A new least-squares registration (NLSR) algorithm is developed to accurately estimate and correct the systematic errors of a data fusion system. First, the two-sensor registration problem is expressed by an averaged least-squares (LS) criterion function of the sensor measurements. The criterion function is optimized by a Newton algorithm. Then, the algorithm is extended to multiple-sensor case. The accuracy of the proposed estimation scheme achieves the Cramer-Rao bound (CRB). Theoretical analysis and simulations are employed to assess the performance of the proposed algorithm.


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    Title :

    New least squares registration algorithm for data fusion


    Contributors:


    Publication date :

    2004-10-01


    Size :

    606222 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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