17978736. MODULAR SYSTEM FOR DETECTING, TRACKING, AND TRANSMITTING TO IDENTIFIED OBJECTS simplified abstract (Anduril Industries, Inc.)

MODULAR SYSTEM FOR DETECTING, TRACKING, AND TRANSMITTING TO IDENTIFIED OBJECTS

Organization Name

Anduril Industries, Inc.

Inventor(s)

Sam El-akkad of Poway CA (US)

Christopher Fischer of Lake Forest CA (US)

Travis Whitaker of Costa Mesa CA (US)

Bryden Pearson of Irvine CA (US)

Todd Berk of Lake Forest CA (US)

Thao Pham of San Diego CA (US)

Jon Hsu of Yorba Linda CA (US)

Cameron Dart of Fountain Valley CA (US)

MODULAR SYSTEM FOR DETECTING, TRACKING, AND TRANSMITTING TO IDENTIFIED OBJECTS - A simplified explanation of the abstract

This abstract first appeared for US patent application 17978736 titled 'MODULAR SYSTEM FOR DETECTING, TRACKING, AND TRANSMITTING TO IDENTIFIED OBJECTS

Simplified Explanation

The abstract describes a modular RF system with directional antennas and machine learning models to monitor and interact with objects in specific directions.

• The RF system includes one or more directional antennas for signal detection and transmission.
• The system is equipped with hardware and software components to enable monitoring and interaction with objects.
• Machine learning models are used to analyze received signals and determine signals to transmit.

Potential Applications

The technology could be applied in:

• Radar systems for tracking objects in specific directions.
• Communication systems for targeted signal transmission.

Problems Solved

The technology addresses issues such as:

• Efficient monitoring and tracking of objects in specific directions.
• Targeted signal transmission to specific locations.

Benefits

The benefits of this technology include:

• Improved accuracy in monitoring and tracking objects.
• Enhanced efficiency in signal transmission.

Potential Commercial Applications

The technology could be commercially used in:

• Military surveillance systems.
• Satellite communication systems.

Possible Prior Art

One possible prior art could be traditional radar systems with fixed antennas for signal detection and transmission.

What are the limitations of the machine learning models used in the RF system?

Machine learning models may have limitations in adapting to new signal patterns or environments, potentially leading to inaccuracies in signal analysis.

How does the modular design of the RF system contribute to its flexibility and scalability?

The modular design allows for easy integration of additional components or antennas, making the system adaptable to different monitoring and interaction requirements.

Original Abstract Submitted

A modular, radio frequency (“RF”) system includes one or more directional antennas and is configured with both hardware and software components to enable the RF system to monitor (e.g., detect or track signals or objects) and/or interact with (e.g., track signals or objects, or transmit signals) objects in particular directions. The RF system includes one or more machine learning models to determine, based on received signals, one or more signals to transmit.