Long-time signal processing algorithm for moving targets based on deconvolution two-step matched Fourier transform

The time-varying line spectrum signals from underwater moving targets cause performance degradation in long-duration processing. A method based on matched Fourier transform (TMFT) and two-dimensional deconvolution, called dTMFT, is proposed to address this. The second-order polynomial phase characteristics of the signals are focused on, and a two-step TMFT is used to concentrate energy in frequency and frequency rate dimensions. The TMFT output is then deconvolved using the Richardson-Lucy (R-L) algorithm, effectively suppressing radial sidelobes and background levels. Simulations and real sea trial data processing confirms enhanced target resolution and reduced background levels while maintaining long-duration processing capability.