Tracking and data association
Shared-Memory Parallelization of the Data Association Problem in Multitarget Tracking
IEEE Transactions on Parallel and Distributed Systems
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The implementations of the Viterbi algorithm (VA) and the interacting multiple model(IMM) algorithm on a shared-bus and shared-memory multiple-input multiple-data (MIMD) multiprocessor are discussed. 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 for large P, especially when many filters and large state and measurement vectors are considered.