Knowledge-aided processing for multipath exploitation radar (MER)

摘要

Truly persistent surveillance of moving vehicles in urban areas spanning approximately 1,000 km2 is a desirable capability that does not exist due to the generally non-line-of-sight (non-LOS) nature of urban terrain. Radar is an attractive sensing modality for this purpose due to its all-weather day or night operation and the potential for a high area coverage rate. However, radar is not achieving the goal of persistent urban surveillance for several reasons. First, urban buildings block LOS between radars mounted on standoff platforms and large swaths of urban roadways. Overcoming the severe LOS blockage would force the sensors to very high aspect ratios that in turn would drive the total number of required platforms to an unacceptably large number. Second, existing airborne radar systems cannot properly function in an urban area due to the complicated multipath environment. In addition to vehicles moving in and out of LOS, reflections from buildings introduce numerous other returns. A classical LOS interpretation of the detections obtained in a multipath environment results in the formation of tracks that typically do not match the number of true objects in the scene or their positions and velocities. As an example, for certain geometries, a multipath return from a retreating vehicle can exhibit a Doppler consistent with a LOS return of an advancing vehicle.