Multiple line-of-sight predicted observations with millimetre wave radar for outdoor SLAM

Millimetre wave radar can offer remarkable advantages for autonomous robotic mapping and navigation because their performance is less affected by dust, fog, moderate rain or snow and ambient lighting conditions. millimetre wave (MMW) radar differs from other range sensors as it can provide complete power returns for many points down range. In addition, MMW radar has a comparatively long range which can enable a vehicle to localise efficiently when there are only a few features in the environment. This paper describes a method to accurately simulate the range spectra using the radar range equation. This is very important in robot navigation (eg. SLAM) for generating predictions of what can be observed from different sensor locations and correspondingly, providing an interpretation for observed targets. To understand the MMW radar range spectrum and to accurately simulate it, it is necessary to know the noise distributions in the radar spectrum. A detailed noise analysis during signal absence and presence is carried out which shows various sources of noise affecting MMW radars. RADAR range bins are then simulated using the radar range equation and the noise statistics are compared with real results in controlled environments. It is demonstrated that it is possible to provide realistic predicted radar power/range spectra, for multiple targets down range. A new augmented state vector for an extended Kalman filter is introduced which includes the relative radar cross sections of features, and the radar constants and losses along with the vehicle pose and feature locations. Finally a SLAM formulation using the proposed methods is shown. This work is a step towards robust outdoor SLAM with MMW radar based continuous power spectra.