On decorrelated track-to-track fusion based on Accumulated State Densities

Originally, the Accumulated State Density (ASD) has been proposed to provide an exact solution to the out-of-sequence measurement problem. The posterior probability density function of the joint states accumulated over time was derived for a centralized fusion, in which time delayed data may appear. On the other hand, an exact solution for T2TF has been published as the Distributed Kalman Filter (DKF). However, the DKF is exact only if global knowledge in terms of the measurement models for all sensors are available at a local processor. In a previous publication it was shown that an exact solution for T2TF can also be achieved as a convex combination of local ASDs generated at each node in a distributed sensor system. This method crucially differs from the DKF, in that an exact solution is achieved without each processing platform being required to have knowledge of the global information. The contribution of this paper is a presentation of the Distributed ASD (DASD) filter with a fixed length of the ASD state. This approach prevents the increasing transmission loads of the previous DASD implementation.