Terrain-based navigation: Trajectory recovery from LiDAR data

The need for complementary technologies to support navigation in GPS-challenged environment is rapidly growing in both outdoor and indoor environments. Remote sensing/mapping sensor performance continues to advance resulting in better spatial and temporal resolution of the acquired geospatial data, which, combined with the increasing hardware performance, can be available real-time or near real-time, and thus could be utilized in forming or improving the navigation solution. Terrain-based navigation has been used for a number of years to navigate airborne platforms, but the continuous exchange of precise geolocation information between the imaging and navigation modules to improve the overall error calibration is a novel idea, which should significantly increase the systempsilas fault tolerance in a variety of situations. The typical navigation solutions for airborne mapping systems are currently based on a GPS or integrated GPS/IMU systems, supporting usually a single imaging sensor, with no feedback between the sensory data processing filters. Most of the research in terrain-based navigation proposes the use of optical measurements from airborne imagery, although the concept of exploring LiDAR-based terrain navigation has also been reported. This paper is concerned with obtaining navigation data from LiDAR, and investigates the feasibility of the airborne trajectory recovery method based on LiDAR data using reference terrain surface models. If GPS signals are lost, the coordinates of LiDAR points can still be computed using the inertial-only solution, however, with errors growing in time. If reference surface data exists, they can be used to recover the LiDAR sensor trajectory by surface matching as long as the IMU drift is under a certain threshold. To assess the performance of the proposed method both simulated LiDAR data were used and an analysis oF the feasibility of the method is provided.