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Detection of vibrating objects in SAR images
Author(s): Francisco Pérez; Balu Santhanam; Thomas Atwood; Ralf Dunkel; Armin W. Doerry; Majeed M. Hayat
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Paper Abstract

The vibratory response of buildings and machines carries key information that can be exploited to infer their operating conditions and to diagnose failures. Moreover, since vibration signatures observed from the exterior surfaces of structures are intrinsically linked to the type of machinery operating inside of them, the ability to monitor vibrations remotely can facilitate the detection and identification of the machinery. Recently, synthetic aperture radar (SAR) has proven to be a versatile tool capable of performing vibrometry and high-precision vibration-estimation algorithms have been developed for reconstructing surface vibration waveforms from SAR images. However, these algorithms tend to be computationally demanding and, in addition, require knowledge of the exact location of the object a priori. This renders their use as unpractical for exploratory applications. This paper focuses on the detection of vibrating objects by exploiting the phase modulation that a vibration causes in the received slow-time SAR data. Two different vibration detection schemes are investigated. The first scheme is data-driven and utilizes features extracted with the help of the discrete fractional Fourier transform (DFrFT) to feed a random-forest detector. The second scheme is model-based, and uses a probabilistic model of the slow-time SAR signal, the Karhunen-Loeve expansion, and a likelihood-ratio detector. The proposed detection algorithms are tested using both simulated and real SAR data. Our results show that both detection schemes can be used to achieve high-performance vibrating-object detectors.

Paper Details

Date Published: 3 May 2019
PDF: 16 pages
Proc. SPIE 11003, Radar Sensor Technology XXIII, 110030P (3 May 2019); doi: 10.1117/12.2517555
Show Author Affiliations
Francisco Pérez, The Univ. of New Mexico (United States)
Balu Santhanam, The Univ. of New Mexico (United States)
Thomas Atwood, The Univ. of New Mexico (United States)
Ralf Dunkel, General Atomics Aeronautical Systems, Inc. (United States)
Armin W. Doerry, Sandia National Labs. (United States)
Majeed M. Hayat, The Univ. of New Mexico (United States)
Marquette Univ. (United States)


Published in SPIE Proceedings Vol. 11003:
Radar Sensor Technology XXIII
Kenneth I. Ranney; Armin Doerry, Editor(s)

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