A new method to classify electronic devices using a Frequency-Swept Harmonic Radar (FSHR) approach is proposed in this paper. The FSHR approach enables us to utilize the frequency diversity of the harmonic responses of the electronic circuits. Unlike previous studies, a frequency-swept signal with a constant power is transmitted to Electronic Circuits Under Test (ECUTs). The harmonic response to a frequency-swept transmitted signal is found to be distinguishable for different types of ECUTs. Statistical and Fourier features of the harmonic responses are derived for classification. Later, the harmonic characteristics of the ECUTs are depicted in 3D harmonic and feature spaces for classification. Three-dimensional harmonic and feature spaces are composed of the first three harmonics of the re-radiated signal and the statistical or Fourier features, respectively. We extensively evaluate the performance of our novel method through Monte Carlo simulations in the presence of noise.

In this study, we exploit new feature sets to classify electronic devices via harmonic radar. Nonlinear characteristics of the devices are recorded as a response to a frequency-swept signal with constant power. The harmonic characteristics of electronic devices are described by statistical and Fourier feature sets. Contrary to previous studies, statistical and Fourier feature sets are composed of both feature parameters and harmonic information. Exploiting these feature sets provides a good baseline for performance comparison rather than analyzing the classification performance of the harmonics individually. The performance assessment is performed by Monte Carlo simulations.