Sigma-point Kalman filters for GPS based position estimation - Details

Author：

Bo, Tang (Bo, Tang.) | Pingyuan, Cui (Pingyuan, Cui.) | Yangzhou, Chen (Yangzhou, Chen.) (Scholars：陈阳舟)

Indexed by：

EI Scopus

Abstract：

Stand-alone　GPS　basted　position　estimation　problem　using　GPS　raw　data,　pseudo-range　and　Doppler　shifts　measurements　are　the　concept　of　fusing　noisy　observations.　A　family　of　improved　derivative　nonlinear　Kalman　filters　called　Sigma　Point　Kalman　filter　(SPKF)　are　applied　to　a　nonlinear　model　of　GPS　based　position　estimation　in　this　paper.　Simulations　are　made　to　compare　the　filter　with　the　traditional　Iterative　Least　Square　(ILS)　method　and　extended　Kalman　filter　(EKF)　method,　results　indicate　that　under　same　conditions,　SPKF　has　higher　filtering　accuracy　and　more　stable　estimation　performance.　©　2005　IEEE.

Keyword：

Global positioning system Problem solving Kalman filters Doppler effect Computer simulation Tracking (position)

Author Community：

[ 1 ] [Bo, Tang]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China
[ 2 ] [Pingyuan, Cui]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China
[ 3 ] [Yangzhou, Chen]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China