhead for storing particle state values compared to traditional realizations.