Multiperspective micro-Doppler signature classification

Multiperspective automatic target recognition is considered to assist underlying classifiers by providing more views of the target. For the first time data from netted radar has been analysed for micro-Doppler signature content and a multiperspective dynamic time warping classifier developed. Despite limitation in the multiperspective data, identification is achieved with a probability of correct classification of 0.99. The results are contrasted with a monoperspective approach.