SkyRadar Blog

In today’s rapidly evolving threat landscape, the ability to counter electronic warfare and ensure accurate radar operations is paramount for military forces. AI-driven radar systems offer a transformative edge in detecting, classifying, and localizing targets, even under conditions of severe interference. The FreeScopes Environment provides military academies with the tools to train radar officers in these advanced technologies, ensuring readiness for modern defense challenges.

In this article, we will explore the deployment of the Spot Jamming DetectionNet into the FreeScopes Environment, showcasing its ability to detect targets and determine their exact positions under challenging jamming conditions.

In this article we will delve into the architecture, features, and training process of the Spot Jamming DetectionNet developed for the FreeScopes environment. This specialized model is designed to detect spot jamming in radar systems and accurately localize targets, even under challenging conditions of intentional interference.

In this article, we will explore the deployment of our trained TargetClassificationNet into the FreeScopes Platform and demonstrate its effectiveness in real-time target classification.

Radar systems face various threats from electronic warfare (EW), with radar jamming being one of the most effective ways to disrupt their performance. Through techniques like barrage jamming, spot jamming, and deception jamming, adversaries can compromise the radar’s ability to detect and track targets. SkySim’s EW Extension provides an advanced simulation platform where users can explore these jamming techniques and learn how to counter them with electronic counter-countermeasures (ECCM), supported by FreeScopes Disturbance Filtering & Analysis.

Mastering the application of artificial intelligence (AI) in radar technology is becoming an essential skill for Air Traffic Safety Electronics Personnel (ATSEP) and military radar operators. By understanding the intricacies of AI-driven radar systems, trainees can develop the expertise needed to enhance target detection, localization, and classification—key components of modern air traffic management and defense strategies. The FreeScopes platform offers a unique, hands-on approach to achieving these learning outcomes through its sophisticated model architecture, which we will outline in this article.

Radar technology plays a critical role in air traffic control (ATC) and military operations, ensuring safety, efficiency, and strategic decision-making. The integration of artificial intelligence (AI) into radar systems is transforming these fields, offering enhanced capabilities in target detection, classification, and localization—even under challenging conditions such as electronic interference. This article summarizes the key advancements demonstrated in our forthcoming series of articles and videos, emphasizing their relevance to Air Traffic Safety Electronics Personnel (ATSEP) and military radar officers.

Training in electronic warfare and radar technology has evolved significantly. For military academies and defense institutions, the ability to combine live radar systems, digital signal processing, and advanced countermeasure algorithms within a single, integrated environment is crucial. SkyRadar’s open and flexible training solutions offer just that, enabling a seamless blend of simulation and live experimentation. This approach not only provides a comprehensive pathway from basic training to advanced research but also supports concurrent learning, distance education, and the integration of emerging technologies like AI. This article explores how SkyRadar’s solutions are redefining defense training and education, providing the tools needed to prepare military personnel for the challenges of modern electronic warfare.

The SASP Deception Detect is a feature in Electronic Warfare. It is implemented in the SkyRadar FreeScopes Training Suite, developed by SkyRadar, building on the foundation of the Enhanced Kalman Disturbance Filter (EKDF).