A novel algorithm for radar classification based on Doppler characteristics exploiting orthogonal pseudo-Zernike polynomials

Phase modulation induced by target micro-motions introduces side-bands in the radar spectral signature returns. Time-frequency distributions facilitate the representation of such modulations in a micro-Doppler signature that is useful in the characterization and classification of targets. Reliable micro-Doppler signature classification requires the use of robust features that is capable of uniquely describing the micro-motion. Moreover, future applications of micro-Doppler classification will require meaningful representation of the observed target by using a limited set of values. In this paper, the application of
the pseudo-Zernike moments for micro-Doppler classification is introduced. Specifically, the proposed algorithm consists in the extraction of the pseudo-Zernike moments from the Cadence Velocity Diagram (CVD). The use of pseudo-Zernike moments allows invariant features to be obtained that are able to discriminate the content of two-dimensional matrices with a small number of coefficients. The analysis has been conducted both on simulated and on real radar data, demonstrating the effectiveness of the proposed approach for classification purposes.