Track fusion by optimal reduced state estimation in multi-sensor environment with limited-bandwidth communication path

Abstract

The invention, called 'ORSE Track Fusion', combines sensor tracks from dispersed sites, when limited communication bandwidth does not permit sharing of individual measurements. Since estimation errors due to maneuver biases are not independent for each sensor, optimal fusion of tracks produced by Kalman filters requires transmission of all the filter gain matrices used to update each sensor track prior to the fusion time. For this reason, prior art has resorted to suboptimal designs. ORSE Track Fusion according to aspects of the invention overcomes this disadvantage by propagating, transmitting, and fusing separately calculated covariance matrices for random and bias estimation errors. Furthermore, with ORSE, each sensor can have its own criteria in forming its track, and track fusion can be performed with different criteria at each processing site. Thus, ORSE Track Fusion has the unique flexibility to optimize track fusion simultaneously for multiple criteria to serve multiple users.