Multi-sensor management for passive target tracking in an anti-submarine warfare scenario

The Multi-Sensor Fusion Management (MSFM) algorithm positions multiple, bearings-only, passive sensors in a two-dimensional plane to optimise the fused probability of detection using a simple decision fusion method. Used iteratively, the MSFM algorithm allows a manoeuvring target to be passively tracked in the presence of clutter and missing measurements. The algorithm also incorporates prior knowledge of the physical constraints of the scenario, the targets initial position and its manoeuvring capabilities. In the MSFM algorithm the probability distribution of the target location is modelled using a non-parametric approach. The logarithm of the fused detection probability is used as a criterion function in the optimisation of the sensor positions, for which a straightforward gradient ascent approach is used. Following the placement optimisation, the sensors are deployed and the individual sensor detections combined using a logical OR fusion rule. The target location distribution can then be updated using the method of sampling, importance re-sampling (SIR). An extension to the MSFM algorithm is used which allows the reduction of the total number of sensors deployed. The MSFM algorithm has been implemented for a simulated, but operationally plausible, anti-submarine warfare scenario. In this scenario a single submarine passing through a channel is tracked by sonobuoys which are deployed by a Maritime Patrol Aircraft. When compared with a model of traditional methods for sonobuoy placement, the MSFM algorithm is found to reduce the time to submarine location by over a factor of three and the number of sonobuoys required by over a factor of four