This chapter focuses on the development and enhancement of autonomous space navigation. To meet the desired accuracy requirements of autonomous space navigation subsystems using low‐cost microelectromechanical systems (MEMS) technology, advanced algorithms with a higher computational burden must be developed and exploited. The chapter investigates concurrent orbit and attitude determination (COAD). COAD greatly reduces the cost and weight of the navigation and control subsystems for small satellites. The chapter discusses sensor calibration and a good knowledge of dynamic system parameters that affect the estimation accuracy, and the problems of simultaneous AD, parameter identification (PI) and measurement system calibration (MSC). The effect of various system and sensor parameters on the observability and estimation accuracy is analysed. It is worth mentioning that the filter tuning is of significance in estimation accuracy, which means that good filter tuning can provide a more precise state estimation in a wide range of acceptable system and mission scenarios.


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    Title :

    Autonomous Space Navigation Using Nonlinear Filters with MEMS Technology


    Contributors:


    Publication date :

    2017-04-03


    Size :

    32 pages




    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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