Understanding radar signal processing is crucial for ATSEP qualification, military radar operations, and academic training in surveillance technologies. To support this, we’ve created a practical walk-through video showcasing FreeScopes' capabilities in live signal analysis and cleaning.

This video shows how to extract plots and tracks from live radar raw data (IQ-data) with FreeScopes.

In today's video, we demonstrate how to create plots and tracks using FreeScopes.

SkyRadar's FreeScopes platform offers a range of distinctive advantages and unique characteristics that make it an ideal choice for educational institutions and training programs focused on radar technology and signal processing.

This brief video outlines FreeScopes ATC I and ATC II within a broader framework. It demonstrates how the algorithms enhance ATSEP skills, building upon the foundations established by FreeScopes Basic I and II.

In this video we show how FreeScopes can track and differentiate multiple targets, plot the history dots and indicate direction and speed with a speed vector.

This video illustrates how to monitor moving targets through various alternative algorithms. It provides an easy to follow introduction into the setup of a radar block diagram and its scopes (A-Scope, PPI) using previously recorded IQ data.

In this video we visualize the movement of a Fidget Spinner (hand-held toy) with the 8 GHz Pulse Radar, a Fast Fourier Transformation and a Heatmap in FreeScopes

This video compares the MTD algorithm and the Kalman filter. The use case is a moving target, in this particular case a person moving zig zag in front of SkyRadar's 8 GHz NextGen Pulse radar.

Sometimes a single plot or a track gets split into two targets appearing at different positions. This split of targets is termed double targeting. This article explains the reasons and suggests countermeasures.

The following video shows the algorithms Moving Target Indication (MTI) , MTI with post processing, Moving Target Detection (MTD) as well as MTD with Doppler filter, applied on raw data of a 24 GHz FMCW.

This video show several blocks in the digital signal processing chain that allow to enhance the visibility and tracking of moving targets. We show CFAR, Moving Targete Detection with Doppler Filtering, a Heatmap and the I and Q signals.

In this video we show, compare and discuss  the implementations of several algorithms to detect or indicate moving targets. The signals are detected with SkyRadar's NextGen 8 GHz Training radar and visualized with the FreeScopes Environment.

The Standing Person Recognition Algorithm – SPRA provides the capability to detect reflections coming from a standing target (person), which exists in a stationary environment.  It is included in SkyRadar's FreeScope ATC I.

The Moving Target Detection is a highly reliable algorithm for detection of moving targets and temporarily non-moving targets in the constant presence of clutter. It is implemented in SkyRadar's ATC I Module.

The Moving Target Indication algorithm provides the capability to detect reflections coming from targets in motion with respect to a standing background environment, such as ground, walls, parked cars, and so on. 

This article features a video which shows the plots and tracks as well as the speed-vector generated in FreeScopes ATC I. Students can build their block diagrams concurrently. After cleaning the signal, e.g. with the MTI block, they can add tracks and plots.