GRASP multi-sensor search tactics against evading targets

Abstract

GRASP (Genetic Range-dependent Algorithm for Search Planning) was developed to nearly optimize sonar search patterns in complicated environments. The standard scenario is to maximize cumulative detection probability (CDP) for several ASW searchers against a randomly patrolling threat. An improvement to the algorithms allows the target to counter-detect an active sonar pulse and to maneuver away from the searcher. In general, the CDP is reduced dramatically by evasive maneuvers, since the counter-detection range is usually greater than the detection range. The analysis covers several combinations of platforms and sensors in artificial environments. The GRASP solutions show significant benefit, especially against an evading target. GRASP joint tactics exploit target evasive maneuvers to significantly increase detection performance relative to non-joint tactics. A somewhat surprising result is that as the target evasion range increases (better intercept receiver), the multi-sensor CDP increases in an explainable way. The advantages of multi-platform and multisensor ASW search plans are described in terms of improved performance and reduced search time.