Modeling and Identification of Hidden Objects in Dynamic Systems using Digital Filters.

Abstract

Digital filters are used for identification, prediction, and modeling of hidden objects in dynamic systems. These filters are Gaussian filter with power spectrum depth estimation, edge detection of the hidden objects as well as constructed 2-D geomagnetic modeling of hidden objects. In this paper, digital filter results are obtained by MATLAB software. Magnetometer instrument is used to collect aeromagnetic data of dynamic systems. Aeromagnetic data are collected from Aswan area in Egypt. MATLAB codes are built to insert data and process this data in user graphic interface (UGI). The estimated depth level of hidden objects in dynamic system is selected via the power spectrum which used to transform processed data in time domain to frequency domain. Then, figure out the hidden objects in shallow and deeper levels. Edge boundary is implemented to obtain hidden objects dynamic system either shallow and deep levels. Edges and clearness hidden objects dynamic systems take out by smoothing total horizontal derivative (THDR) and enhanced total horizontal derivative (ETHDR) filter. The estimation depth of hidden objects and their extension are calculated from the 2-D modeling filter. Also, the 2-D model shown the difference hidden objects dynamic systems types through there magnetic susceptibility. Keywords—Identification, Modeling, Hidden Objects, Aeromagnetic Data, Digital Filters.