Track modeling for maritime surveillance

Maritime surveillance of coastal regions requires the processing of data from a large number of heterogeneous surveillance sources. The generation of effective maritime domain awareness requires that the tracks from these sources must be fused. An automated fusion process that supports maritime domain awareness requires that the tracks from heterogeneous sources be modeled in such a way as to support an automated track association decision process. Collection of sensor contact reports are therefore grouped into tracks and a mathematical model of these tracks are used to support track correlation which leads to track association. This paper presents the approach for track modeling based on genetic algorithm optimization and discusses its performance.