Track before detect for radar using stochastic particle flow filters
Fred E. Daum, Jim Huang, Arjang Noushin · 2020
We have invented a new algorithm that is many orders of magnitude faster than the current state of the art for track before detect problems with radar. We use stochastic particle flow filters to solve this problem for difficult radar applications in dense clutter with closely spaced multiple targets. In some of our applications the density of targets is so high that the radar measurements are often unresolved. Particle filters are particularly good for this application for two reasons: the measurement model is highly nonlinear, and the conditional probability density is extremely multimodal.