On the Effect of Data Contamination on Track Purity

The work presented here is concerned with performance analysis for data association, in a target tracking environment. Effects of misassociation are considered in a simple (linear) multiscan framework so as to provide closed-form expressions of the probability of correct association. We focus here on the development of explicit approximations of this probability. Via rigorous calculations the effect of dimensioning parameters (number of scans, false measurement positions or densities) is analyzed, for various modelings of the false measurements. Remarkably, it is possible to derive very simple expressions of the probability of correct association which are independent of the scenario kinematic parameters.