23 May 2013 Seismic signature analysis for discrimination of people from animals
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Abstract
Cadence analysis has been the main focus for discriminating between the seismic signatures of people and animals. However, cadence analysis fails when multiple targets are generating the signatures. We analyze the mechanism of human walking and the signature generated by a human walker, and compare it with the signature generated by a quadruped. We develop Fourier-based analysis to differentiate the human signatures from the animal signatures. We extract a set of basis vectors to represent the human and animal signatures using non-negative matrix factorization, and use them to separate and classify both the targets. Grazing animals such as deer, cows, etc., often produce sporadic signals as they move around from patch to patch of grass and one must characterize them so as to differentiate their signatures from signatures generated by a horse steadily walking along a path. These differences in the signatures are used in developing a robust algorithm to distinguish the signatures of animals from humans. The algorithm is tested on real data collected in a remote area.
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Thyagaraju Damarla, Thyagaraju Damarla, Asif Mehmood, Asif Mehmood, James M. Sabatier, James M. Sabatier, } "Seismic signature analysis for discrimination of people from animals", Proc. SPIE 8745, Signal Processing, Sensor Fusion, and Target Recognition XXII, 874518 (23 May 2013); doi: 10.1117/12.2014956; https://doi.org/10.1117/12.2014956
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