Resolution enhancement in time-frequency signal processing using inverse methods

The author applies ideas from tomographic imaging to the problem of enhancing the resolution of time-frequency spectrum estimators based on elements of Cohen´s (1966) class of time-frequency distributions. A multiple-least-squares (L₂) deconvolution method is introduced, and reblurring is used to stabilize the method. Multiple window functions are used to simulate tomographic slices. The estimated posterior density weighted (EPDW) algorithm from emission tomography is also applied to this problem, and the results are compared for some simulated signals. It is shown that the EPDW algorithm is superior, offering a higher degree of noise robustness and resolution enhancement