Target detection enhancement using target motion discrimination

The significant challenge in shallow water environments is performing reliable target detection and classification while maintaining a reasonable false alert rate. Recent Navy operational experiences in shallow water environments have shown that existing active sonar systems experience excessive amounts of clutter and false alerts which result in a significant reduction in platform tactical advantage and survivability. A target motion discriminator (TMD) technique based on the Interacting Multiple Model (IMM) estimation algorithm is presented to exploit the consistency of position and motion information observed over multiple pings to form a robust classification decision. Several motion class models reside within the TMD, to provide accurate target state estimates and target likelihood functions for both maneuvering and non-maneuvering contacts. Classification performance is dramatically enhanced by using a “no target model” to reject contacts which exhibit erratic motion, i.e., inconsistent with a target motion model while promoting contacts with consistent motion. The accurate estimation of target dynamics obtained by the IMM approach provides the capability to reject stationary clutter resulting from surface and bottom reverberation and reliably detect the slow moving threat. A robust sequential likelihood ratio test which minimizes the classification decision time and improves classification performance is developed and demonstrated using sea test data collected in various environments.