Inertial/Stellar Celestial Navigation can greatly improve position accuracy by correcting gyro drift through stellar observations, but position error still diverges over time due to unobservable accelerometer loop error. With the development of resident space object (RSO) observation method and the improvement of orbit determination accuracy, navigation using RSO observations is becoming increasingly feasible. This paper models the RSO navigation problem as Perspective-n-Point (PnP) problem and proposes that observing more than 6 RSOs can achieve complete solutions for position and attitude. Furthermore, an inertial/stellar/RSO tightly coupled navigation algorithm is proposed, which unifies the RSOs and Stars by introducing the deviation angle of line-of-sight vector. Finally, simulation validation is carried out under dynamic condition with position accuracy of 30 m and attitude accuracy of 5 arcsec(RMS), demonstrating the effectiveness of the proposed algorithm.

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INS/Stellar/RSO Tightly Coupled Celestial Navigation

  • Jiayu Wang,
  • Weiping Yang,
  • Guoliang Yang,
  • Yu Tian,
  • Xiaokun Ding

摘要

Inertial/Stellar Celestial Navigation can greatly improve position accuracy by correcting gyro drift through stellar observations, but position error still diverges over time due to unobservable accelerometer loop error. With the development of resident space object (RSO) observation method and the improvement of orbit determination accuracy, navigation using RSO observations is becoming increasingly feasible. This paper models the RSO navigation problem as Perspective-n-Point (PnP) problem and proposes that observing more than 6 RSOs can achieve complete solutions for position and attitude. Furthermore, an inertial/stellar/RSO tightly coupled navigation algorithm is proposed, which unifies the RSOs and Stars by introducing the deviation angle of line-of-sight vector. Finally, simulation validation is carried out under dynamic condition with position accuracy of 30 m and attitude accuracy of 5 arcsec(RMS), demonstrating the effectiveness of the proposed algorithm.