Correlation based testing for passive sonar picture rationalization

Modern passive sonar systems employ a high degree of automation to produce a track-level sonar picture. Further refinement of the track-level information is normally performed by a human operator. Providing automated assistance would reduce the operator´s workload and is a key enabler for semi- and fully automated sonar systems. The nature of the signals emitted by targets and of the underwater environment typically results in each target being represented by multiple track segments. A tool is required which can numerically describe the relationship between pairs of track segments so that those that apparently share a common origin can be identified automatically. The sample correlation coefficient, is a statistical measure of relatedness. This paper describes the application of a test based on that measure to compare tracks produced by a probabilistic data association filter from a set of towed array sonar data