Current correlation technology revolves around likelihood ratio theory and the assignment algorithm to resolve association ambiguities. While a Bayes classifier is the best classifier, all classifiers potentially lead to classification errors. In this paper, we examine the track association and sensor registration problem in terms of several correlation classifiers, the most famous of these being the matched filter. Thus, we seek some unification between the term correlation with regards to track association and correlation with regards to pattern recognition. We examine several classes of correlation classifiers and discuss their application to the generation of a SIP when coupled with a sensor registration algorithm. The availability of these techniques on optical processing platforms is an obvious benefit to track association. We briefly discuss the implementation of some of these techniques on a commercial frequency plane correlator.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Filter construction for topological track association and sensor registration


    Contributors:
    Stanek, C.J. (author) / Javidi, B. (author) / Skorokhod, A. (author) / Yanni, P. (author)


    Publication date :

    2002


    Size :

    17 Seiten, 12 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English






    Clustering Track Pairs for Multi-Sensor Track Association

    IMRAN SYED ASIF | European Patent Office | 2023

    Free access

    Assignment costs for multiple sensor track-to-track association

    Kaplan, L. / Bar-Shalom, Y. / Blair, W. | IEEE | 2008