Recently, the one dimensional (1D) spectral fringe-adjusted joint transform correlation (SFJTC) technique has been proposed as an effective means for performing deterministic target detection in hyperspectral imagery. In addition, different types of sensor data have been proposed in the literature to characterize and detect objects or targets. Some of the recently proposed sensors are accelerometers and laser vibrometers. In this work, we investigate how a laser vibrometer data signature is correlated to any accelerometer based data signature using SFJTC. Toward this end, we applied SFJTC to several data sets of laser velocity vibrometer data and different accelerometer data recorded from a vehicle under different challenging conditions. It was found that all laser vibrometer data correlated equally well with all accelerometer data regardless of the position of the accelerometer under all conditions. This result suggests that laser vibrometric data may be used instead of accelerometric data to uniquely characterize desired objects such as vehicles.

Date Published: 20 April 2016
PDF: 7 pages
Proc. SPIE 9845, Optical Pattern Recognition XXVII, 98450U (20 April 2016); doi: 10.1117/12.2225252

Published in SPIE Proceedings Vol. 9845:
Optical Pattern Recognition XXVII
David Casasent; Mohammad S. Alam, Editor(s)