Sensor trajectory estimation by triangulating lidar returns

TL;DR

This paper presents a method for estimating the trajectory of an aerial lidar sensor by triangulating multiple lidar returns, incorporating scan angle data to also estimate pitch and yaw, extending previous work with a spline-based least-squares approach.

Contribution

It introduces a novel least-squares spline fitting method for simultaneous multi-return lidar data to recover sensor position and orientation, including pitch and yaw.

Findings

Effective trajectory estimation from multiple lidar returns

Extension to include scan angle for full orientation recovery

Improved accuracy over previous methods

Abstract

The paper describes how to recover the sensor trajectory for an aerial lidar collect using the data for multiple-return lidar pulses. This work extends the work of Gatziolis and McGaughey (2019) by performing a least-squares fit for multiple pulses simultaneously with a spline fit for the sensor trajectory. The method can be naturally extended to incorporate the scan angle of the lidar returns following Hartzell (2020). This allows the pitch and the yaw of the sensor to be estimated in addition to its position.