Track-Before-Detect for an Active Towed Array Sonar

Conventional active sonar processing systems typically reduce the sensor data from an intensity map to a pointmeasurement form via a detection thresholding process. This approach is often sufficient for detecting and tracking high signal-to-noise-ratio (SNR) targets but becomes more challenging for low SNR targets. Track-Before-Detect (TkBD) is an alternative tracking technique that supplies raw sensor data to the tracker to determine the presence and kinematic state of a target. This paper considers the application of TkBD to an active sonar tracking problem using the Histogram-Probabilistic Multi-Hypothesis Tracking (H-PMHT) algorithm. To aid in the detection of targets in the sensor image, the measurement model for the standard H-PMHT algorithm is extended to incorporate a bearingdependent point spread function. Using real data gathered from sonar trials, the performance of the resulting multitarget TkBD algorithm is shown to be more robust at low SNR levels when compared against a conventional point measurement tracker based on Integrated Probabilistic Data Association.