: The technical results contained in this report include: Formulas for optimum processing of complex samples when the sign als has known and unknown phase structure; Formulas for optimum processing of complex sample amplitude, phases, and symmetric phase-differences when the signal has known and unknown phase structure; Formulas for the optimum processing of the frequency domain representation of the signal samples when the signal is narrowband; explicit formulas for processing samples when the statics are modeled by either non- central or central mixture models for which the parameters are estimated or implicit; Processing gain over traditional processing bounds and estimates in terms of model parameters for the above algorithms when the statics are modeled by either non-central or central mixture models; Comparison of processing gain bounds and estimates with performance estimates obtained through simulations for two- and three-state mixture models; Simulation results for averages of the transformed samples; and results for the loss of performance due to target motion for processing at the output of a beamformer.

Adaptive Locally Optimum Processing for Interference Suppression from Communication and Undersea Surveillance Signals

Three receivers are compared for the detection of a known signal in additive ambient underwater noise of seagoing merchant ves- sels. These receivers are: the matched filter, which is the classical lin- ear receiver based on a Gaussian assumption; the soft-limiter, which is the robust receiver when the noise uncertainty is modeled as a mix- ture process with a Gaussian nominal; and the Gaussian-Gaussian mixture likelihood ratio receiver. This last receiver is adaptive in the sense that it is based on a parametric model whose parameters are computed from the actual data. The principal results of this study are that, in terms of the receiving operating curves (ROC), the adaptive receiver performs better than the linear one which, in turn, performs better than the robust soft limiter. This study illustrates the merit of the simple mixture model in adaptive processing for signal detection purposes. Abstract-The reconstruction problem we address is that of working backwards from a spectrogram to a waveform producing it. We de- velop a time-sequential algorithm for reconstruction and investigate its performance as various parameters are changed. Because the algo- rithm is time sequential, memory requirements do not grow linearly with the length of the desired reconstruction. We have found this bounded-memory property important in efficiently using an array pro- cessor to speed up computer simulations requiring reconstruction. Ad- ditionally, a time-sequential bounded-memory, algorithm would be es- sential if a hardware realization intended for continuous operation in real time were eyer to be attempted.

Comparison of Adaptive and Robust Receivers for Time-Iterative Synthesis of a Time-Domain Signal Detection in Ambient Underwater Noise Waveform Having a Desired Spectrogram

D. L. Duttweiler

Papers

Comparison of Adaptive and Robust Receivers for Time-Iterative Synthesis of a Time-Domain Signal Detection in Ambient Underwater Noise Waveform Having a Desired Spectrogram