Adaptive measuring trajectory for scanning lidars: proof of concept

Abstract

Abstract Application of nacelle-mounted long-range scanning lidars is facing the challenge that the nacelle motion causes deviations in the measuring trajectories. Such lidars are very sensitive to even the slightest trajectory deviation due to its long measuring range. Motivated by this need, we propose the concept of adaptive measuring trajectory and explore its use for eliminating the effect of the rotational motion of the lidar on the target measuring trajectory. This work first aims to experimentally test the performance of adaptive measuring trajectory under ideal conditions by installing a scanning lidar on a 6DOF motion platform to model the lidar motion on the turbine nacelle. The real trajectory with and without correction is measured by a camera. The comparison confirms that the adaptive measuring trajectory could stablize the target measuring trajectory given the lidar motion. Then, the possibility of using Kalman filter to estimate lidar motion given noisy motion measurements is investigated. The results show great potential of Kalman filter for lidar motion estimation, which could be very useful for its future application.