Fourier-Bessel transform and time-frequency-based approach for detecting manoeuvring air target in sea-clutter

In many applications, it may be desired to decompose a non-stationary signal into its individual components. If spectral components of the non-stationary signal do not overlap in the frequency domain then Fourier transform can be used to decompose the non-stationary signal. Fourier transform fails to decompose the non-stationary signal if its spectral components overlap in the frequency domain. In this study, the authors propose Fourier-Bessel transform and the time-frequency analysis in conjunction with the fractional Fourier transform (FB-TF) method for the separation of multi-component non-stationary signal whose components overlap in both time and/or frequency domains. The efficiency of the proposed method is compared with one of the traditional decomposition methods like EMD. The proposed approach is applied to both simulated and experimental radar data. Results demonstrate the effectiveness of the proposed method for non-stationary signal separation and for detecting manoeuvring target in heavy sea-clutter environments. The improvement factor and clutter attenuation are calculated and used to compare the performance of the EMD and the FB-TF methods in suppressing the sea-clutter and enhancing target detection. The proposed method can be used as a potential tool for detecting and enhancing the low observable manoeuvring air targets in the sea-clutter environment.