Bae Systems Information and Electronic Systems Integration Inc.

Matthew Anderson

Brandon P Hombs

John A Tranquilli, Jr

Scott A Kuzdeba

Bradley J Bell

Daniel Massar

Brandt J Lomen

Steven R Grimes

A method, system, and computer readable medium for performing a generalized angle-based tracker for a target determines angle-based information from a target signal, and initializes a Stationary Surface Filter (SSF), a Moving Surface Filter (MSF), and a Pseudorange Kalman Filter (PKF) with the angle-based information. Next, the SSF and MSF are scored by the PKF. If the information is associated, then the SSF, MSF, and PKF are updated. It is determined if at least one plausible Constituent Kalman Filter (CKF) exists for the SSF and MSF. If at least one CKF exists for the SSF and no CKF exists for the MSF, then the target is stationary surface; if at least one CKF exists for the MSF and no CKF exists for the SSF, then the target is moving surface; if no CKF exists for both the SSF and the MSF, then the target is moving airborne.

Generalized angle-based tracker (GABT)

A closed loop, real-time, cognitive Electronic Warfare (EW) system without a threat database includes an EW receiver for receiving radar threat signals; a Signal Analysis and Characterization module; a Pulse to Emitter Association sub-module; a Function De-interleaving Classifier sub-module; a Threat Behavior Model sub-module; a Countermeasures Synthesis module; a Capability, Severity, and Intent sub-module; a Countermeasure Selection sub-module; a Countermeasure Optimization sub-module; a Countermeasures Effectiveness Assessment module; a Resource Management module; and an EW transmitter.

Radar electronic countermeasures without a threat database

A method is provided for correlating signals. The method includes receiving a plurality of data vectors representing a plurality of signals. The method further includes determining, for each of the data vectors, a first set of correlation coefficients, where each of the correlation coefficients in the first set is based on a direct cross-correlation between each of the data vectors. The method further includes calculating an average of the first set of correlation coefficients, and determining, for each of the data vectors, a second set of correlation coefficients, where each of the correlation coefficients in the second set are based on an indirect cross-correlation between each of the data vectors and the average of the first set of correlation coefficients. The method further includes detecting a correlation between at least two of the data vectors based on the second set of correlation coefficients.

Signal correlation estimator and detector

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Mont Vernon, NH, United States of America

Matthew Anderson