Raytheon Company

H Brown Cribbs, Iii

Danielle J Marchione

Jacob M Miller

A method includes obtaining pairs of in-phase (I) and quadrature (Q) samples associated with a signal to be demodulated. The method also includes providing a set of the I/Q pairs to a trained AI/ML model. The set of the I/Q pairs includes an I/Q pair associated with a symbol being demodulated and at least one I/Q pair associated with at least one prior symbol that has been demodulated. In addition, the method includes using the trained AI/ML model to generate a symbol estimate for the symbol based on the set of the I/Q pairs, where the symbol estimate represents a portion of data that is encoded in the signal.

Demodulation of non-return to zero (NRZ) or other signals using multiple-input artificial intelligence/machine learning (AI/ML) model

A method includes obtaining multiple geolocation measurements, where each geolocation measurement is generated using cross-ambiguity function (CAF) detection. The geolocation measurements are associated with at least one signal from at least one signal source and received by multiple receivers. The method also includes associating related geolocation measurements to form at least one collection of related geolocation measurements, where each collection of related geolocation measurements is associated with a common one of the at least one signal received by at least some of the receivers. The method further includes performing geolocation using the at least one collection of related geolocation measurements to identify one or more geolocations of the at least one signal source.

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Arlington, VA, United States of America

H Brown Cribbs, Iii