The application of the multifractal cross-correlation analysis methods in radar target detection within sea clutter

- We study the parameter settings and the applicabilities of MFXPF, MFXDFA and MFXDMA.
- Do comparative analysis of the artificial time series with different probabilities by these methods.
- Provide a guideline on the choice and parameter settings of the three methods in practice.
- Feasibility test of the target detection method based on the multifractal cross-correlation analysis.
- Summarize the flow chart of radar detecting low-observable target within sea clutters.

Many complex systems generate multifractal time series which are long-range cross-correlated. This paper introduces three multifractal cross-correlation analysis methods, such as multifractal cross-correlation analysis based on the partition function approach (MFXPF), multifractal detrended cross-correlation analysis (MFDCCA) methods based on detrended fluctuation analysis (MFXDFA) and detrended moving average analysis (MFXDMA), which only consider one moment order. We do comparative analysis of the artificial time series (binomial multiplicative cascades and Cantor sets with different probabilities) by these methods. Then we do a feasibility test of the fixed threshold target detection within sea clutter by applying the multifractal cross-correlation analysis methods to the IPIX radar sea clutter data. The results show that it is feasible to use the method of the fixed threshold based on the multifractal feature parameter Δf(α) by the MFXPF and MFXDFA-1 methods. At last, we give the main conclusions and provide a valuable reference on how to choose the multifractal algorithms, the detection parameters and the target detection methods within sea clutter in practice.