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Peter Green

Peter Green is an internationally active manager in Air Traffic Control. He looks back at a technical career in the fields of ATC and also has been in charge of ATCO and ATSEP qualification for many years.

SkyRadar & Artificial Intelligence (Part 5) - pot Jamming DetectionNet Deployment in the FreeScopes Environment

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.

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Radar & Artificial Intelligence (Part 4) - Spot Jamming DetectionNet in FreeScopes Platform (Video)

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.

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Radar & Artificial Intelligence (Part 3) - Deployment of TargetClassificationNet in FreeScopes Environment (Video)

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.

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Electronic Warfare Applications: Simulating Radar Jamming and Countermeasures with SkySim’s EW Extension

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.

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Radar & Artificial Intelligence (Part 2)- Training the Classification Model (Video)

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.

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Human Factors in Radar Operation: Training for Error Mitigation with SkySim

Human factors play a significant role in radar operation, as radar operators must process large amounts of data, make quick decisions, and maintain situational awareness—often under intense pressure. The risk of human error can have serious consequences, particularly in air traffic control (ATC) and military radar operations, where a mistake could lead to safety hazards or mission failure. SkySim offers a practical solution for mitigating human error by simulating high-stress environments and training operators to manage cognitive load, decision-making, and situational awareness.

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Weather Radar and SkySim: Simulating Precipitation, Wind Shear, and More

Weather conditions can significantly impact radar performance, especially in civil aviation and maritime operations. SkySim provides users with the ability to simulate various weather conditions, including precipitation, wind shear, and storms, offering a hands-on approach to understanding how radar systems perform in adverse conditions. This feature is crucial for air traffic controllers, pilots, and radar engineers who need to ensure radar systems function optimally in all weather scenarios.

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Integrating Real-World Radar Data with Simulations: SkySim’s Capabilities


One of the unique features of SkySim is its ability to integrate real-world radar data with simulations, providing an unparalleled training experience. This capability allows users to practice using actual radar signals in a controlled, simulated environment, offering the benefits of live data without the risks and complexities associated with real-world radar operations. This feature is particularly valuable in both civil aviation and defense settings, where radar operators must be able to transition smoothly from training to real-world operations.

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Radar Signal Processing: Understanding Clutter and Its Suppression Techniques

Radar clutter is a significant challenge in radar systems, particularly when attempting to detect legitimate targets in environments filled with unwanted reflections. Clutter comes from objects like buildings, trees, mountains, or even the sea surface, all of which can produce strong radar returns that obscure the objects radar operators actually want to track, such as aircraft or ships. The ability to suppress this clutter is critical for effective radar operation, especially in civil aviation and maritime surveillance.

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