NDLI: Strong tracking filter modeling for GPS robust navigation

Content Provider	IEEE Xplore Digital Library
Author	Fanchen Meng Shan Wang Bocheng Zhu
Copyright Year	2013
Description	Author affiliation: Sch. of Electron. Eng. & Comput. Sci., Peking Univ., Beijing, China (Fanchen Meng; Shan Wang; Bocheng Zhu)
Abstract	Efficient implementation of positioning algorithm plays a crucial role in modern Global Positioning System (GPS). Conventional non-linear Least Squares (LS) method is applied iteratively by Taylor expansion, which doesn't combine different epoch-time for mutual restraint. While with respect to generally used extended Kalman filter (EKF), it requires an accurate system model estimation and exact stochastic Gaussian white noise, resulting in non-uniformly convergence with an unknown bias or model error. To solve this problem, this paper proposes a Strong Tracking Filter (STF) modeling. To achieve robustness about model uncertainty and tracking capability on the mutation status, the STF adjusts the real-time state prediction error covariance matrix and the corresponding gain matrix. It also makes use of Time-varying Fading Factor (TVFF) to deal with the past data, which weakens the stale data to the impact of current filtered value. Simulation shows that the proposed STF is capable of enhancing more than half precision than traditional EKF and LS.
Starting Page	154
Ending Page	157
File Size	764560
Page Count	4
File Format	PDF
e-ISBN	9781467364812
DOI	10.1109/IWSDA.2013.6849086
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-10-27
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Time-varying Fading Factor Satellites extended Kalman filter Receivers GPS Kalman filters Mathematical model Covariance matrices Equations Least Squares Strong Tracking Filter Global Positioning System
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Application of improved strong tracking Kalman filter in MSINS/GPS integrated navigation system

Position estimation using extended Kalman Filter and RTS-smoother in a GPS receiver

Design of a BD-2/GPS Integrated Positioning Algorithm and Analysis of Its Positioning Accuracy

The study of GPS Time Transfer based on extended Kalman filter

Strong tracking cubature Kalman filter algorithm for GPS/INS Integrated Navigation System

Adaptive Fuzzy Strong Tracking Extended Kalman Filtering for GPS Navigation

Real time orbit determination using particle and Extended Kalman Filter

A robust adaptively filtering algorithm in GPS/DR integrated navigation

Robust autonomous vehicle navigation using adaptive interacting multiple model estimator

Strong tracking filter modeling for GPS robust navigation

Similar Documents

Application of improved strong tracking Kalman filter in MSINS/GPS integrated navigation system

Position estimation using extended Kalman Filter and RTS-smoother in a GPS receiver

Design of a BD-2/GPS Integrated Positioning Algorithm and Analysis of Its Positioning Accuracy

The study of GPS Time Transfer based on extended Kalman filter

Strong tracking cubature Kalman filter algorithm for GPS/INS Integrated Navigation System

Adaptive Fuzzy Strong Tracking Extended Kalman Filtering for GPS Navigation

Real time orbit determination using particle and Extended Kalman Filter

A robust adaptively filtering algorithm in GPS/DR integrated navigation

Robust autonomous vehicle navigation using adaptive interacting multiple model estimator

Strong tracking filter modeling for GPS robust navigation