Homomorphic estimation and detection of convolved signals

A new approach to estimating convolved signals, refered to as homomorphic estimation, is presented. This method is the fusion of two well-developed signal processing techniques. The first is the class of homomorphic systems which are characterized by a generalized principle of superposition and allow any linear filter method to be applied when signals are non-additively combined. The second well-known technique is the Wiener estimation filter which has the ability to estimate a desired signal in the presence of additive noise. The theory and realization of the homomorphic system for convolution based on the Fourier transform is developed. Homomorphic estimation system performance is analyzed using digital computer simulation. Homomorphic detection is also presented and is shown to be a useful and easily implemented method.