Bayesian filtering for tracking pose and location of rigid targets

Tracking of target pose is important for ATR in situations where there is a relative motion between the targets and the sensor(s). Taking a Bayesian approach, we formulate the problem of jointly tracking the target positions and orientations las elements of SE(3)) as a problem in nonlinear filtering. Combining pertinent ideas from importance sampling and sequential methods, we apply an iterative Monte Carlo approach to solve for MMSE solutions. This tracking algorithm is demonstrated for tracking individual targets in a simulated environment.