Share Email Print

Proceedings Paper

An X-band radar terrain feature detection method for low-altitude SVS operations and calibration using LiDAR
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

To enable safe use of Synthetic Vision Systems at low altitudes, real-time range-to-terrain measurements may be required to ensure the integrity of terrain models stored in the system. This paper reviews and extends previous work describing the application of x-band radar to terrain model integrity monitoring. A method of terrain feature extraction and a transformation of the features to a common reference domain are proposed. Expected error distributions for the extracted features are required to establish appropriate thresholds whereby a consistency-checking function can trigger an alert. A calibration-based approach is presented that can be used to obtain these distributions. To verify the approach, NASA's DC-8 airborne science platform was used to collect data from two mapping sensors. An Airborne Laser Terrain Mapping (ALTM) sensor was installed in the cargo bay of the DC-8. After processing, the ALTM produced a reference terrain model with a vertical accuracy of less than one meter. Also installed was a commercial-off-the-shelf x-band radar in the nose radome of the DC-8. Although primarily designed to measure precipitation, the radar also provides estimates of terrain reflectivity at low altitudes. Using the ALTM data as the reference, errors in features extracted from the radar are estimated. A method to estimate errors in features extracted from the terrain model is also presented.

Paper Details

Date Published: 11 August 2004
PDF: 15 pages
Proc. SPIE 5424, Enhanced and Synthetic Vision 2004, (11 August 2004); doi: 10.1117/12.542452
Show Author Affiliations
Steven D. Young, NASA Langley Research Ctr. (United States)
Maarten Uijt de Haag, Ohio Univ. (United States)
Jacob Campbell, Ohio Univ. (United States)

Published in SPIE Proceedings Vol. 5424:
Enhanced and Synthetic Vision 2004
Jacques G. Verly, Editor(s)

© SPIE. Terms of Use
Back to Top