A linear Kalman filter approach for estimation of a vehicle's motion parameters using range-Doppler tracking and road information

For the processing of ISAR images of curving vehicles, the accurate knowledge of the target position as well as the aspect angle rate is essential. Especially when the targets are non-cooperative, there are no measurements like GPS positions available. This paper presents a Kalman filter based algorithm which fuses radar measurements of distance and velocity in line of sight with road information. The result is a set of parameters containing target position, velocity and acceleration, each in Cartesian coordinates. The aspect angle can then be obtained by calculating the angle between target velocity vector and the slant range vector.