Scale-invariant multi-sensor velocity component estimation using certainty grids

Doppler frequency only reveals the radial component of a target´s velocity. In order to actually measure the true velocity vector of an object, at least two targets originating from the same object are required to resolve velocity ambiguities. However, the accuracy of this resolution heavily depends on wide angular separation of source targets, otherwise resulting equations will be ill-conditioned and error-prone. We propose a novel approach to velocity component measurement based on multiple distributed sensors, exploiting the fact that velocity space is invariant to sensor location. The focus is to improve conditioning by virtually expanding angular target spread. This is accomplished by choosing suitable fixed relative sensor rotations such that velocities can be robustly measured even for small objects and within each single measurement cycle. Basic data fusion is carried out using a probabilistic velocity grid which avoids the need for sophisticated clustering, especially in case of transients.