Paper
29 September 2004 IIR adaptive filters for detection of gravitational waves from coalescing binaries
Fausto Acernese, Fabrizio Barone, Rosario De Rosa, Antonio Eleuteri, Lara Giordano, Leopoldo Milano
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Abstract
In this paper we propose a new strategy for gravitational waves detection from coalescing binaries, using IIR Adaptive Line Enhancer (ALE) filters. This strategy is a classical hierarchical strategy in which the ALE filters have the role of triggers, used to select data chunks which may contain gravitational events, to be further analyzed with more refined optimal techniques, like the the classical Matched Filter Technique. After a direct comparison of the performances of ALE filters with the Wiener-Komolgoroff optimum filters (matched filters), necessary to discuss their performance and to evaluate the statistical limitation in their use as triggers, we performed a series of tests, demonstrating that these filters are quite promising both for the relatively small computational power needed and for the robustness of the algorithms used. The performed tests have shown a weak point of ALE filters, that we fixed by introducing a further strategy, based on a dynamic bank of ALE filters, running simultaneously, but started after fixed delay times. The results of this global trigger strategy seems to be very promising, and can be already used in the present interferometers, since it has the great advantage of requiring a quite small computational power and can easily run in real-time, in parallel with other data analysis algorithms.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fausto Acernese, Fabrizio Barone, Rosario De Rosa, Antonio Eleuteri, Lara Giordano, and Leopoldo Milano "IIR adaptive filters for detection of gravitational waves from coalescing binaries", Proc. SPIE 5500, Gravitational Wave and Particle Astrophysics Detectors, (29 September 2004); https://doi.org/10.1117/12.553016
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KEYWORDS
Focus stacking software

Signal detection

Signal to noise ratio

Electronic filtering

Digital filtering

Bandpass filters

Binary data

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