Deghosting in multipassive acoustic sensors

In this paper, we describe a deghosting algorithm in multiple passive acoustic sensor environment. In a passive acoustic sensor system, a target is detected by its bearing to the sensor, and the target location is obtained from triangulation of bearings on different sensors. However, in multi-passive sensor and multi-target scenario, triangulation is difficult. This is because multi-target triangulation results in a number of ghost targets being generated. In order to remove the triangulating ghosts, the deghosting technique is essential to distinguish the true targets from the ghost targets. We suggest a deghosting algorithm by applying Bayes’ theorem and the likelihood function on the acoustic signals. A probability related to acoustic signal on each triangulating point is recursively computed and updated at every time stamp or frame. The triangulating point will be classified as a true target, once its probability exceeds a predefined threshold. Furthermore, acoustic signal has propagation delay. The situation yields the triangulating location biased to the bearing of the nearest sensor. In our algorithm, the propagation delay problem is solved by matching the histories of bearing tracks, and yields the unbiased location that has similar emitting times for the sensors contributing to the triangulation point. The emitting times can be derived from detecting times and propagation delays. Performance result is presented on simulation data.