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Inertial Sensor Error Rate Reduction Scheme for INS/GPS Integration  

Khan, Iftikhar (Dept. of Communication Eng., Myongji University)
Baek, Seung-Hyun (Dept. of Communication Eng., Myongji University)
Park, Gyung-Leen (Dept. of Computer Eng. Cheju National University)
Kang, Sung-Min (College of Business Administration Chung-Ang University)
Lee, Yeon-Seok (Dept. of Electronics and Information Eng. Kunsan National University)
Jeong, Tai-Kyeong (Dept. of Communication Eng., Myongji University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SC / v.46, no.3, 2009 , pp. 22-30 More about this Journal
Abstract
GPS and INS integrated systems are expected to become commonly available as a result of low cost Micro-Electro-Mechanical Sensor (MEMS) technology. However, the current performance achieved by low cost sensors is still relatively poor due to the large inertial sensor errors. This is particularly prevalent in the urban environment where there are significant periods of restricted sky view. To reduce the inertial sensor error, GPS and low cost INS are integrated using a Loosely Coupled Kalman Filter architecture which is appropriate in most applications where there is good satellite availability. In this paper, we present the GPS/INS sensor Integration using Loosely Coupled Kalman Filter approach. We also compare the simulation results of Wander Azimuth Strapdown Mechanization Scheme with the reference values generated by the ZH35C trajectory simulator that is describe mathematically either by the geometry of the path, or as the position of the object over time.
Keywords
Micro-Electro-Mechanical Sensor(MEMS); Loosely Coupled; Kalman Filter; Wander Azimuth Strapdown Mechanization;
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