A survey of filtering techniques for vehicle tracking by radar equipped automotive platforms
Nikos Floudas, Aris Polychronopoulos, Angelos Amditis · 2005
In modern automotive safety applications, the use of radar technology seems to be a promising technique. Vehicles equipped with on board radar sensors aim at detecting moving or stationary objects in the sensor's field of view and identifying critical collision situations. Thus, reliable tracking is of crucial importance for efficiency improvement in such systems. The presence of non linearities in measurement space is quite common in these architectures, i.e. the existence of radial velocity measurements in absence of lateral velocity ones generates a non-linear measurement model. In this paper, filtering techniques for the solution of this problem are tested, including Kalman filter and particle filters solutions. The test set of this study is consisted of a simulated highway scenario and the efficiency of filtering in position estimation; velocity estimation and time delay is checked.