Tracking Aircraft by Acoustic Sensors; Multiple Hypothesis Approach Applied to Possibly Unresolved Measurements

Poor resolution of acoustic sensors frequently lead to merged measurements for closely spaced targets. This paper considers tracking low-altitude aircraft by a network of acoustic sensors. Merging measurement outputs from sensors are probabilistically analysed. A multiple hypothesis approach is then used to derive an algorithm for tracking the targets. The likelihood functions used in hypothesis evaluation are derived assuming two-way merging and a simulated example is used to illustrate the algorithm.