This paper presents an efficient weight sorting based scheme and architecture for distributed particle filters (PFs). Instead of redistributing particles among processing elements (PEs) after the resampling step, the proposed scheme sorts the newly generated weights, along with the corresponding propagated particles, in reverse order of the current partial weight sums (PWSs) of PEs so that the final local weight sums in each PE are as close to each other as possible. Resampling is then performed locally in each PE without the redistribution procedure before the next iteration. The corresponding architecture uses two levels of multiplexers to realize the weight/state sorting operation, and features regular structure, low execution time, high memory efficiency and well scalability.