DARPA funding brings machine learning to BAE Systems’ Signals Intelligence capabilities - 4 minutes read
DARPA funding brings machine learning to BAE Systems’ Signals Intelligence capabilities
The solution provides a reconfigurable hardware platform for developers to make sense of radio frequency signals in increasingly crowded electromagnetic spectrum environments
BAE Systems has been awarded funding from the Defense Advanced Research Projects Agency (DARPA) to integrate machine-learning (ML) technology into platforms that decipher radio frequency signals. Its Controllable Hardware Integration for Machine-learning Enabled Real-time Adaptivity (CHIMERA) solution provides a reconfigurable hardware platform for ML algorithm developers to make sense of radio frequency (RF) signals in increasingly crowded electromagnetic spectrum environments.
The up to $4.7 million contract, dependent on successful completion of milestones, includes hardware delivery along with integration and demonstration support. CHIMERA's hardware platform will enable algorithm developers to decipher the ever-growing number of RF signals, providing commercial or military users with greater automated situational awareness of their operating environment. This contract is adjacent to the previously announced award for the development of data-driven ML algorithms under the same DARPA program (Radio Frequency Machine Learning Systems, or RFMLS).
RFMLS requires a robust, adaptable hardware solution with a multitude of control surfaces to enable improved discrimination of signals in the evolving dense spectrum environments of the future.
"CHIMERA brings the flexibility of a software solution to hardware," said Dave Logan, vice president and general manager of Command, Control, Communications, Computers, Intelligence, Surveillance, and Reconnaissance (C4ISR) Systems at BAE Systems. "Machine-learning is on the verge of revolutionizing signals intelligence technology, just as it has in other industries."
In an evolving threat environment, CHIMERA will enable ML software development to adapt the hardware’s RF configuration in real time to optimize mission performance. This capability has never before been available in a hardware solution. The system provides multiple control surfaces for the user, enabling on-the-fly performance trade-offs that can maximize its sensitivity, selectivity, and scalability depending on mission need. The system's open architecture interfaces allow for third party algorithm development, making the system future-proof and easily upgradable upon deployment.
Other RF functions, including communications, radar, and electronic warfare, also can benefit from this agile hardware platform, which has a reconfigurable array, front-end, full transceiver and digital pre-processing stage. Work on these phases of the program will take place at BAE Systems' sites in Hudson and Merrimack, New Hampshire, and Dallas, Texas.
Learn more about BAE Systems' SIGINT capabilities here.
Source: Baesystems.com
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Keywords:
DARPA • Machine learning • BAE Systems • Signals intelligence • Reconfigurable computing • Radio frequency • Signal processing • Electromagnetic spectrum • BAE Systems • DARPA • DARPA • Integral • Machine learning • Maximum likelihood estimation • Technology • Radio frequency • Military communications • Machine learning • Real-time computing • Chimera (genetics) • Reconfigurable computing • Algorithm • Sensor • Radio frequency • Radio frequency • Electromagnetic spectrum • Technology demonstration • Chimera (mythology) • Algorithm • Radio frequency • Military communications • User (computing) • Automation • Situation awareness • Software development • Data-driven programming • Markup language • Algorithm • DARPA • Computer program • Radio frequency • Machine learning • System • Robustness (computer science) • Adaptation • Computer hardware • Military communications • Evolution • Chimera (genetics) • Software • Dave Logan (American football) • General manager • Command and control • Command and control • BAE Systems • Machine learning • Signals intelligence • Technology • Evolution • Natural environment • Chimera (genetics) • Software engineering • Computer hardware • Real-time computing • Computer performance • Computer hardware • System • Scalability • System • Application programming interface • Algorithm • Software development • Computer • Future proof • Upgrade • Software deployment • Radio frequency • Subroutine • Communication • Radar • Electronic warfare • Agile software development • Array data type • Compiler • Two-way radio • Digital electronics • Computer program • BAE Systems • Merrimack, New Hampshire • Dallas • BAE Systems • Signals intelligence •
The solution provides a reconfigurable hardware platform for developers to make sense of radio frequency signals in increasingly crowded electromagnetic spectrum environments
BAE Systems has been awarded funding from the Defense Advanced Research Projects Agency (DARPA) to integrate machine-learning (ML) technology into platforms that decipher radio frequency signals. Its Controllable Hardware Integration for Machine-learning Enabled Real-time Adaptivity (CHIMERA) solution provides a reconfigurable hardware platform for ML algorithm developers to make sense of radio frequency (RF) signals in increasingly crowded electromagnetic spectrum environments.
The up to $4.7 million contract, dependent on successful completion of milestones, includes hardware delivery along with integration and demonstration support. CHIMERA's hardware platform will enable algorithm developers to decipher the ever-growing number of RF signals, providing commercial or military users with greater automated situational awareness of their operating environment. This contract is adjacent to the previously announced award for the development of data-driven ML algorithms under the same DARPA program (Radio Frequency Machine Learning Systems, or RFMLS).
RFMLS requires a robust, adaptable hardware solution with a multitude of control surfaces to enable improved discrimination of signals in the evolving dense spectrum environments of the future.
"CHIMERA brings the flexibility of a software solution to hardware," said Dave Logan, vice president and general manager of Command, Control, Communications, Computers, Intelligence, Surveillance, and Reconnaissance (C4ISR) Systems at BAE Systems. "Machine-learning is on the verge of revolutionizing signals intelligence technology, just as it has in other industries."
In an evolving threat environment, CHIMERA will enable ML software development to adapt the hardware’s RF configuration in real time to optimize mission performance. This capability has never before been available in a hardware solution. The system provides multiple control surfaces for the user, enabling on-the-fly performance trade-offs that can maximize its sensitivity, selectivity, and scalability depending on mission need. The system's open architecture interfaces allow for third party algorithm development, making the system future-proof and easily upgradable upon deployment.
Other RF functions, including communications, radar, and electronic warfare, also can benefit from this agile hardware platform, which has a reconfigurable array, front-end, full transceiver and digital pre-processing stage. Work on these phases of the program will take place at BAE Systems' sites in Hudson and Merrimack, New Hampshire, and Dallas, Texas.
Learn more about BAE Systems' SIGINT capabilities here.
Source: Baesystems.com
Powered by NewsAPI.org
Keywords:
DARPA • Machine learning • BAE Systems • Signals intelligence • Reconfigurable computing • Radio frequency • Signal processing • Electromagnetic spectrum • BAE Systems • DARPA • DARPA • Integral • Machine learning • Maximum likelihood estimation • Technology • Radio frequency • Military communications • Machine learning • Real-time computing • Chimera (genetics) • Reconfigurable computing • Algorithm • Sensor • Radio frequency • Radio frequency • Electromagnetic spectrum • Technology demonstration • Chimera (mythology) • Algorithm • Radio frequency • Military communications • User (computing) • Automation • Situation awareness • Software development • Data-driven programming • Markup language • Algorithm • DARPA • Computer program • Radio frequency • Machine learning • System • Robustness (computer science) • Adaptation • Computer hardware • Military communications • Evolution • Chimera (genetics) • Software • Dave Logan (American football) • General manager • Command and control • Command and control • BAE Systems • Machine learning • Signals intelligence • Technology • Evolution • Natural environment • Chimera (genetics) • Software engineering • Computer hardware • Real-time computing • Computer performance • Computer hardware • System • Scalability • System • Application programming interface • Algorithm • Software development • Computer • Future proof • Upgrade • Software deployment • Radio frequency • Subroutine • Communication • Radar • Electronic warfare • Agile software development • Array data type • Compiler • Two-way radio • Digital electronics • Computer program • BAE Systems • Merrimack, New Hampshire • Dallas • BAE Systems • Signals intelligence •