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公开(公告)号：US20220163629A1
公开(公告)日：2022-05-26
申请号：US16953659
申请日：2020-11-20
发明人： Scott A. Kuzdeba , Matthew Anderson , Brandon P. Hombs , Daniel Massar , John A. Tranquilli, JR.
摘要： 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.
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公开(公告)号：US20240183970A1
公开(公告)日：2024-06-06
申请号：US17971806
申请日：2022-10-24
发明人： Matthew Anderson
IPC分类号： G01S13/72
CPC分类号： G01S13/726
摘要： A method, system, and computer readable medium for performing a scalar agile parameter estimation for continuous-valued univariate parameters to estimate and track a likelihood of a measurement where a parameter distribution domain of an emitter is unknown, comprising: receiving a signal from an emitter source; measuring a feature of said signal; calculating a likelihood of said feature by a feature likelihood tracking model; adding a new parameter source model by creating a node, based on said feature likelihood; establishing a likelihood of a measurement using a measurement likelihood tracking model; starting a new feature track, based on said measurement likelihood; and assigning said feature to a track.
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公开(公告)号：US11808882B2
公开(公告)日：2023-11-07
申请号：US16953659
申请日：2020-11-20
发明人： Scott A Kuzdeba , Matthew Anderson , Brandon P. Hombs , Daniel Massar , John A. Tranquilli, Jr.
摘要： 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.
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公开(公告)号：US11637577B1
公开(公告)日：2023-04-25
申请号：US17584793
申请日：2022-01-26
摘要： 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.
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公开(公告)号：US20240142602A1
公开(公告)日：2024-05-02
申请号：US17965400
申请日：2022-10-13
发明人： Matthew Anderson , Bradley J. Bell
IPC分类号： G01S13/68 , G01S13/526
CPC分类号： G01S13/68 , G01S13/526
摘要： 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.
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公开(公告)号：US20230315806A1
公开(公告)日：2023-10-05
申请号：US17712630
申请日：2022-04-04
发明人： Brandt J. Lomen , Paul Monahan , Matthew Anderson
IPC分类号： G06F17/18
CPC分类号： G06F17/18
摘要： A method of recognizing a pattern in a signal is provided. The method includes receiving, by a processor and at an input, the signal comprising data; converting, by the processor and based on a plurality of features, the data from the signal into a collection of features; identifying, by the processor, one or more feature-to-feature transitions between features in the collection of features; plotting, by the processor, a directed graph of each of the feature-to-feature transitions, wherein each unique feature in the collection of features is represented by a single vertex and each feature-to-feature transition is represented by a directed edge between two vertices weighted by a corresponding number of each of the feature-to-feature transitions; and detecting, by the processor, a pattern in the data by comparing the weight of each of the feature-to-feature transitions in the directed graph to a user-defined threshold.
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