Realtime visual-inertial SLAM integrated with radar data to triangulate targets

[weisongwen]

This paper presents research concerning the use of visual-inertial Simultaneous Localization And Mapping (SLAM) algorithms to aid in Continuous Wave (CW) radar target mapping. SLAM is an established field in which radar has been used to internally contribute to the localization algorithms. Instead, the application in this case is to use SLAM outputs to localize radar data and construct three-dimensional target maps which can be viewed live in augmented reality. These methods are transferable to other types of radar units and sensors, but this paper presents the research showing how the methods can be applied to calculate depth efficiently with CW radar through triangulation using a Boolean intersection algorithm. Localization of the radar target is achieved through quaternion algebra. Due to the compact nature of the SLAM and CW devices, the radar unit can be operated entirely handheld. Targets are scanned in a free-form manner where there is no need to have a gridded scanning layout. The main advantage to this method is eliminating many hours of usage training and expertise, thereby eliminating ambiguity in the location, size and depth of buried or hidden targets. Additionally, this method grants the user the additional power, penetration and sensitivity of CW radar without the lack of range finding. Applications include pipe and buried structure location, avalanche rescue, structural health monitoring and historical site research. --