A novel solution to multi-scale deconvolution of sensor array signals

The authors' model assumes that the data are generated as a convolution of an unknown wavelet with various time-scaled versions of an unknown reflectivity sequence. Their approach relies on exploiting the redundancy in the measurements due to time-scaling. No assumptions are made on the statistical properties of these signals. The deconvolution problem is solved as a quadratic minimization subject to a quadratic constraint. The results are illustrated with a simulation example.<>