title: Error and Performance Analysis of MEMS-based Inertial Sensors with a Low-cost GPS Receiver.
abstract: Global Navigation Satellite Systems (GNSS), such as the Global Positioning System (GPS), have been widely utilized and their applications are becoming popular, not only in military or commercial applications, but also for everyday life. Although GPS measurements are the essential information for currently developed land vehicle navigation systems (LVNS), GPS signals are often unavailable or unreliable due to signal blockages under certain environments such as urban canyons. This situation must be compensated in order to provide continuous navigation solutions. To overcome the problems of unavailability and unreliability using GPS and to be cost and size effective as well, Micro Electro Mechanical Systems (MEMS) based inertial sensor technology has been pushing for the development of low-cost integrated navigation systems for land vehicle navigation and guidance applications. This paper will analyze the characterization of MEMS based inertial sensors and the performance of an integrated system prototype of MEMS based inertial sensors, a low-cost GPS receiver and a digital compass. The influence of the stochastic variation of sensors will be assessed and modeled by two different methods, namely Gauss-Markov (GM) and AutoRegressive (AR) models, with GPS signal blockage of different lengths. Numerical results from kinematic testing have been used to assess the performance of different modeling schemes.
authors.affiliation: Research & Development Center, Hyundai Autonet Co., Ltd. Ami-ri, Bubal-eub, Ichon-si, kyoungki-do, 467-701, Korea. mipark@hyundaiautonet.com.
authors.forename: Minha
authors.initials: M
authors.lastname: Park
authors.affiliation: Department of Geomatics Engineering, Schulich School of Engineering, The University of Calgary, Calgary, Alberta, Canada T2N 1N4. gao@geomatics.ucalgary.ca.
authors.forename: Yang
authors.initials: Y
authors.lastname: Gao
keywords: Global Positioning System (GPS); Inertial Measurement Unit(IMU); Micro Electro Mechanical Systems(MEMS); Stochastic Modeling