Study on acoustic impedance conversion using an optimal chirplet analyzed in chirp SBP raw data

Abstract

Chirplets are wavelets that are transmitted by a chirp sub-bottom profiler (SBP) system. They contain multiple frequencies, typically in the kHz range, and are modulated linearly within a fixed signal length, which makes efficient data analysis possible. However, when chirp SBP field data are recorded, they are usually not raw but have gone through a matching filter and been converted to a Klauder wavelet section or signal envelope. When pre-processed data are reviewed, anomalies can easily be distinguished by sight, and since the data are not raw, reliable quantitative analysis of physical properties is unlikely. Moreover, as chirplets are transmitted through media, their waveforms often become distorted, creating many difficulties in performing analysis of physical properties following data processing. In this study, raw data were used as input to perform an accurate physical analysis of the background media and anomalies at the site of a 600-year-old shipwreck off the coast of Korea. During data processing, an optimal chirplet found through an analysis of the seabed reflection in the raw data was used, instead of the original chirplet set that was applied during acquisition. Conventional data processing was performed in addition to sparse-spike deconvolution and acoustic impedance conversion, using the optimal chirplet found in the raw data. The acoustic impedance results obtained by using the optimal chirplet had a higher level of accuracy when determining the properties of the medium and identifying anomalies, compared to those obtained when the original chirplet was used.