Multi-target tracking for multistatic sonobuoy systems

We describe a technique for detection and tracking of multiple targets using a multistatic sonobuoy array. The innovation in the proposed algorithm is the use of a clustering step, posed as Bayesian mixture estimation, to produce Cartesian position measurements. These are passed to a sequential Monte Carlo approximation of the multiple hypothesis tracker. The improvement offered by the proposed algorithm compared to an existing algorithm is demonstrated in a simulation analysis.