Combined acoustic target tracking and sensor localization

This study investigates the application of a batch oriented maximum a posteriori (MAP) estimation scheme to the problem of tracking a moving target using acoustic bearing-only data from sensors with unknown positions. In this paper a simple method for determining sensor location and movement from the measured acoustic data is proposed, and is subsequently utilized to update the sensor positions to reduce tracking errors. The Cramer-Rao bound (CRB) on the estimate is derived, and simulations show that the proposed method compares favorably to the bound.