A novel technique for detection and discrimination of artificial objects, such as land mines, pipes, containers, etc., buried in the ground, has been developed and tested. The developed approach utilizes vibration (using seismic or airborne acoustic waves) of buried objects, remote measurements of soil surface vibration (using laser or microwave vibrometers), and processing of the measured vibration to extract mine's "vibration signatures." The technique does not depend upon the material from which the mine is fabricated whether it be metal, plastic, wood, or any other material. It depends upon the fact that a mine is a "container" whose purpose is to contain explosive materials and associated detonation apparatus. The mine container is in contact with the soil in which it is buried. The container is an acoustically compliant article, whose compliance is notably different from the compliance of the surrounding soil. Dynamic interaction of the compliant container and soil on top of it leads to specific linear and nonlinear effects used for mine detection and discrimination. The mass of the soil on top of a compliant container creates a classical mass-spring system with a well-defined resonance response. Besides, the connection between mass (soil) and spring (mine) is not elastic (linear) but rather nonlinear, due to the separation of the soil/mine interface in the tensile phase of applied dynamic stress. These two effects, constituting the mine's vibration signature have been measured in numerous laboratory and field tests, which proved that the resonance and nonlinear responses of a mine/soil system can be used for detection and discrimination of buried mines. Thus, the fact that the mine is buried is turned into a detection advantage. Because the seismo-acoustic technique intrinsically detects buried containers, it can discriminate mines from noncompliant false targets such as rocks, tree roots, chunks of metal, bricks, etc. This was also confirmed experimentally in laboratory and field tests.
The acoustic signature of a footstep is one of several signatures that can be exploited for human recognition. Early research showed the maximum value for the force of multiple footsteps to be in the frequency band of 1-4 Hz. This paper reports on the broadband frequency-dependent vibrations and sound pressure responses of human footsteps in buildings. Past studies have shown that the low-frequency band (below 500 Hz) is well known in the literature, and generated by the force normal to the ground/floor. The seismic particle velocity response to footsteps was shown to be site specific and the characteristic frequency band was 20-90 Hz. In this paper, the high-frequency band (above 500 Hz) is investigated. The high-frequency band of the vibration and sound of a human footstep is shown to be generated by the tangential force to the floor and the floor reaction, or friction force. The vibration signals, as a function of floor coverings and walking style, were studied in a broadband frequency range. Different walking styles result in different vibration signatures in the low-frequency range. However, for the walking styles tested, the magnitudes in the high-frequency range are comparable and independent of walking style.
Buried landmines exhibit complex structural vibrations, which are dependent on interaction between soil and mines as well as on their respective properties. This paper presents experimental and theoretical studies of multimodal vibrations of buried mines and discusses the effects of burial depth and soil properties on dynamics of the soil-mine system. The two-dimensional model of the soil-mine system that accounts for soil-coupled mine's multiple vibration modes and spatial distribution of vibrations over the soil surface is introduced. The model was tested using experiments with the plastic mine simulant. The study reveals that the soil shear stiffness is one of the key governing parameters determining the resonance vibration frequency and the amplitude of the soil-mine system. Burial depth, soil moisture, and consolidation are among factors leading to the increase of the soil shear stiffness, therefore effectively influencing modal vibrations of buried mines.
Stevens Institute of Technology is performing research aimed at determining the acoustical parameters that are necessary for detecting and classifying underwater threats. This paper specifically addresses the problems of passive acoustic detection of small targets in noisy urban river and harbor environments. We describe experiments to determine the acoustic signatures of these threats and the background acoustic noise. Based on these measurements, we present an algorithm for robustly discriminating threat presence from severe acoustic background noise. Measurements of the target's acoustic radiation signal were conducted in the Hudson River. The acoustic noise in the Hudson River was also recorded for various environmental conditions. A useful discriminating feature can be extracted from the acoustic signal of the threat, calculated by detecting packets of multi-spectral high frequency sound which occur repetitively at low frequency intervals. We use experimental data to show how the feature varies with range between the sensor and the detected underwater threat. We also estimate the effective detection range by evaluating this feature for hydrophone signals, recorded in the river both with and without threat presence.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.