Sequential unscented Kalman filter for radar target tracking with range rate measurements

Abstract

To solve the radar target tracking problem with range rate measurements, in which the errors between range and range rate measurements are correlated, a sequential unscented Kalman filter (SUKF) is proposed in this paper. A pseudo measurement is constructed by block-partitioned Cholesky factorization first, this can keep the range, bearing and elevation (or two direction cosine) measurements unchanged, while the errors between the original range and range rate measurement are decorrelated; then based on the UKF, the bearing, elevation (or two direction cosine) and the pseudo measurement are sequentially processed to enhance the filtering precision and the computational efficiency simultaneously. Validity and consistency of the new proposed algorithm is verified by Monte-Carlo simulation.