Using robotic total station networks for 360° prism deviation reduction

Abstract The accurate generation of reference trajectories is essential for the empirical evaluation of navigation sensors. Systematic deviations of the reference trajectory should be avoided as much as possible, as they distort the result of the trajectory comparison. While robotic total stations (RTS) already have several advantages over commonly used GNSS/IMU reference trajectories, they are still not free of systematic deviations due to the use of 360° prisms. Depending on the angle of incidence of the RTS signal into the prism, these cause systematic deviations in the position in the range of several millimeters. In this paper, we therefore present a measurement concept that can be used to reduce these deviations. We use a network of multiple RTS that track the same 360° prism. Due to the different RTS-target geometry of each RTS, the resulting deviations also differ and can be reduced when averaged. We support this claim with experiments which show a reduction of horizontal position deviations of up to 38.5 % in a static measurement and up to 22.4 % in a kinematic measurement. However, the vertical deviations cannot be reduced by combining multiple RTS with our measurement setup. We publish the code for controlling and managing RTS networks here: https://github.com/Engineering-Geodesy-Bonn/rts-network .