A Deep Integration Estimator for Urban Ground Navigation

D. Landis, T. Thorvaldsen, B. Fink, P. Sherman and S. Holmes

Abstract:	The objective of the Personal Navigator System (PNS) is to construct a wearable navigation system that provides accurate position over extended missions in a deprived Global Positioning System (GPS) environment. The prototype multisensor navigator included a set of micromechanical inertial sensors, a three-axis miniature radar, a selective availability antispoofing module (SAASM) GPS receiver, and a barometric altimeter. Realtime embedded software sampled sensor data, controlled GPS receiver tracking loops, and hosted a multisensor optimal estimator whose output position was transmitted via wireless link to a high-resolution personal data accessory (PDA) tracking display. The fully packaged system was field tested in Cambridge, Massachusetts under realistic, GPS-stressed conditions. This paper focuses on the Deep Integration (DI) algorithm design used for the optimal estimation of both position and receiver tracking control. The algorithm was tailored here for intermittent GPS visibility on the ground and in outdoor-indoor-outdoor maneuvers. DI has been used previously for missile guidance, navigation, and control with clear sky view. The PNS required an optimal estimator that combined the nonlinear GPS/inertial DI algorithm with measurements from other sensors. The mission duration here was much longer, and the satellite environment over the ground track was highly variable compared with earlier DI applications. This required the development of strategies for dropping satellites from track after long blockage times and for taking control of newly visible satellites under DI tracking. Here, the advantage of DI tracking is the ability to extract GPS pseudorange information almost instantly if a satellite reappears momentarily from a blockage. This paper reviews the DI approach with stress on the receiver correlator power measurements, nonlinear filter equations, and the calculation of numerically-controlled oscillator (NCO) commands. Specific problems encountered, such as clock error recalculation and numerical issues, will be mentioned. Urban canyon performance data demonstrating accurate navigation under sparse GPS availability are also described.
Published in:	Proceedings of IEEE/ION PLANS 2006 April 25 - 27, 2006 Loews Coronado Resort Hotel San Diego, CA
Pages:	927 - 932
Cite this article:	Landis, D., Thorvaldsen, T., Fink, B., Sherman, P., Holmes, S., "A Deep Integration Estimator for Urban Ground Navigation," Proceedings of IEEE/ION PLANS 2006, San Diego, CA, April 2006, pp. 927-932. https://doi.org/10.1109/PLANS.2006.1650693
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