Improving Automated Search for Underwater Threats Using Multistatic Sensor Fields by Incorporating Unconfirmed Track Information

Sonobuoy fields, comprising a network of sonar transmitters and receivers, are used to search for and track underwater targets. Although normally such fields are operated from a maritime patrol aircraft, automated scheduling and processing creates opportunities for employing them as autonomous sensor systems. The automated search mechanism considered in this work is controlled by modelling the presence of undetected threats in an Operational Area (OA) using a spatial probability density function (PDF), known as a threat map. The algorithm decides how to schedule waveform transmissions, known as pings, to efficiently search and clear the OA. A conventional approach is to update the threat map based on just the characteristics of the sonobuoy field and switch to a separate metric to track a target after track confirmation. In this study we address the phase when there are potential contacts which cannot yet be promoted to confirmed tracks. We develop a mechanism for probing the associated areas of interest while still remaining in the threat map driven search scheduling. To this end, we propose reinitialising the threat map after each transmission using an augmented PDF, where unconfirmed tracks are represented by weighted Gaussians. Simulations show that this approach significantly improves search performance, reducing the number of pings required to confirm a track, distance from a confirmed track to the target and the proportion of falsely confirmed tracks.