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.