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In this paper, we propose an application specific instrument (ASIN)-based ultrawideband (UWB) radar system for sludge monitoring from scattering signatures from the bottom of industrial oil tanks. The method is validated by successful estimation of sludge volume in oil tanks using simulated and real data. First, as a demonstration of the conventional system, image reconstruction algorithms are used for tankbottom sludge profile imaging for symmetrical and asymmetrical sludge profiles, where the setup is modeled in finite difference time domain method with reduced dimensions of the tank. A 3-D imaging algorithm is used for the 3-D simulation of real life targets. To get the volume of the sludge, ASIN-based UWB radar system is then applied and its effectiveness is demonstrated. In this framework, to get information about the sludge at the bottom of industrial tank, first, a scheme is proposed to differentiate between two sets of data which correspond to two different set of volumes. This method is validated using a commercial UWB kit, in which, practical experiments were performed. The data obtained is visualized using multidimensional scaling procedure and analyzed. Then, regression analysis using radial basis function artificial neuron network is performed, so that given a particular data, it can be predicted that, to which volume it best corresponds.INDEX TERMS ASIN, UWB, FDTD, MDS, regression analysis, RBF, ANN.