MULTI-SENSOR MULTI-TARGET TRACKING IN 3—DIMENSIONAL SPACE USING RANGE AND BEARING MEASUREMENTS

In this paper the problem of estimation and tracking of geometric position of an object in a 3— dimensional space is considered using a network of sensors positioned at known points. Observations from each sensor include bearing and slant range of each object. Cramer—Rao error bound for estimation of target cartesian coordinates is derived and analyzed, in order to study the effects of measurement noise and sensor distribution in geometrical space. A basic structure for an adaptive algorithm is proposed for data association and tracking.