Extraction of complex resonances associated with buried targets

Abstract

Early time returns affect the estimation of complex natural resonance (CNR) frequencies associated with a target. This is especially true when there is a small separation between the early time returns and the late time response of the target and the CNRs are low Q mechanisms. A good example of this scenario is antipersonnel mines. In this situation, it helps to remove the early time returns from the total scattered field. A new technique to accomplish this is presented here. Using some numerical data and some experimental data, it is demonstrated that this technique is very effective in removing the early time returns. The modified scattered field data then yields better estimates of CNR frequencies.

Principal component analysis and Akaike information criterion based image enhancement for ground penetrating radar

“…Frequency domain feature based approach [8] fails to detect target, if the target and the clutter have overlapping response in time domain. Some other image enhancement schemes consist of spatial modeling and subtracting the peak response due to the response of the airground interface [9], [10]. However, these require accurate modeling of air-ground interface (which is not practically possible) and the performance of these methods degrade for non-homogenous medium [9], [10].…”

“…Some other image enhancement schemes consist of spatial modeling and subtracting the peak response due to the response of the airground interface [9], [10]. However, these require accurate modeling of air-ground interface (which is not practically possible) and the performance of these methods degrade for non-homogenous medium [9], [10]. Another clutter reduction scheme uses adaptive linear prediction theory (to cancel the non stationary clutter environment) [11], however drawback is that, it makes the assumption of Gaussian noise for the prediction error [11].…”

Information Theoretic Criterion Based Clutter Reduction for Ground Penetrating Radar

“…However, these require accurate modeling of air-ground interface (which is not practically possible) and the performance of these methods degrade for non-homogenous mediums [9,10]. Another clutter reduction scheme uses adaptive linear prediction theory (to cancel the non stationary clutter environment) [11], however (its drawback is that) it makes the assumption of Gaussian noise for the prediction error [11].…”

“…Some other clutter reduction schemes consist of spatial modeling and subtracting the peak response due to the response of the airground interface [9,10]. However, these require accurate modeling of air-ground interface (which is not practically possible) and the performance of these methods degrade for non-homogenous mediums [9,10].…”

Landmines Ground-Penetrating Radar Signal Enhancement by Digital Filtering

“…Methods vary depending on the chosen approach to model the peak. In [5] and [6], the method is based on peak modeling by a linear combination of complex exponentials whose parameters are estimated by the Prony method. Generally speaking, these methods are based on peak modeling that result from the response of the air-ground interface and eventually from antenna coupling and the subtraction of this modeled peak from the recorded signal.…”