The use of iterative deconvolution for scattering function identification

Abstract

A deconvolution technique utilized in image restoration is applied to the problem of estimating the scattering function of a communication channel. Under wide sense stationary and uncorrelated scattering (WSSUS) conditions, the expected matched filter output is equal to the two-dimensional convolution of the scattering function with the ambiguity function of the interrogating waveform. This convolution process introduces a known blur, the ambiguity function of the transmitted signal, which can be partially removed using a constrained iterative deconvolution technique. A preprocessed matched filter output is used to lessen the amount of unwanted additive noise that is incorporated into the deconvolution process. In the no-constraint case, it is equivalent to the practice of performing a pseudoinversion using a truncated singular value decomposition (SVD). This particular preprocessed image effectively combines the truncated SVD and Van Cittert deconvolution schemes.

A New Approach for Time Reversal Communication over Doubly Spread Channels

“…Hence the CAF plane cannot well represent the distinct paths which are required by path-based receivers, and resolution improvement or extra path selection criterion is necessary. To improve the delay-Doppler resolution, iterative methods for deconvolution of 2D signals or images have been investigated [14,15].…”

Rapid estimation of the range-doppler scattering function

“…Under wide sense stationary and uncorrelated scattering (WSSUS) conditions, the scattering function completely describes the second-order statistics of the channel. It can be viewed as a density function giving the average power modulation as a function of delay and Doppler [1]. The scattering function (SF) is typically defined as being independent of the transmitted signal.…”

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