ABSTRACT
Millimeter wave (MMW) RADAR provides consistent and accurate range measurements for the environmental imaging required to navigate in dusty, foggy, and poorly illuminated environments. For localization and map building, it is necessary to predict the target locations accurately given a prediction of the vehicle/RADAR location. This chapter describes a new approach in predicting RADAR range bins which is essential for simultaneous localization and map building (SLAM) with MMW RADAR. The third contribution of this chapter is a SLAM formulation using an augmented state vector which includes the normalized RADAR cross sections (RCS) and absorption cross sections of features as well as the usual feature Cartesian coordinates. Most of the work in short-range RADAR has focused on millimeter waves as this allows narrow beam shaping, which is necessary for higher angular resolution. RADAR noise is the unwanted power that impedes the performance of the RADAR. For the accurate prediction of range bins, the characterization of noise is important.
