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

Qingli Li, Yalong Ban, Xiaoji Niu, Quan Zhang, Linlin Gong and Jingnan Liu

Mathematical Problems in Engineering, 2015, vol. 2015, 1-13

Abstract:

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 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.

Date: 2015
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2015/109267.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2015/109267.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:109267

DOI: 10.1155/2015/109267

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().