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Electronic Warfare: Doppler Phase Shift Enhanced Disturbance Filter

The Doppler Phase Shift Enhanced Disturbance Filter (EDF) is an advanced radar signal processing system designed to effectively handle jammed radar data. It utilizes sophisticated algorithms to distinguish genuine radar reflections from jamming signals, thereby enhancing the radar's ability to accurately detect and track targets even in hostile environments.

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Electronic Warfare: Range Gate Pull Off - Kalman-based Countermeasures in FreeScopes (Video)

The Enhanced Kalman Disturbance Filter is a feature developed by SkyRadar. It is part of its training radar system, designed to detect and handle range deception data using the Kalman Filter and the most recent RGPO detection features. This block includes several sub-functions, each serving a specific purpose in the processing of incoming radar reflections to identify and manage potential range deceived targets.

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Comparing Various Algorithms to Monitor Moving Targets (Video)

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.

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Surveillance of Moving Targets - Comparison of MTD & Kalman Filter (Video)

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.

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A Short Video-Explanation of the Kalman Filter Shown in FreeScopes ATC II (Video)

This article presents the Kalman filter in text and video. It is implemented in FreeScopes ATC II and works with live data, recorded data and simulation.

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Barrage-Noise Jamming Detection with FreeScopes

SkyRadar's FreeScopes module "Disturbance Filtering & Analysis I" provides two algorithms for barrage jamming detection.

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Tracking for Pulse Radars – the Kalman Filter

One of the most powerful statistical estimation techniques, which is widely applied in navigation, radar tracking, satellite orbit determination, autonomous driving, and many other fields is the Kalman filter. This digital filter provides a quite accurate estimation of the next state (position, movement, temperature, etc.) from any possible noisy input signal, in real time, which makes it very suitable for radar navigation and tracking purposes.

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Kalman Filter for Intelligent Tracking

One of the most powerful statistical estimation techniques, which is widely applied in navigation, radar tracking, satellite orbit determination, autonomous driving, and many other fields is the Kalman filter.

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