摘要
The Periodicallg Moving Part Modulation (PMPM) for the moving parts in targetprovides important signatures for target recognition. However, most radars operate inmultiple-target mode and can only get discontinuous clusters of the returned pulses, which makes itextremely difficult to extract PMPM signature from the echoes. This paper puts forward theAlternative Iteration Deconvolution based on Minimum Entropy criteria (AIDME) for spectralestimation of extended target's echoes, utilizing the special feature that the PMPM spectra usuallyhave simple structures. Experimental results show that this method can effectively eliminate thesevere influence caused hy the convolution kernel and gain a satisfactory spectral estimation thatapproaches to the true spectrum.
The Periodicallg Moving Part Modulation (PMPM) for the moving parts in targetprovides important signatures for target recognition. However, most radars operate inmultiple-target mode and can only get discontinuous clusters of the returned pulses, which makes itextremely difficult to extract PMPM signature from the echoes. This paper puts forward theAlternative Iteration Deconvolution based on Minimum Entropy criteria (AIDME) for spectralestimation of extended target's echoes, utilizing the special feature that the PMPM spectra usuallyhave simple structures. Experimental results show that this method can effectively eliminate thesevere influence caused hy the convolution kernel and gain a satisfactory spectral estimation thatapproaches to the true spectrum.
