Multisensor Track-to-Track Fusion for Airborne Surveillance Systems.
Abstract
This report describes a track-to-track fusion algorithm for airborne surveillance systems employing multiple dissimilar sensors (radar, LR, and laser radar). These sensors detect targets and create tracks at different data rates. The algorithm presented performs synchronization by predicting the slower tracks to the update times of the faster tracks. The synchronized tracks are then tested for association to determine whether or not the two tracks originated from the same target. It is shown that the probability distribution of correct track association can be improved if the test statistic for association incorporates cross-covariance between the two tracks. A recursive algorithm for computing the cross-covariance is obtained. In addition, a trade-off study involving the probability of correct association, number of track matching points, size of association gate, and probability of false correlation has been prepared. These algorithms are coded in MATLAB and the results of simulations confirming the proof of concept are also presented.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 01, 1996
- Accession Number
- ADA314308
Entities
People
- Kai-Chi Chang
- Mieczyslaw M. Kokar
- Ritabrata Saha