Feature-based robot navigation using a Doppler-azimuth radar
Guan RP., Ristic B., Wang L., Moran B., Evans R.
The merits of the Doppler radar compared to other existing sensors used for robot navigation, such as the LIDAR, include a lower cost, smaller size and lower weight which could prove to be useful in economically building a swarm of mobile vehicles. This paper demonstrates that, given a feature-based map and landmark associations, a Doppler radar which outputs Doppler-shift measurements with associated azimuth readings and an Extended Kalman filter for processing measurements, a robot is able to self-localise. Additionally, the Cramer–Rao lower bound (CRLB) for the estimation error of this scenario is computed to show that it is theoretically feasible for robot self-localisation, which is later verified through Monte–Carlo simulations.