View source for 20240037426. AUTOMATIC DEPENDENT SURVEILLANCE BROADCAST (ADS-B) SYSTEM PROVIDING ANOMALY DETECTION AND RELATED METHODS simplified abstract (Eagle Technology, LLC)

=AUTOMATIC DEPENDENT SURVEILLANCE BROADCAST (ADS-B) SYSTEM PROVIDING ANOMALY DETECTION AND RELATED METHODS=


==Organization Name==

[[:Category:Eagle Technology, LLC|Eagle Technology, LLC]]


[[Category:Eagle Technology, LLC]]

==Inventor(s)==

[[:Category:MARK D. Rahmes of MELBOURNE FL (US)|MARK D. Rahmes of MELBOURNE FL (US)]][[Category:MARK D. Rahmes of MELBOURNE FL (US)]]

[[:Category:KEVIN L. Fox of PALM BAY FL (US)|KEVIN L. Fox of PALM BAY FL (US)]][[Category:KEVIN L. Fox of PALM BAY FL (US)]]

[[:Category:GRAN Roe of MELBOURNE FL (US)|GRAN Roe of MELBOURNE FL (US)]][[Category:GRAN Roe of MELBOURNE FL (US)]]

[[:Category:CHRISTOPHER JASON Berger of LEESBURG VA (US)|CHRISTOPHER JASON Berger of LEESBURG VA (US)]][[Category:CHRISTOPHER JASON Berger of LEESBURG VA (US)]]

[[:Category:RALPH Smith of OAK HILL VA (US)|RALPH Smith of OAK HILL VA (US)]][[Category:RALPH Smith of OAK HILL VA (US)]]

[[:Category:TIMOTHY B. Faulkner of PALM BAY FL (US)|TIMOTHY B. Faulkner of PALM BAY FL (US)]][[Category:TIMOTHY B. Faulkner of PALM BAY FL (US)]]

[[:Category:ROBERT Konczynski of MELBOURNE FL (US)|ROBERT Konczynski of MELBOURNE FL (US)]][[Category:ROBERT Konczynski of MELBOURNE FL (US)]]

[[:Category:KEVIN R. Niewoehner of STAFFORD VA (US)|KEVIN R. Niewoehner of STAFFORD VA (US)]][[Category:KEVIN R. Niewoehner of STAFFORD VA (US)]]

==AUTOMATIC DEPENDENT SURVEILLANCE BROADCAST (ADS-B) SYSTEM PROVIDING ANOMALY DETECTION AND RELATED METHODS - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240037426 titled 'AUTOMATIC DEPENDENT SURVEILLANCE BROADCAST (ADS-B) SYSTEM PROVIDING ANOMALY DETECTION AND RELATED METHODS

==Simplified Explanation==

The patent application describes an automatic dependent surveillance broadcast (ADS-B) system that includes multiple ADS-B terrestrial stations. Each station consists of an antenna and wireless circuitry with a station gain pattern. The system also includes a controller with a variational autoencoder (VAE) that compresses the station pattern data from the terrestrial stations, creates a normal distribution of the compressed data in a latent space of the VAE, and decompresses the compressed station pattern data. The controller further includes a processor that processes the decompressed station pattern data using different probabilistic models selected based on a game theoretic reward matrix. The processor determines anomalies from the processed data and generates alerts based on the detected anomalies.

* The system includes multiple ADS-B terrestrial stations with antennas and wireless circuitry.
* A controller with a variational autoencoder (VAE) compresses and decompresses the station pattern data.
* The VAE creates a normal distribution of the compressed data in a latent space.
* A processor processes the decompressed data using different probabilistic models based on a game theoretic reward matrix.
* Anomalies are determined from the processed data.
* Alerts, such as station-specific alerts, are generated based on the detected anomalies.

Potential Applications:
* Air traffic control: The ADS-B system can be used for monitoring and managing air traffic by detecting anomalies in station pattern data and generating alerts for potential issues or threats.
* Aviation safety: The system can contribute to enhancing aviation safety by identifying abnormal patterns in ADS-B data and providing timely alerts for potential risks or malfunctions.
* Aircraft tracking: By analyzing ADS-B data from multiple terrestrial stations, the system can help track and monitor the movement of aircraft, ensuring accurate and reliable information for air traffic management.

Problems Solved:
* Detection of anomalies: The system addresses the challenge of identifying anomalies in ADS-B station pattern data by utilizing a variational autoencoder and probabilistic models.
* Timely alerts: By generating alerts based on the determined anomalies, the system enables prompt response to potential issues or threats in air traffic.

Benefits:
* Improved air traffic management: The system's ability to detect anomalies and generate alerts helps enhance the efficiency and safety of air traffic control operations.
* Enhanced aviation safety: By monitoring and analyzing ADS-B data, the system contributes to identifying potential risks or malfunctions, thereby improving overall aviation safety.
* Accurate aircraft tracking: The system's utilization of multiple terrestrial stations and pattern data analysis ensures accurate and reliable tracking of aircraft movements.


==Original Abstract Submitted==

an automatic dependent surveillance broadcast (ads-b) system may include a plurality of ads-b terrestrial stations, with each ads-b terrestrial station comprising an antenna and wireless circuitry associated therewith defining a station gain pattern. the system may further include a controller including a variational autoencoder (vae) configured to compress station pattern data from the plurality of ads-b terrestrial stations, create a normal distribution of the compressed data in a latent space of the vae, and decompress the compressed station pattern data from the latent space. the controller may also include a processor coupled to the vae and configured to process the decompressed station pattern data using a probabilistic model selected from among different probabilistic models based upon a game theoretic reward matrix, determine an anomaly from the processed decompressed station pattern data, and generate an alert (e.g., a station specific alert) based upon the determined anomaly.



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