Cross Correlation Singularity Power Spectrum Theory and Application in Radar Target Detection Within Sea Clutters

The cross correlation power spectrum of multiple signal sequences in the singularity domain is studied in this paper. With theoretical derivation and quantitative analysis, the cross correlation singularity power spectrum (CSPS) distribution theory is proposed. Developed from correlation function (CF), spectrum CF (SCF), singularity power spectrum (SPS), and multifractal cross correlation analysis, the CSPS can be applied for the correlation analysis of multiple fractal time series. In this paper, the CSPS is rigorously derived based on SPS and SCF, and is verified with classical multifractal time series. Furthermore, a target detection method based on the proposed CSPS method is also proposed. The proposed methodology is tested on sea clutters, both with and without target, from the Ice Multiparameter Imaging X-Band radar data set. The simulation results indicate that the target detection based on CSPS performs better than conventional multifractal spectrum methods, and can achieve almost 100% detection probability of detecting low-observable targets within sea clutters.

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