EXTREMELY-LOW-FREQUENCY MODELING IN LOSSY MEDIA USING FDTD WITH APPLICATION IN SEA-FLOOR CHARACTERIZATION

In this paper we discuss a low-frequency computational procedure based on the Finite Difference Time Domain (FDTD) algorithm, for numerical modeling of electromagnetic scattering by buried objects in sediment l ayers under sea water. The FDTD algorithm is found to be accurate for modeling buried objects in sediment layers tens of meters away from a constant current dipole source of 1A in sea water. For validation of t he low-frequency FDTD modeling, the computed FDTD results are compared with those calculated by using analytic expressions and integral,equa tion techniques. In this paper we also present a technique for detecti ng conductivity anomalies in sediments, e.g., a buried object in sedim entary layers under sea water, by using the neural network approach. T he electric field values are used as the inputs to the neural network and the associated conductivities are used as the targets. The neural network is then trained to associate these conductivities and field va lues. It is shown in this paper that a trained neural network can be u sed to estimate the conductivity of new objects that have not been emp loyed to train the network.