A target tracking algorithm with range rate under the color measurement environment

In this paper a new observation model is presented to improve the state estimation and prediction in a target tracking problem. Comparing with conventional approaches, the following are distinguished points of the approach. First, the measurement equation is set up in the polar coordinate and even combines the range rate measurement with the usual position measurements (i.e. range, azimuth, elevation angle, range rate). Second, the observation noise of sensor data is considered as a colored one, so new linear state and observation equation can be obtained by incorporating the noise vector into the state vector, which satisfy the requirement of Kalman filter. As a result, the accuracy of both the measurement and the prediction will be increased.