Achieving Full-Spectrum Dominance with DRFM-based Technology

Overview

The white paper titled "Achieving Full-Spectrum Dominance" emphasizes the necessity for advanced radar testing and emulation in electronic warfare (EW) to maintain military superiority in the increasingly contested electromagnetic spectrum. Full-spectrum dominance refers to a military entity's ability to control the battlespace, which includes capturing, detecting, and manipulating signals from both friendly and adversarial radars.

As technology rapidly advances, the complexity of EW has escalated, making it challenging to keep pace with adversaries. The paper highlights the critical need for effective and efficient radar testing and pilot training solutions to address this complexity. Modern EW systems play vital roles in protecting pilots by warning them of inbound threats, detecting adversarial radars, and deceiving enemies through altered radio frequency signals.

The introduction of cognitive electronic warfare (cognitive EW) systems, which leverage artificial intelligence (AI) and machine learning (ML), presents both opportunities and challenges. While these technologies can enhance capabilities, they also introduce issues related to reliability and transparency. Unlike traditional rules-based algorithms, neural networks operate as "black boxes," making their decision-making processes less interpretable and predictable.

To effectively train pilots, the paper advocates for enhanced realism in training scenarios, utilizing digital radio frequency memory (DRFM) technology to accurately emulate adversarial radar jamming capabilities. This approach allows pilots to practice against realistic threats, improving their skills in recognizing and responding to jamming and spoofing.

Ultimately, the white paper underscores the importance of integrating advanced testing and training assets to keep up with cognitive EW advancements. By doing so, military forces can ensure they are prepared to face current and future threats in a rapidly evolving technological landscape.