Integration of Ladar Vision and Inertial Data for GNSS Denied Navigation

A. Soloviev, D. Eaton, M. Uijt de Haag, Z. Zhu

Abstract:	This paper describes the integration of images from a monocular video camera, twodimensional (2D) laser scanner data and measurements from an inertial navigation system (INS) for navigation in Global Navigation Satellite Systems (GNSS)-denied environments. The integrated solution uses a feature-based navigation approach that extracts features from video and laser scan images, and uses these features as landmarks. Changes in feature parameters are used for navigation. Laser scan data are applied to resolve the unknown scale of video images or, equivalently, to estimate the range parameter of video features. The estimation technique parameterizes features that are extracted from laser scans and video images at two platform locations and uses these parameters to estimate the range to the features. The estimator does not require the camera and the laser to observe the same features. Inertial data are applied to perform robust feature matching between images, enhance featuretracking performance, and perform coasting in those cases where the number of features is limited. The fusion of camera/laser/INS data is implemented through a complementary Kalman filter that estimates the INS drift terms. The tightly-coupled formulation of the Kalman filter is applied. Simulation results and initial experimental results are presented to demonstrate the feasibility of the vision/laser/inertial integrated solution.
Published in:	Proceedings of the 22nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2009) September 22 - 25, 2009 Savannah International Convention Center Savannah, GA
Pages:	818 - 825
Cite this article:	Soloviev, A., Eaton, D., de Haag, M. Uijt, Zhu, Z., "Integration of Ladar Vision and Inertial Data for GNSS Denied Navigation," Proceedings of the 22nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2009), Savannah, GA, September 2009, pp. 818-825.
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