4 May 2009 Orthogonal sensor suite and the signal-processing algorithm for human detection and discrimination
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The focus of this paper is a review of methods and algorithms for human motion detection in the presence of nonstationary environmental background noise. Human footstep forces on the ground/floor generate periodic broadband seismic and sound signals envelopes with two characteristic times, T1 (the footstep repetition time, which is equal to the time of the whole body periodic vibrations) and T2 (the footstep duration time, which is equal to the time interval for a single footstep from "heel strike" to "toe slap and weight transfer"). Human body motions due to walking are periodic movements of a multiple-degrees-of-freedom mechanical system with a specific cadence frequency equal to 1/T1. For a walking human, the cadence frequencies for the appendages are the same and lie below 3 Hz. Simultaneously collecting footstep seismic, ultrasonic, and Doppler signals of human motion enhance the capability to detect humans in quiet and noisy environments. The common denominator of in the use of these orthogonal sensors (seismic, ultrasonic, Doppler) is a signal-processing algorithm package that allows detection of human-specific time-frequency signatures and discriminates them using a distinct cadence frequency from signals produced by other moving and stationary objects (e.g. vehicular and animal signatures). It has been experimentally shown that human cadence frequencies for seismic, passive ultrasonic, and Doppler motion signatures are equivalent and temporally stable.
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Alexander Ekimov and James M. Sabatier "Orthogonal sensor suite and the signal-processing algorithm for human detection and discrimination", Proc. SPIE 7303, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV, 73030K (4 May 2009); doi: 10.1117/12.818823; https://doi.org/10.1117/12.818823


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