Improved Detection, Localization, and Classification of Torpedoes

Torpedoes are a lethal threat to surface ships, and the ability to detect them remains a ship-safety priority. Current torpedo-detection algorithms are effective against certain models, but evolving torpedo propulsion systems and enemy tactics constantly chip at away at the present defense capability. This proposal will demonstrate opportunities to use the hull-mounted sensor to significantly close that gap by increasing the probability of detecting torpedoes and reducing false torpedo alerts. Work will be focused on developing improvements across three areas of the torpedo-detection chain: beamforming, detection, and classification. 1. Utilize extended bandwidth and other improvements to the hull-array adaptive beamformer (ABF) to better detect both kinematic and acoustic-signature torpedo characteristics 2. Develop a kinematic feature-detector algorithm capable of detecting various torpedo motion patterns (for example, wake-homing torpedoes) with the hull array 3. Develop a classifier that incorporates data from the hull kinematic and acoustic-feature detectors, as well as any other available sensors, to determine whether a contact has weapon-like characteristics Other benefits include reduced development time and costs by reducing the need to retune the torpedo classifier when threat torpedo characteristics change.