Sensor Modelling for Radar-Based Occupancy Mapping

This paper addresses the issue of creating a sensor model for a new short-range 24GHz close proximity detection (CPD) radar. The CPD radar is designed to provide improved situational awareness to the driver of a large vehicle. It is able to detect light vehicles and other targets at ranges from 2.2m to 45m within an arc of 160 degrees azimuth, but radar measurements contain data from noise and clutter which must be filtered out. Dynamic thresholds such as constant false-alarm rate (CFAR) processors [19] do not work well with short measurement vectors or targets that occupy multiple measurement bins. In this paper, a new method is used where measurements of environmental noise, clutter and targets are used to calculate the false alarm and target detection probabilities for each bin and develop a fixed detection threshold for each bin. This filter is used to construct a sensor model which maps measurement power to probability of bin occupancy, which is then used to generate an occupancy grid map of the environment from CPD radar measurements.