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The Kalman filter algorithms are computationally intensive, therefore, parallel processing could be an option to meet the timing performance requirements. In this paper detailed research and experimentation have been done for parallel processing of the Kalman filter and the Extended Kalman filter based on operating system and multiple general purpose processors that support shared memory. The time comparison of the various methods is analyzed with respect to real-time spacecraft vehicle parameters estimation and a slight time reduction in the parallel Kaman filter has been observed compared with sequential method © 2005 IEEE.
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