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Improving classification accuracy in through-wall radar imaging using hybrid prony~s and singular value decomposition method

This paper investigates the classification and identification of objects of different material behind a wall. The different materials are defined based on their permittivity, permeability and conductivity and include concrete, wood, glass and metal. A simulation program based on the finite difference time domain (FDTD) (1) method was first used to model the wall and objects behind the wall. An ultra-wideband (UWB) electromagnetic pulse was then transmitted through the wall towards the object. The receiver (on the same side of the wall as the transmitter) recorded the reflected signal which was subsequently analyzed using Prony's method (2). Prony's method decomposes the transient signal into a sum of decaying sinusoids. These sinusoids are represented by their poles and residues. Detailed analysis of the poles and residues was then carried out with the aim of classifying them based on the material medium of the object. It is known that the pole positions tend to become unstable and will shift when there is noise. Therefore, an investigation was also carried out on the effect of noise (with SNR from 20 to 40 dB) on the pole positions. Singular value decomposition (3) was also used to enhance the pole stability in the presence of noise.