Highest density gates for target tracking

The problem of forming validation regions or gates for new sensor measurements obtained when tracking targets in clutter is considered. Target dynamics and measurement characteristics are modeled with, possible non-Gaussianities or nonlinearities, so that some degree of approximation is usually required in the computation of the filtering densities for the target position and predictive densities for future measurements. Highest density gates (HDGs) are proposed as summaries of the predictive densities. These gates are constructed numerically, via simulation from the filtering density approximation. The algorithm results in gates that are "exact" (up to numerical accuracy) regardless of the approximation used for the filtering density. That is, given an approximation to the filtering density, the gating procedure accounts for all further nonlinearities and non-Gaussianities. Numerical example show that when the predictive density is markedly non-Gaussian, HDGs offer advantages over the more common rectangular and ellipsoidal gates.