Author : Adam Werries
Publisher :
ISBN 13 :
Total Pages : 6 pages
Book Rating : 4.:/5 (115 download)
Book Synopsis Adaptive Kalman Filtering Methods for Low-cost GPS/INS Localization for Autonomous Vehicles by : Adam Werries
Download or read book Adaptive Kalman Filtering Methods for Low-cost GPS/INS Localization for Autonomous Vehicles written by Adam Werries and published by . This book was released on 2016 with total page 6 pages. Available in PDF, EPUB and Kindle. Book excerpt: For autonomous vehicles, navigation systems must be accurate enough to provide lane-level localization. High-accuracy sensors are available but not cost-effective for production use. Although prone to significant error in poor circumstances, even low-cost GPS systems are able to correct Inertial Navigation Systems to limit the effects of dead reckoning error over short periods between sufficiently accurate GPS updates. Kalman filters are a standard approach for GPS/INS integration, but require careful tuning in order to achieve quality results. This creates a motivation for a Kalman filter which is able to adapt to different sensors and circumstances on its own. Typically for adaptive filters, either the process (Q) or measurement (R) noise covariance matrix of Kalman filters is adapted, and the other is fixed to values estimated a priori. We show that intelligently adapting both matrices in an intelligent manner can provide a more accurate navigation solution.