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公开(公告)号：US20250054159A1
公开(公告)日：2025-02-13
申请号：US18933733
申请日：2024-10-31
Applicant: L3Harris Technologies, Inc.
Inventor： Mark Rahmes , Jennifer Spicer , Robert Konczynski , Kusay Rukieh , Jody Flieder , Dustin Ellsworth , Michael Fischer , Timothy Bruce Faulkner
Abstract: Systems and methods for detecting anomalies in aviation data communication systems (e.g., air traffic control surveillance systems), include a processor receiving device status information. A variational autoencoder receives and optimizes the device status information and determines whether it qualifies as an anomaly. Optimized device status information is compared to either non-anomalous or anomalous device status data in a latent space of the variational autoencoder. The latent space preferably includes an n-D point scatter plot and hidden vector values. The processor optimizes the device status information by generating a plurality of probabilistic models of the device status information and determining which of the plurality of models is optimal. A game theoretic optimization is applied to the plurality of models, and the best model is used to generate the n-D point scatter plot in latent space. An image gradient sobel edge detector preprocesses the device status information prior to optimization.
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公开(公告)号：US12190525B2
公开(公告)日：2025-01-07
申请号：US17552074
申请日：2021-12-15
Applicant: L3Harris Technologies, Inc.
Inventor： Mark Rahmes , Jennifer Spicer , Robert Konczynski , Kusay Rukieh , Jody Flieder , Dustin Ellsworth , Michael Fischer , Timothy Bruce Faulkner
Abstract: Systems and methods for detecting anomalies in aviation data communication systems (e.g., air traffic control surveillance systems), include a processor receiving device status information. A variational autoencoder receives and optimizes the device status information and determines whether it qualifies as an anomaly. Optimized device status information is compared to either non-anomalous or anomalous device status data in a latent space of the variational autoencoder. The latent space preferably includes an n-D point scatter plot and hidden vector values. The processor optimizes the device status information by generating a plurality of probabilistic models of the device status information and determining which of the plurality of models is optimal. A game theoretic optimization is applied to the plurality of models, and the best model is used to generate the n-D point scatter plot in latent space. An image gradient sobel edge detector preprocesses the device status information prior to optimization.
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3.发明公开公开(公告)号：US20230186482A1
公开(公告)日：2023-06-15
申请号：US17552074
申请日：2021-12-15
Applicant: L3Harris Technologies, Inc.
Inventor： Mark Rahmes , Jennifer Spicer , Robert Konczynski , Kusay Rukieh , Jody Flieder , Dustin Ellsworth , Michael Fischer , Timothy Bruce Faulkner
CPC classification number: G06T7/13 , G06V10/457 , G06V10/462 , G06V10/476 , G06V10/26 , G08G5/0004 , G08G5/0073 , G06T2207/10028
Abstract: Systems and methods for detecting anomalies in aviation data communication systems (e.g., air traffic control surveillance systems), include a processor receiving device status information. A variational autoencoder receives and optimizes the device status information and determines whether it qualifies as an anomaly. Optimized device status information is compared to either non-anomalous or anomalous device status data in a latent space of the variational autoencoder. The latent space preferably includes an n-D point scatter plot and hidden vector values. The processor optimizes the device status information by generating a plurality of probabilistic models of the device status information and determining which of the plurality of models is optimal. A game theoretic optimization is applied to the plurality of models, and the best model is used to generate the n-D point scatter plot in latent space. An image gradient sobel edge detector preprocesses the device status information prior to optimization.
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