Robust Performance Analysis of Terrain Referenced Navigation Using Flash Lidar

Hyun Cheol Jeon, Young Bum Park and Chan Gook Park

Abstract: The sequential processing Terrain Referenced Navigation (TRN) updates the vehicle position using Extended Kalman Filter (EKF) whenever the measurement is acquired. The conventional sequential TRN uses RADAR (Radio Detection And Ranging) altimeter as a TRN sensor and uses only one range measurement. However, the TRN performance can be improved by replacing the TRN sensor with a flash LiDAR (Light Detection And Ranging), which measures multiple ranges between the LiDAR and the targets by using speed of light and Time Of Flight (TOF). It is possible because the receiver of the flash LiDAR has Focal Plane Array (FPA) which consists of many photo detectors as a form of array. In the conventional TRN algorithm, Digital Elevation Map (DEM) error is applied to the measurement covariance. However, the location where the terrain elevation is computed is not coincide with DEM location in general. Therefore applying the DEM error to all estimated target location is not realistic. In this paper, it is shown that it is possible to get more robust result by using Gaussian Process which calculates the terrain elevation and its variance at any location.
Published in: Proceedings of IEEE/ION PLANS 2016
April 11 - 14, 2016
Hyatt Regency Hotel
Savannah, GA
Pages: 970 - 975
Cite this article: Jeon, Hyun Cheol, Park, Young Bum, Park, Chan Gook, "Robust Performance Analysis of Terrain Referenced Navigation Using Flash Lidar," Proceedings of IEEE/ION PLANS 2016, Savannah, GA, April 2016, pp. 970-975.
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