Automotive radar is the most important component in the autonomous driving system, which detects the obstacles, vehicles and pedestrians around with acceptable cost. The target tracking is one of the key functions in the automotive radar which estimates the position and speed of the targets having regarding to the measurement inaccuracy and interferences. Modern automotive radar requires a multi-target tracking algorithm, as in the radar field of view hundreds of targets can present. In practice, the automotive radar faces very complicated and fast-changing road conditions, for example tunnels and curved roads. The targets’ unpredictable movements and the reflections of the electromagnetic wave from the tunnel walls and the roads will make the multi-target tracking a difficult task. Such situation may last several seconds so that the continuous tracks of the targets cannot be maintained and the tracks are dropped mistakenly. In the adaptive cruise control (ACC) system, non-continuous tracks leads to poor system performance, e.g. unwanted dangerous acceleration due to the target lost and unwanted sudden brake when previously dropped targets by mistake are tracked again. This paper presents a robust target tracking algorithm in our radar prototype which can maintain continuous track of the targets. This algorithm is verified in road tests on vehicle.