Self-localization of distributed radar nodes based on velocity matching of moving targets

Data fusion of multiple radar sensors illuminating the same scene from different locations requires precise knowledge of sensor arrangement. Utilizing a novel strategy for automatic self-localization solely based on measurements of a moving target we eliminate the need for manual sensor positioning as well as external infrastructure like GPS or location-aware tags. The proposed method exploits the mismatch of target velocity as a vectorial feature as measured by a pair of sensors by means of extrapolation to what we call a significant point of transit (SPT). The intersection angle of these vectors at the SPT is independent of sensor positions, revealing information about the underlying sensor rotation. Afterwards, the relative translation is found by coordinate projection of target positions. This general concept is verified by real world SIMO radar data, presenting self-localization concepts in range-azimuth and azimuth-Doppler spaces.