Modified RHKF Filter for Improved DR/GPS Navigation against Uncertain Model Dynamics
In this paper, an error compensation technique for a dead reckoning (DR) system using a magnetic compass module is proposed. The magnetic compass‐based azimuth may include a bias that varies with location due to the surrounding magnetic sources. In this paper, the DR system is integrated with a Glob...
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| Vydané v: | ETRI journal Ročník 34; číslo 3; s. 379 - 387 |
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| Hlavní autori: | , |
| Médium: | Journal Article |
| Jazyk: | English |
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한국전자통신연구원
01.06.2012
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| ISSN: | 1225-6463, 2233-7326 |
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| Abstract | In this paper, an error compensation technique for a dead reckoning (DR) system using a magnetic compass module is proposed. The magnetic compass‐based azimuth may include a bias that varies with location due to the surrounding magnetic sources. In this paper, the DR system is integrated with a Global Positioning System (GPS) receiver using a finite impulse response (FIR) filter to reduce errors. This filter can estimate the varying bias more effectively than the conventional Kalman filter, which has an infinite impulse response structure. Moreover, the conventional receding horizon Kalman FIR (RHKF) filter is modified for application in nonlinear systems and to compensate the drawbacks of the RHKF filter. The modified RHKF filter is a novel RHKF filter scheme for nonlinear dynamics. The inverse covariance form of the linearized Kalman filter is combined with a receding horizon FIR strategy. This filter is then combined with an extended Kalman filter to enhance the convergence characteristics of the FIR filter. Also, the receding interval is extended to reduce the computational burden. The performance of the proposed DR/GPS integrated system using the modified RHKF filter is evaluated through simulation. |
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| AbstractList | In this paper, an error compensation technique for a dead reckoning (DR) system using a magnetic compass module is proposed. The magnetic compass‐based azimuth may include a bias that varies with location due to the surrounding magnetic sources. In this paper, the DR system is integrated with a Global Positioning System (GPS) receiver using a finite impulse response (FIR) filter to reduce errors. This filter can estimate the varying bias more effectively than the conventional Kalman filter, which has an infinite impulse response structure. Moreover, the conventional receding horizon Kalman FIR (RHKF) filter is modified for application in nonlinear systems and to compensate the drawbacks of the RHKF filter. The modified RHKF filter is a novel RHKF filter scheme for nonlinear dynamics. The inverse covariance form of the linearized Kalman filter is combined with a receding horizon FIR strategy. This filter is then combined with an extended Kalman filter to enhance the convergence characteristics of the FIR filter. Also, the receding interval is extended to reduce the computational burden. The performance of the proposed DR/GPS integrated system using the modified RHKF filter is evaluated through simulation. In this paper, an error compensation technique for a dead reckoning (DR) system using a magnetic compass module is proposed. The magnetic compass-based azimuth may include a bias that varies with location due to the surrounding magnetic sources. In this paper, the DR system is integrated with a Global Positioning System (GPS) receiver using a finite impulse response (FIR) filter to reduce errors. This filter can estimate the varying bias more effectively than the conventional Kalman filter,which has an infinite impulse response structure. Moreover, the conventional receding horizon Kalman FIR (RHKF) filter is modified for application in nonlinear systems and to compensate the drawbacks of the RHKF filter. The modified RHKF filter is a novel RHKF filter scheme for nonlinear dynamics. The inverse covariance form of the linearized Kalman filter is combined with a receding horizon FIR strategy. This filter is then combined with an extended Kalman filter to enhance the convergence characteristics of the FIR filter. Also, the receding interval is extended to reduce the computational burden. The performance of the proposed DR/GPS integrated system using the modified RHKF filter is evaluated through simulation. KCI Citation Count: 8 |
| Author | Cho, Seong Yun Lee, Hyung Keun |
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| Cites_doi | 10.1109/TAC.2002.802772 10.1109/9.328818 10.1016/S0005-1098(01)00242-4 10.1109/9.788546 10.1109/9.388677 10.1109/9.788554 |
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| References_xml | – volume: 40 start-page: 995 issue: 6 year: 1995 end-page: 1006 article-title: Moving Horizon Observers and Observer Based Control publication-title: IEEE Trans. Autom. Control – volume: 44 start-page: 1750 issue: 9 year: 1999 end-page: 1753 article-title: Receding Horizon Recursive State Estimation publication-title: IEEE Trans. Autom. Control – year: 2000 article-title: Stability of Receding Horizon Kalman Filter in State Estimation of Linear Time‐varying Systems – volume: 38 start-page: 545 issue: 3 year: 2002 end-page: 551 article-title: A Receding Horizon Unbiased FIR Filter for Discrete‐Time State Space Models publication-title: Automatica – volume: 39 start-page: 2087 issue: 10 year: 1994 end-page: 2091 article-title: Optimal State Estimation without the Requirement of a Priori Statistics Information of the Initial State publication-title: IEEE Trans. Autom. Control – year: 2001 – start-page: 15 year: 1997 end-page: 21 article-title: Applications of Magnetoresistive Sensors in Navigation System – year: 1996 – volume: 39 issue: 22 year: 2003 article-title: Tilt Compensation Algorithm for 2‐Axis Magnetic Compass publication-title: IEE Electron. Lett. – volume: 38 start-page: 333 year: 2002 end-page: 339 article-title: Separate‐Bias Estimation Scheme with Diversely Behaved Biases publication-title: IEEE Trans. Aerospace Electron. Syst. – start-page: 1860 year: 2001 end-page: 1865 article-title: A Suboptimal Algorithm for the Optimal Bayesian Filter Using Receding Horizon FIR Filter – volume: 44 start-page: 1787 issue: 9 year: 1999 end-page: 1791 article-title: A Receding Horizon Kalman FIR Filter for Discrete Time‐Invariant Systems publication-title: IEEE Trans. Autom. Control – volume: 47 start-page: 1663 issue: 10 year: 2002 end-page: 1676 article-title: Moving Horizon Estimation for Hybrid Systems publication-title: IEEE Trans. Automatic Control – year: 1993 – year: 1999 – ident: Key-10.4218/etrij.12.0111.0391-13 doi: 10.1109/TAC.2002.802772 – ident: Key-10.4218/etrij.12.0111.0391-10 doi: 10.1109/9.328818 – ident: Key-10.4218/etrij.12.0111.0391-8 doi: 10.1016/S0005-1098(01)00242-4 – ident: Key-10.4218/etrij.12.0111.0391-9 doi: 10.1109/9.788546 – ident: Key-10.4218/etrij.12.0111.0391-11 doi: 10.1109/9.388677 – ident: Key-10.4218/etrij.12.0111.0391-7 doi: 10.1109/9.788554 |
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| Snippet | In this paper, an error compensation technique for a dead reckoning (DR) system using a magnetic compass module is proposed. The magnetic compass‐based azimuth... In this paper, an error compensation technique for a dead reckoning (DR) system using a magnetic compass module is proposed. The magnetic compass-based azimuth... |
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| SubjectTerms | bias estimation DR/GPS EKF magnetic compass RHKF filter varying bias 전자/정보통신공학 |
| Title | Modified RHKF Filter for Improved DR/GPS Navigation against Uncertain Model Dynamics |
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