Efficiency Improvement of Kalman Filter for GNSS/INS through One-Step Prediction of P Matrix

To meet the real-time and low power consumption demands in MEMS navigation and guidance field, an improved Kalman filter algorithm for GNSS/INS was proposed in this paper named as one-step prediction of P matrix. Quantitative analysis of field test datasets was made to compare the navigation accurac...

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Bibliographic Details
Main Authors: Qingli Li, Yalong Ban, Xiaoji Niu, Quan Zhang, Linlin Gong, Jingnan Liu
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2015/109267
Description
Summary:To meet the real-time and low power consumption demands in MEMS navigation and guidance field, an improved Kalman filter algorithm for GNSS/INS was proposed in this paper named as one-step prediction of P matrix. Quantitative analysis of field test datasets was made to compare the navigation accuracy with the standard algorithm, which indicated that the degradation caused by the simplified algorithm is small enough compared to the navigation errors of the GNSS/INS system itself. Meanwhile, the computation load and time consumption of the algorithm decreased over 50% by the improved algorithm. The work has special significance for navigation applications that request low power consumption and strict real-time response, such as cellphone, wearable devices, and deeply coupled GNSS/INS systems.
ISSN:1024-123X
1563-5147