We propose a fast labeled multi-Bernoulli (LMB) filter that uses belief propagation for probabilistic data association. The complexity of our filter scales only linearly in the numbers of Bernoulli components and measurements, while the performance is comparable to or better than that of the Gibbs sampler-based LMB filter.
A Fast Labeled Multi-Bernoulli Filter Using Belief Propagation
IEEE Transactions on Aerospace and Electronic Systems ; 56 , 3 ; 2478-2488
2020-06-01
657147 byte
Article (Journal)
Electronic Resource
English