GA-ML-PDA Based Track Initialization with Passive Multistatic Radar (Poster)

摘要

In order to address the problem of track initialization in the presence of clutter with passive multistatic radar, a genetic algorithm based maximum likelihood probabilistic data association (GA-ML-PDA) algorithm is proposed in this paper. First, the log-likelihood ratio (LLR) function is established from multiframe measurements. Then, the track is initialized by maximizing the LLR function with the genetic algorithm (GA). Last, the extreme value theory (EVT) is used for the track acceptance test. Simulation results verify the effectiveness of the algorithm.