LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Loss Tangent Estimation From GPR Data in Complex Medium Scenarios Using Amplitude and Power Spectrum Centroid Frequency Shift Methods

Photo by sakethgaruda from unsplash

Electromagnetic (EM) losses estimation in complex scenarios lacking subsurface continuous reflectors is challenging. We present here a robust approach based on the centroid frequency shift method and Ricker wavelet as… Click to show full abstract

Electromagnetic (EM) losses estimation in complex scenarios lacking subsurface continuous reflectors is challenging. We present here a robust approach based on the centroid frequency shift method and Ricker wavelet as the input signal, to compute intrinsic (absorption) losses. The centroid-frequency shift is calculated using the amplitude and power spectrum of records, leading to equations that relate the centroid frequency variation in time to the loss tangent (intrinsic losses). First, the approaches are evaluated and compared by implementation to synthetic ground penetrating radar (GPR) data generated with the gprMax simulator, starting from an inhomogeneous material with spatially smooth dielectric variations. Then, they are applied to real GPR data collected on a fractured basaltic lava flow. The retrieved loss tangent values are compared to the total attenuation estimated from the signal amplitude decay, to evaluate the contribution due to scattering phenomena. The proposed analysis is particularly suitable for GPR data collected in planetary environments, since dielectric losses could be used to constrain the oxide composition of the material as well as scattering losses to determine the amount and distribution of subsurface inhomogeneities.

Keywords: frequency shift; centroid frequency; gpr data; loss tangent

Journal Title: IEEE Transactions on Geoscience and Remote Sensing
Year Published: 2023

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.