On the use of the Hilbert transform for processing measured CW data

The Hilbert transform is a commonly used technique for relating the real and imaginary parts of a causal spectral response. It is found in both continuous and discrete forms and is widely used in circuit analysis, digital signal processing, image reconstruction and remote sensing. One useful application in the area of high-power microwave (HPM) technology is in correcting measured continuous wave (CW) transfer function data, so as to insure causality in reconstructed transient responses. Another application of the Hilbert transform is in the area of complex spectral estimation using magnitude-only data. Here, the applications of the transform to several specific spectral filtering and phase reconstruction problems are illustrated.>