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Proceedings Paper

Noisy Stepped Frequency (NSF) waveform in RF tomography
Author(s): Russell Vela; Lorenzo Lo Monte
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Paper Abstract

Radio Frequency (RF) tomography has been proposed for imaging dielectric and conducting anomalies above-ground. Accordingly, low-cost electromagnetic transmitters are placed arbitrarily above ground, surrounding a large area of interest. In a preliminary stage, sensors identify their position, orientation, and time reference. Subsequently, a transmitter radiates a known waveform. The probing wave impinges upon a target (represented in terms of dielectric or conducting anomaly), thus producing scattered elds. Spatially distributed receivers collect samples of the total electric eld, remove noise, clutter and the direct path, and store the information concerning only the scattered eld. In the next iteration, a dierent transmitter is activated, or dierent wave- forms are used. Then, the collected data is typically relayed to a centralized location for processing and imaging. To ensure persistent sensing, fast back-propagation algorithms are implemented (either involving correlation or multiplication by a hermitian matrix). Resolution using back-propagation is aected by the sidelobe structure of the ambiguity function of the wave. Clearly, Linearly Stepped Frequency (LSF) waveform requires the lowest instantaneous bandwidth, but produces poor correlation properties. On the converse, Noise waveforms exhibit the idealized thumb-tack ambiguity function but typically require large instantaneous bandwidths. In an eort to exploit the benets of both individual waveforms, a noisy LSF waveform is developed. The NLSF performance, limitation and spectral dominance in reference to RF Tomography, along with its theoretical bounds, will be provided. Reconstructed images from simulated and experimental data will be compared.

Paper Details

Date Published: 3 May 2012
PDF: 11 pages
Proc. SPIE 8361, Radar Sensor Technology XVI, 836116 (3 May 2012); doi: 10.1117/12.921222
Show Author Affiliations
Russell Vela, Univ. of Dayton Research Lab. (United States)
Lorenzo Lo Monte, Univ. of Dayton Research Lab. (United States)

Published in SPIE Proceedings Vol. 8361:
Radar Sensor Technology XVI
Kenneth I. Ranney; Armin W. Doerry, Editor(s)

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