Practical aspects of Kalman filtering applications are considered in this chapter, as follows:

    how performance of the Kalman filter can degrade due to computer roundoff errors and alternative implementation methods with better robustness against roundoff;

    how to determine computer memory, word length, and throughput requirements for implementing Kalman filters in computers;

    ways to implement real‐time monitoring and analysis of filter performance;

    the Schmidt–Kalman suboptimal filter, designed for reducing computer requirements;

    covariance analysis, which uses the Riccati equations for performance‐based predictive design of sensor systems; and

    Kalman filter architectures for GPS/INS integration.


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    Title :

    Kalman Filter Engineering


    Contributors:


    Publication date :

    2000-12-15


    Size :

    36 pages




    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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