SkyRadar Blog

FreeScopes AI enables engineers to build and deploy AI for radar and sensor data without coding. A short demonstration shows rapid object classification in practice.

With the release of FreeScopes AI 1, SkyRadar introduces a structured framework for applying artificial intelligence to radar-based target detection and classification. The system is designed to bridge the gap between raw radar signals and operationally relevant insight, following a transparent and reproducible processing chain.

This article discussed why AI skills are critical for ATSEP and radar operators, and how SkyRadar’s FreeScopes AI delivers hands-on training for future-ready qualification.

In light of the rapidly changing geopolitical landscape, Europe is taking bold steps to reinforce its defense readiness—its Verteidigungsfähigkeit. This strategic pivot demands more than just modernized equipment; it calls for innovation and comprehensive qualification of military personnel. SkyRadar is ready to play its part.

Air traffic control (ATC) is the backbone of modern aviation, ensuring safety, efficiency, and seamless coordination in increasingly crowded skies. As AI reshapes the landscape of radar systems, ATC academies must adapt their training programs to prepare Air Traffic Safety Electronics Personnel (ATSEP) for the challenges and opportunities ahead. The FreeScopes Environment offers a comprehensive AI training solution designed to future-proof ATC operations.

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.

The integration of Artificial Intelligence (AI) in Air Traffic Management (ATM) is rapidly transforming the way airspace is monitored, optimized, and secured. However, for AI to be effectively implemented in ATC (Air Traffic Control) and ATSEP (Air Traffic Safety Electronics Personnel) operations, a centralized data and cloud architecture is essential.

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.