OPTIMIZATION OF SYSTEM PARAMETERS FOR DIFFERENT APPLICATION OF GROUND PENETRATING

Abstract

This work deals with the Optimization of system parameters for different applications like low dielectric materials detection and tree root detection. Currently Step Frequency Continuous Wave (SFCW) Ground Penetrating Radar (GPR) is used to detect subsurface objects. Detection of low dielectric subsurface objects especially when target is at greater depth, detection of such target becomes difficult in the presence of heavy clutter. Tree root detection is another challenge using GPR because very small difference between the dielectric contrast of the tree root and soil. For this purpose, ground penetrating radar has gained considerable importance in the recent years as a promising technology to extract the information of different low dielectric material in the soil using different GPR techniques. The GPR system parameters like - range resolution, maximum probing depth, detection accuracy in terms of location of target specially depth of target, cross range resolution, side lobe suppression and false alarm rate, are to be optimization to improve system performance. Optimization of some of the parameter can be achieved by hardware changes and others need only change in application software. In hardware only recalibration and adjustment in antenna high adjustment to mitigate cable loss and nearby reflections respectively is achieved without change hardware components’ have tried most of the GPR parameter optimization by post signal processing. It is found that signal processing may play important roll while applying it suitably on different types of targets Three targets –a metal sheet a, a cavity and a PVC pipe were buried at different locations and data was collected using a Step Frequency Continuous Wave (SFCW) Radar. Different clutter removal techniques, Normalization, thresholding techniques, weighting function and slicing method is applied on the data to enhance the low dielectric target detection. This experiment was repeated in different soil moisture condition and keeping targets at different depth. After converting SFCW GPR data into time domain I have applied hamming window and time gating to mask side lobe effect and to remove reflection from ground respectively. Subsequently A-scan was plotted to get the range profile. Different thresholding techniques were implemented on the collected data after comparison we found OTSU thresholding method with mean subtraction is efficient in the detection of different targets with different dielectric. The result obtained using above method is further improved by using different weighting functions for the different depth under the ground.