This paper derives a general expression for the Cramer-Rao bound (CRB) of wireless localization algorithms using range measurements subject to bias corruption. Specifically, the a priori knowledge about which range measurements are biased, and the probability density functions (pdf) of the biases are assumed to be available. For each range measurement, the error due to estimating the time-of-arrival (TOA) of the detected signal is modeled as a Gaussian distributed random variable with zero mean and known variance. In general, the derived CRB expression can be evaluated numerically. An approximate CRB expression is also derived when the bias pdf is very informative. Using these CRB expressions, we study the impact of the bias distribution on the mean square error (MSE) bound corresponding to the CRB. The analysis is corroborated by numerical experiments.


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    Title :

    Cramer-Rao Bound for Localization with A Priori Knowledge on Biased Range Measurements


    Contributors:
    Tao Wang (author)


    Publication date :

    2012-01-01


    Size :

    1291963 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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