Automated Detection, Extraction, and Measurement of Regional Surface Waves

Abstract

 — Our goal is to develop and test an effective method to detect, identify, extract, and quantify surface wave signals for weak events observed at regional stations. We describe an automated surface wave detector and extractor designed to work on weak surface wave signals across Eurasia at intermediate periods (8 s–40 s). The method is based on phase-matched filters defined by the Rayleigh wave group travel-time predictions from the broadband group velocity maps presented by Ritzwoller and Levshin (1998) and Ritzwoller et al. (1998) and proceeds in three steps: Signal compression, signal extraction or cleaning, and measurement. First, the dispersed surface wave signals are compressed in time by applying an anti-dispersion or phase-matched filter defined from the group velocity maps. We refer to this as the `compressed signal.' Second, the surface wave is then extracted by filtering `noise' temporally isolated from the time-compressed signal. This filtered signal is then redispersed by applying the inverse of the phase-matched filter. Finally, we adaptively estimate spectral amplitude as well as group and phase velocity on the filtered signal. The method is naturally used as a detector by allowing origin time to slide along the time axis. We describe preliminary results of the application of this method to a set of nuclear explosions and earthquakes that occurred on or near the Chinese Lop Nor test site from 1992 through 1996 and one explosion on the Indian Rajasthan test site that occurred in May of 1998.