• Title/Summary/Keyword: double Kalman filter

Search Result 23, Processing Time 0.017 seconds

Real-Time Relative Navigation with Integer Ambiguity

  • Shim, Sun-Hwa;Park, Sang-Young;Choi, Kyu-Hong
    • Bulletin of the Korean Space Science Society
    • /
    • 2008.10a
    • /
    • pp.34.3-34.3
    • /
    • 2008
  • Relative navigation system is presented using measurements from a single-channel global positioning system (GPS) simulator. The objective of this study is to provide real-time relative navigation results as well as absolute navigation results for two formation flying satellites separated about 1km in low earth orbit. To improve the performance, more accurate dynamic model and modified relative measurement model are developed. This modified method prevents non-linearity of the measurement model from degrading precision by applying linearization about the states from absolute navigation algorithm not about a priori states. Furthermore, absolute states are obtained using ion-free GRAPHIC pseudo-ranges and precise relative states are provided using double differential carrier-phase data based on Extended Kalman Filter. The software-based simulation is performed and achieved meter-level precision for absolute navigation and millimeter-level precision for relative navigation. The absolute and relative accuracies at steady state are about 0.77m and 4mm respectively (3D, r.m.s.). In addition, Integer ambiguity algorithm (LAMBDA method) improves simulation performances.

  • PDF

Adaptive Sea Level Prediction Method Based on Harmonic Analysis (조화분석에 기반한 적응적 조위 예측 방법)

  • Park, Sanghyun
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.22 no.2
    • /
    • pp.276-283
    • /
    • 2018
  • Climate changes consistently cause coastal accidents such as coastal flooding, so the studies on monitoring the marine environments are progressing to prevent and reduce the damage from coastal accidents. In this paper, we propose a new method to predict the sea level which can be applied to coastal monitoring systems to observe the variation of sea level and warn about the dangers. Existing sea level models are very complicated and need a lot of tidal data, so they are not proper for real-time prediction systems. On the other hand, the proposed algorithm is very simple but precise in short period such as one or two hours since we use the measured data from the sensor. The proposed method uses Kalman filter algorithm for harmonic analysis and double exponential smoothing for additional error correction. It is shown by experimental results that the proposed method is simple but predicts the sea level accurately.

Precise Relative Positioning for Formation Flying Satellite using GPS Carrier-phase Measurements (GPS 반송파 위상을 사용한 편대비행위성 상대위치결정 연구)

  • Park, Jae-Ik;Lee, Eunsung;Heo, Moon-Beom
    • Journal of the Korean Society for Aeronautical & Space Sciences
    • /
    • v.40 no.12
    • /
    • pp.1032-1039
    • /
    • 2012
  • The present paper deals with precise relative positioning of formation satellites with long baseline in low Earth orbit making use of L1/L2 dual frequency GPS carrier phase measurements. Kinematic approach means to describe the motion of objects without taking its mass/dynamics model into consideration. The advantage of the kinematic approach is that information about dynamics of the system is not applied, which gives more flexibility and could improve the scientific interest of the observations made by the mission. The ionosphere terms, which are not canceled by double differenced measurement equation in the case of the long baseline, are explicitly estimated as unknown parameters by extended Kalman filter. The estimated float ambiguities by EKF are solved by existing efficient integer vector search strategy under integer least square condition. For the integer vector search, we employ well known MLAMBDA. Finally, The feasibility and accuracy of processing scheme are demonstrated using the GPS measurements for two satellites in low Earth orbit separated by baselines of 100 km.