Target tracking problem is normally composed of three main major functions: automatic track initiation, correlation, and track update. target tracking algorithms are usually based on applying optimal filtering theory. There have been numerous derivations of the optimal relations between the tracking parameters. In this paper, track update based on an adaptive Kalman algorithm with simplest case the adaptive aog filter is formulated as shown in Fig.1. The necessary relations for pre-update extrapolation gain selection, update position, velocity filtering or smoothing, covariance matrix, and post-update are discussed. Implementation and results of multi-target tracking (MU) using simulated electronic system input are presented. Results show a significant improvement in position and velocity of target tracking performance.