This paper describes the first feasibility study using dynamic time warping (DTW) to classify the micro-Doppler signature (μ-DS ) for radar automatic target recognition (ATR). Real radar data has been used in the testing, and the performance of the DTW classifier has been benchmarked against the conventional k-nearest neighbour (k-NN) algorithm. The basic theory behind the μ-DS is introduced, and aspects of the phenomenon that could cause difficulties for classifiers are highlighted. We explain how DTW can cope with these difficulties and achieve successful classification of three target classes. A correct classification rate exceeding 0.8 has been achieved, leading to the conclusion that this technique shows considerable promise for application in radar ATR systems.


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    Title :

    Radar Micro-Doppler Signature Classification using Dynamic Time Warping


    Contributors:


    Publication date :

    2010-07-01


    Size :

    4345069 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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