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Integrated Orbit and Attitude Parameter Determination of a Satellite Using Hybrid Nonlinear Filters

Kiani, Maryam | 2014

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  1. Type of Document: Ph.D. Dissertation
  2. Language: Farsi
  3. Document No: 46677 (45)
  4. University: Sharif University Technology
  5. Department: Aerospace Engineering
  6. Advisor(s): Pourtakdoust, Hossein
  7. Abstract:
  8. Rapid growth of space traffic and small satellite systems for current and future space missions have generated new enhanced performance requirements for navigation subsystem. As such, the navigation subsystem is considered as a vital part of all active satellite systems that effectively influences their successful missions. In this regard, the present work is dedicated on the subject of autonomous satellite navigation utilizing nonlinear filters, for which some laboratory experimentations have also been implemented. Generally, advanced orbit and attitude estimation algorithms can effectively compensate for the effect of low cost hardware and sensor packs utilized in microsatellites. In this aspect, development, enhancement, integration and hybridization of nonlinear filters are concentrated in the current dissertation. In addition, two novel filters have been developed with a distinct view against the traditional existing estimation outlook. In the first algorithm, the nonlinear estimation problem is considered as a stochastic optimization process for which an adaptive Gaussian swarm optimization filtering technique is introduced and implemented. The second algorithm combines two criteria of minimum error entropy as well as minimum mean square error to present a new robust and accurate estimator. The exponential stability of the proposed algorithm is also demonstrated. Naturally, the orbit and attitude motion of low Earth satellites under the action of existing multiple perturbations are usually coupled and nonlinear. In this regard, concurrent orbit and attitude determination (COAD) of satellites is attended to investigate the correlation of roto-translational dynamics that in turn helps towards reducing the satellite mass and subsystem budget requirements. The viability and performance of the proposed filters in this subject are verified and demonstrated via Monte Carlo analysis. Finally, as accurate identification of system as well as measurement model parameters have an important role in navigation subsystem performance enhancement, the problem of simultaneous parameter and state estimation of satellites is also considered as a part of the current research
  9. Keywords:
  10. Orbit Determination ; Attitude Determination ; Particle Filter ; Sensor Calibration

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