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


In several applications, it might be desired to decompose a non-stationary signal into its individual parts. If spectral components of the non-stationary signal do not overlap within the frequency domain then Fourier remodel will be used to decompose the non-stationary signal. Fourier transform fails to decompose the non-stationary signal if its spectral parts overlap within the frequency domain. In this study, the authors propose Fourier-Bessel remodel and therefore the time-frequency analysis together with the fractional Fourier rework (FB-TF) methodology for the separation of multi-component non-stationary signal whose elements overlap in each time and/or frequency domains. The potency of the proposed method is compared with one amongst the ancient decomposition methods like EMD. The proposed approach is applied to each simulated and experimental radar data. Results demonstrate the effectiveness of the proposed method for non-stationary signal separation and for detecting manoeuvring target in serious ocean-clutter environments. The improvement issue and muddle attenuation are calculated and used to check the performance of the EMD and the FB-TF ways in suppressing the ocean-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 surroundings.

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