Utilizing Kalman(EKF) filter to resolve the single point positioning problem using code peudo-range

https://tapchi.humg.edu.vn/en/archives?article=967
  • Affiliations:

    Khoa Trắc địa - Bản đồ và Quản lý đất đai, Trường Đại học Mỏ - Địa chất, Việt Nam

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  • Received: 13th-Dec-2018
  • Revised: 6th-Feb-2019
  • Accepted: 28th-Feb-2019
  • Online: 28th-Feb-2019
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Abstract:

Currently, more than 90% of navigation and mobile mapping applications uses GNSS signal based on the single point positioning principle. It is also a basic problem of satellite positioning. To solve it, we can use the least square principle or Kalman filter method. Least square is a method which has advantages in solving the static objectives problem (such as adjusting the traditional ground network or GNSS geodetic network). Nevertheless, navigation is a kinematic problem with many components which always change over time. This paper introduces the algorithm of Kalman filter which is used to solve the absolute positioning probem using code pseudo-range. Based on the selected formulation system, the authors programmed a computer module to solve the single point positioning problem. The experimental results depict that this computer module can obtain the horizontal accuracy less than 1.5m in case of combining P1 observations and satellite precise ephemeris. In addition, the authors proposed the use of formula to compute weighting of observations by estimating variance due to the influence of error sources on observations, according to the criterias of the Radio Technical Commission for Aeronautics (RTCA)

How to Cite
Nguyen, T.Gia and Pham, Q.Ngoc 2019. Utilizing Kalman(EKF) filter to resolve the single point positioning problem using code peudo-range (in Vietnamese). Journal of Mining and Earth Sciences. 60, 1 (Feb, 2019).

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