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.

In May 2025, the multinational field exercise Hedgehog 2025 (also known as Siil 2025 in Estonia) brought together more than 16 000 personnel from 12 member states of the North Atlantic Treaty Organisation. With scenarios centered on a simulated incursion across Estonia’s eastern border, the drills were intended to test European deterrence and defense concepts under high pressure (Defence24.com, 17.02.2026).

This article provides an overview of cognitive radar and cognitive electronic warfare, explaining adaptive sensing, decision-making, and the role of algorithms, simulation, and training.

Radio frequency interference increasingly affects aviation safety. This article links recent research to ATSEP and military training using simulation-based analysis.

As U.S. strategic focus shifts toward the Indo-Pacific, Europe faces rising pressure to coordinate defense autonomously; this article examines the technical role of ISR integration, MPCC, PESCO, and EDF in enabling European military action.

This blog explains why chaff clouds and radar decoys remain relevant in EW training, while a short video shows how they are configured and displayed in SkySim’s ECCM extension.

This article introduces electronic counter-countermeasures explained as a layered ECCM stack, from waveform agility to multi-static geometry. It further describes SkyRadar trains these capabilities.

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.

The rapid growth of small, low-cost drones has placed new demands on Electronic Warfare, requiring defensive systems capable of detecting and responding to agile, low-signature threats. A recent comprehensive survey of anti-UAV research offers an in-depth view of how multi-modal sensing, machine learning and adaptive algorithms are reshaping this domain. As a continuation of our series on innovation in EW, this article examines these developments and their implications for future training and defense architectures.