Dynamic Positioning Filter of Global Position System with Recursive Input Estimation Method Application in Navigation System
碩士 === 國防大學理工學院 === 兵器系統工程碩士班 === 99 === Global positioning systems (GPS)are used to establish the movement models of military vehicles. The Kalman filter, input estimation (IE) and carrier signal recursive dynamic positioning are now commonly used in state estimation. The Kalman filter measurement-...
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Other Authors: | |
Format: | Others |
Language: | zh-TW |
Published: |
2011
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Online Access: | http://ndltd.ncl.edu.tw/handle/03027598845342149445 |
Summary: | 碩士 === 國防大學理工學院 === 兵器系統工程碩士班 === 99 === Global positioning systems (GPS)are used to establish the movement models of military vehicles. The Kalman filter, input estimation (IE) and carrier signal recursive dynamic positioning are now commonly used in state estimation. The Kalman filter measurement-based rules are problematic in the the face of non-linear systems, thus limiting using this method will be limited. This paper replaces the linear Kalman filter with an Extended Kalman Filter, EKF that uses the Input Estimation method as the nonlinear state input estimation model. The results show that the input estimation method is better by improving the estimation accuracy in estimating the unknown velocity acceleration, vehicle out of position trajectory and velocity estimation. The arrival time and location of military vehicles can be accurately estimated. Under accident conditions the response time and search range can be shortened.
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