Parallel Implementation of Multiple Model Tracking Algorithms

Multifilter algorithms are usually applied in solving the maneuvering target tracking problem. However, in real applications, processing time may become impractical. Multiprocessors seem to offer the throughput needed for such applications. In this paper, we investigate the performances of Viterbi algorithm and the interacting multiple model algorithm, applied to the tracking problem, when implemented on a general purpose shared-memory and shared-bus MIMD multiprocessor. The computational complexity as well as the speedup and efficiency are examined in detail. It is shown that the computational complexity of the parallel implementation of these algorithms is about the same in both memory space and processing time categories. Efficiency with P processors is about 1 - 1/P for small P and is expected to be relatively high also for large P, especially when many filters and large state and measurement vectors are considered.