Target tracking in clutter using a high pulse repetition frequency radar

We investigate two solutions for single target tracking in clutter using a high pulse repetition frequency (HPRF) radar. With the HPRF radar, each ambiguous range measurement corresponds to a set of unambiguous range measurements. Both algorithms enable false track discrimination (FTD) using the probability of target existence. One approach adapts the Gaussian mixture measurement likelihood-integrated track splitting to the problem, where each measurement likelihood is approximated by a Gaussian mixture. The other approach is an integration of previously published multiple models approach with the probability of target existence paradigm. Here each model is a separate probabilistic data association filter. In both cases the track trajectory probability density function is a Gaussian mixture.