Evaluation of a Novel Radar Based Scanning Method

Abstract

The following paper introduces a novel scanning method for mapping and localization purposes in mobile robotics. Our method is based on a rotating monostatic radar network, which determines the positions of objects around the scanner via a continuously running lateration algorithm. The estimation of surfaces with ultrawideband radar networks has been studied experimentally in lab environments, especially with lateration, envelopes of spheres, and SEABED algorithms. But we do not see a link to the field of mapping and localization of mobile robots, where laser scanners are dominating. Indeed, only few research groups use radars for mapping and localization, but their applied sensor principle is based on a rotating focused radar beam. Consequently, only 2D radar scanners are known inside the robotic world and methods for 3D scanning with radars need to be investigated. This paper will derive the theoretical background of the sensor principle, which is based on a radar network on a rotating joint, and discuss its erroneous influences. We were performing first scans of standard geometries and deriving a model in order to compare theoretical and experimental measurement results. Furthermore, we present first mapping approaches and a simulation of a scanner with multiple sensors.

Multiple Direction Interference Suppression by Uniform Linear Phased Array Sidelobe Efficient Canceller

“…If the scanning step is wider than the interference direction spacing, then the ULA sidelobe cancellation is not effective, let alone its efficiency. In this case, obviously, the scanning step should be shortened [23], [24], [32], [33]. If the shortening is not possible, a tradeoff between the ULA radar effectiveness and the power-geometry loss must be made [34], [35].…”

A study of some FMCW radar algorithms for target location at low frequencies

“…Low-frequency radar must then be adapted to handle both the directivity and the bandwidth problem. There is the possibility of using geometrical methods, or trilateration [Groginsky, 1959;Lübbert, 2005;Fölster and Rohling, 2005;Rabe et al, 2009;Fritsche and Wagner, 2015;Huang and Narayanan, 2014;Samokhin et al, 2014;Brida and Machaj, 2013], for the azimuth problem. This approach requires some combinatorics in order to handle the ordering and the confluence of radar echoes.…”