Radar Micro-Doppler Signature Classification using Dynamic Time Warping.
IEEE T AERO ELEC SYS
This paper describes the first feasibility study using dynamic time warping (DTW) to classify the micro-Doppler signature (mu-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 mu-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.
|Title:||Radar Micro-Doppler Signature Classification using Dynamic Time Warping|
|Keywords:||WORD RECOGNITION, IDENTIFICATION|
|UCL classification:||UCL > School of BEAMS > Faculty of Engineering Science
UCL > School of BEAMS > Faculty of Engineering Science > Electronic and Electrical Engineering
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