• Title/Summary/Keyword: Kalman FIlter Estimation

Search Result 821, Processing Time 0.019 seconds

Multiple Reference Network Data Processing Algorithms for High Precision of Long-Baseline Kinematic Positioning by GPS/INS Integration (GPS/INS 통합에 의한 고정밀 장기선 동적 측위를 위한 다중 기준국 네트워크 데이터 처리 알고리즘)

  • Lee, Hung-Kyu
    • KSCE Journal of Civil and Environmental Engineering Research
    • /
    • v.29 no.1D
    • /
    • pp.135-143
    • /
    • 2009
  • Integrating the Global Positioning System (GPS) and Inertial Navigation System (INS) sensor technologies using the precise GPS Carrier phase measurements is a methodology that has been widely applied in those application fields requiring accurate and reliable positioning and attitude determination; ranging from 'kinematic geodesy', to mobile mapping and imaging, to precise navigation. However, such integrated system may not fulfil the demanding performance requirements when the baseline length between reference and mobil user GPS receiver is grater than a few tens of kilometers. This is because their positioning/attitude determination is still very dependent on the errors of the GPS observations, so-called "baseline dependent errors". This limitation can be remedied by the integration of GPS and INS sensors, using multiple reference stations. Hence, in order to derive the GPS distance dependent errors, this research proposes measurement processing algorithms for multiple reference stations, such as a reference station ambiguity resolution procedure using linear combination techniques, a error estimation based on Kalman filter and a error interpolation. In addition, all the algorithms are evaluated by processing real observations and results are summarized in this paper.