An augmented state SLAM formulation for multiple line-of-sight features with millimetre wave RADAR

Abstract

Millimetre wave RADAR can penetrate certain non-metallic objects, meaning that multiple line-of-sight objects can sometimes be detected, a property which can be exploited in mobile robot navigation in outdoor unstructured environments. This paper describes a new approach in predicting RADAR range bins which is essential for simultaneous localisation and map building (SLAM) with millimetre wave RADAR. The first contribution of this paper is a SLAM formulation using an augmented state vector which includes the normalised RADAR cross sections (RCS) and absorption cross sections of features as well as the usual feature Cartesian coordinates. The term "normalised" is used as the actual RCS is incorporated into a reflectivity parameter. Normalisation results as it is assumed that the sum of this reflectivity parameter and the absorption and transmittance parameters is unity. This is carried out to provide feature rich representations of the environment to significantly aid the data association process in SLAM. The second contribution is a predictive model of the power-range spectra (often referred to as range bins), from differing vehicle locations, for multiple line-of-sight targets. This forms a predicted power-range observation, based on estimates of the augmented SLAM state. The formulation of power returns from multiple objects down-range is derived and predicted RADAR range spectra are compared with real spectra, recorded outdoors. This prediction of power-range spectra is a step towards a full, RADAR based SLAM framework.