Moving source localization using seismic signal processing

Abstract

Accurate localization of a seismic source in a near-field scenario where the distances between sensors and the source are less than a few wavelengths of the generated signal has shown to be a challenging task. Conventional localization algorithms often prove to be ineffective, as near-field seismic signals exhibit characteristics different from the well-studied far-field signals. The current work is aimed at the employment of a seismic sensor array for the localization and tracking of a near-field wideband moving source. In this paper, the mathematical derivation of a novel DOA estimation algorithm—dubbed the Modified Kirlin Method—has been presented in details. The estimated DOAs are then combined using a least-squares optimization method for source localization. The performance of the proposed method has been evaluated in a field experiment to track a moving truck. We also compare the DOA estimation and source localization results of the proposed method with those of two other existing methods originally developed for localization of a stationary wideband source; Covariance Matrix Analysis and the Surface Wave Analysis. Our results indicate that both the Surface Wave Analysis and the Modified Kirlin Methods are effective in locating and tracking a moving truck.