Over the last ten years progress has been made in developing inverse scattering algorithms that go beyond the range of applicability of the first Born and Rytov approximations. Our efforts have focused on a nonlinear filtering technique which appears at first glance to be straightforward to implement and offer the possibility of recovering strongly scattering structures. Upon applying the method to various simulated and real data sets, its performance has been inconsistent. In this paper we discuss the various numerical concerns that have arisen from executing a nonlinear filter on limited sampled noisy data and clarify the potential advantages and limitations of this approach.
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