APPROVED FOR PUBLIC RELEASE

This paper presents the theory and examples of performance for a new algorithm that initiates tracks using a multiple model Probabilistic Data Association (PDA) filter. The analysis is generalised for the case of multiple non-uniform clutter regions within the measurement data that updates the filter. The algorithm starts multiple parallel PDA filters from a single sensor measurement. Each filter is assigned one of a range of possible target model parameters. To reduce the possibility of clutter measurements forming established tracks, the solution includes a model for a visible target. That is, a target that gives sensor measurements that satisfy one of the target models. Other features included in the algorithm are the selection of a fixed number of nearest measurements and the addition of signal amplitude to the target state vector. The inclusion of signal amplitude is one coordinate that is applicable to the non-uniform clutter model developed in this paper