Sensor Data Analysis for a Dual Airborne Laser Scanner Aided Inertial Navigator

Ananth K. Vadlamani, and Maarten Uijt de Haag

Abstract:	Aiding an Inertial Measurement Unit (IMU) with terrain measurements from Dual Airborne Laser Scanners (DALS) is a novel approach to enable autonomous aircraft navigation. Initial results show the integrated system achieves position drift performance of about 100 m/hr. Similar to inertial navigation by itself, the DALS aiding algorithm is also considered a dead-reckoning navigation method where the position drift errors are characterized by a random-walk process. However, if the sensor data or its knowledge thereof is off-nominal, the drift errors can increase by several orders of magnitude. This paper discusses two separate sensor data error scenarios: large (off-nominal) errors in the terrain models reconstructed from ALS measurements and initial heading uncertainty on the IMU. The former scenario includes noise from both ALS and IMU sensors. These errors and their effect on the generated terrain cause the variance of the differenced (residual) terrain models to exceed its nominal threshold. The detection and exclusion of these kinds of faults will be discussed in more detail in this paper. In case of an initial heading uncertainty, the horizontal components of position/velocity vectors are incorrectly resolved resulting in the accumulation of position errors. Such a heading uncertainty can be calibrated by incorporating additional information into the DALS solution. Various methods to find the heading bias based on terrain correlation and features will be addressed. These techniques are discussed using example results that are obtained by applying the DALS aiding algorithm to inertial sensor data collected during flight tests.
Published in:	Proceedings of the 63rd Annual Meeting of The Institute of Navigation (2007) April 23 - 25, 2007 Royal Sonesta Hotel Cambridge, MA
Pages:	89 - 96
Cite this article:	Vadlamani, Ananth K., de Haag, Maarten Uijt, "Sensor Data Analysis for a Dual Airborne Laser Scanner Aided Inertial Navigator," Proceedings of the 63rd Annual Meeting of The Institute of Navigation (2007), Cambridge, MA, April 2007, pp. 89-96.
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