TERRAIN-AIDED LOCALIZATION USING FEATURE-BASED PARTICLE FILTERING
Open Access
Author:
Kadetotad, Sneha
Graduate Program:
Electrical Engineering
Degree:
Master of Science
Document Type:
Master Thesis
Date of Defense:
April 28, 2011
Committee Members:
Constantino Manuel Lagoa, Thesis Advisor/Co-Advisor Sean N Brennan, Thesis Advisor/Co-Advisor Constantino Manuel Lagoa, Thesis Advisor/Co-Advisor
Keywords:
features particle filtering localization vehicles tracking
Abstract:
The localization of vehicles on roadways without the use of a GPS has been of great interest in recent years and a number of solutions have been proposed for the same. The localization of vehicles has traditionally been divided by their solution approaches into two different categories: global localization which uses feature-vector matching, and local tracking which has been dealt with using techniques like Particle filtering or Kalman Filtering. This effort proposes a unifying approach that combines the feature-based robustness of global search with the local tracking capabilities of a Particle filter. Using feature vectors produced from pitch measurements from Interstate I-80 and US Route 220 in Pennsylvania, this work demonstrates wide area localization of a vehicle with the computational efficiency of local tracking.
