Multisensor Track Management for Targets with Fluctuating SNR

In active sonar tracking applications, targets frequently undergo fading in which the target's detection probability can shift suddenly between high and low values. This characteristic is a function of the undersea environment. Using a multisensor active sonar problem, we examine the performance of track management (confirmation and termination) routines where target detections are based on an underlying hidden Markov model (HMM) with high and low detection states. Rule-based track confirmation tests are compared including M/N rules and rules that differentiate the measurements by receiver source (M/N from at least C sensors), each of which is suboptimal compared with a fixed-length likelihood ratio test. We show that significant performance improvements (to near-optimal) can be obtained using a composite track confirmation test that combines two or three such rules in a logical OR operation. Track termination tests are next compared, and it is shown that a Bayesian sequential test (the Shiryaev test) yields dramatic performance improvements over a K/N track termination rule and the Page test. The model-based results are validated using simulations of a multisensor tracking scenario. The results of this paper are informed by a multisensor sonar application. However, targets may fade in and out of view in other modalities as well, due to aspect-dependent radar cross-section or occlusion. As such, our suggestions for improved HMM-modulated SNR track initiation and termination apply to multisensor radar target tracking as well.