Ambient noise data selection based on the asymmetry of cross-correlation functions for near surface applications

摘要: Abstract Passive surface wave methods utilizing traffic noise have been studied in recent years to estimate shear velocity urban near-surface explorations. Suitable processing scheme is necessary for the emergence of coherent signal, and even account azimuthal effects acquired data. We propose a new ambient data selection technique based on asymmetry cross-correlation functions refine quality complex city environment. The coefficient defined by logarithmic energy ratio casual acausal waves measure correlation asymmetry, two kinds symmetric are taken into establish screening conditions. underlying physics symmetries demonstrated prove feasibility our algorithm. Two numerical tests suggest that bidirectional inline sources adequately highlighted, high anomalies caused offline eliminated method. Furthermore, significances applications time window normalization investigated improve reliability also apply method three-component field from pavement. comparisons between results raw selected confirmed random artifacts can be effectively suppressed, dispersion trends emerge clearly become more convergent toward lower frequency. Finally, concluded practical noise.