Time-Based Geolocation and Main Beam Estimation of an Airborne Rotating Radar for Spectrum Sharing

Dynamic spectrum sharing between airborne radars and 5G cellular networks has the potential for granting additional RF spectrum to cellular networks while preserving the performance of airborne radars. In the case of an airborne radar with a predictably rotating antenna, a spectrum sharing controller can use estimates of the radar's location and beam orientation to anticipate and mitigate RF interference events over a large geographic area. However, localization of the radar is complicated by airborne radar's relatively narrow beamwidth and time-varying waveform. We introduce the Rotating Beam Time-of-Arrival (RB-TOA) algorithm to jointly estimate the radar's location and antenna main beam orientation. Each RF sensor is coarsely time-synchronized and measures the peak of the received signal envelope over each rotation interval to estimate when the radar's main beam maximally couples with the sensor's antenna; these time estimates are then combined at a sensor fusion server and the radar's main beam orientation and location are jointly solved using a gradient descent algorithm. We show that the RBTOA algorithm rapidly converges to a geolocation accuracy that is 50x better than the performance of a two-antenna angle-of-arrival algorithm (AoA) for the same number of sensors.