The optimal order of processing sensor information in sequential multisensor fusion algorithms

Abstract

We examine the order of sensor processing in the sequential multisensor probabilistic data association (MSPDA) filter for target tracking applications. If two sensors of different qualities are used in the sequential MSPDA filter, the r.m.s. position error is generally smaller when the worse sensor is processed first. This finding regarding the order of sensor processing is supported by simulations of a target tracking system, and by analysis of firstthrough sixth-order target process models using the modified Riccati equation.