New development on tracking algorithm with derivation measurement

We present a new observation model to improve the state estimation and prediction in a target tracking problems. There are two distinguished points in this approach. First, the measurement equation is set up in the polar coordinate and even combines the derivation measurement (range rate, azimuth rate, and elevation rate) with the usual position measurements (range, azimuth angle, and elevation angle). Next, the observation noise of sensor data is considered as a colored one and is being set up as a model of AR(1), by means of a pseudo measurement equation, and the requirement of Kalman filter can be satisfied. As a result, the accuracy of both the observation and prediction is increased.