Abstract
In the tracking of a target using a radar or an imaging sensor, the acceleration of the target is usually modeled as a random vector (or the process noise in the state-space model) with known statistical properties. For a highly maneuvering target, the process noise has a large covariance matrix, and consequently, the estimated state has a large error. This paper proposes an approach that estimates the acceleration from the attitude of the target and uses the estimated acceleration for accurate tracking of the target. An imaging sensor is used for attitude estimation of the target (an aircraft; in this paper) as well as for tracking, without reliance on radar. Our simulation shows that the proposed method can track a maneuvering target much more accurately than traditional Kalman filters.
