Target position and velocity estimation for track declaration using air-to-air radar

Abstract

In this paper, target position and velocity estimation is investigated for track declaration using an air-to-air radar. A post-Kalman filtering processing method is proposed to improve the filtering accuracy and thus to improve the target position and velocity estimation accuracy. The proposed method passes the outputs of the Kalman filters (KFs) within a sliding window through a weighted least squares (WLS) estimator to refine the estimates of current target position and velocity and their variances. It is therefore referred to as the post-KF-WLS method. The post-KF-WLS estimates of the current target position and velocity are utilized to project the target position in a future time of interest. The uncertainty of the target position projection is derived and a closed-form solution is formulated. The effectiveness of the proposed method is demonstrated by using Monte Carlo simulations. Impacts of contributing factors to the target position projection uncertainty are quantified via simulations and the dominating factor is identified as well.