This article introduces a "reflection power tracking", a statistical method to neutralize range deception. It shows a training implementation in FreeScopes. In previous articles we showed ways for radar experts to neutralize noise jamming attacks (spot jamming, barrage jamming) as well as  We also showed in SkyRadar's simulator "SkySim", how to detect and defeat range deception with Pulse Compression and Pulse Doppler and concatenated algorithms.

In this article and video, we will use statistical methods to detect and neutralize the range deception jamming. In our experimental set-up we attacked our radar with our ARESIA ative target jammer.


Let us first revisit the typical scenario of a range deception attack.

Radar Lock-on and Range Gate Pull Off

Range deception is created through DRFM jammers, which are placed on intruding aircraft or drones. Digital Radio Frequency Memory (DRFM) jammers digitally capture and retransmit RF signals. In the case of range deception, they delay or advance the "reflected" signal. First the DRFM creates a cover pulse over the real target's reflection. It is much higher than the reflection of the real target. The surveillance radar reduces the gain in this range gate with electronic circuits at the radar receiver, in order to control the amplitude of the covered pulse. We call this Automatic Gain Control (AGC). The consequence of this cheat: the real target disappears below clutter level. We call this Radar Lock-on and Range Gate Pull Off.

The consequence: surveillance radar gets a wrong impression of the target position.

Reflection Power Tracking - A Statistical Method to Neutralize Range Deception

To detect and remove/suppress the fake targets (range decepted targets), in this application we implemented an algorithm which does reflection power tracking. This algorithm consists of a search window of 5 samples and a tracking algorithm which tracks the return of reflected power within the sliding window.

As the window is sliding in the whole radar range, the tracker checks if the power within the 5 samples does differ by more than 75%. As you can see in the video, once the active target starts to increase its reflection power towards the radar, we see an immense power increment of the fake target, which makes the real target almost undetectable for the radar.

However, if the algorithm captures these big deviations, outside the expected power increments, while the fake target remains in the same position, it concludes that the reflected power can not come from a real target, therefore it cancels out those positions. In the same time it localizes from where the deception is coming, by marking the position of the target, equipped with a deception jammer with an orange dot in the PPI scope.

In addition we implemented another robustness measure to prevent major toggling in the detected signals. We developed it using a dynamic threshold. Within the first 100 radar updates, the dynamic threshold is estimated and later used to filter-out big power spikes above that threshold, as those do not belong to a real detected target.

HubSpot Video

Many Applications for Electronic Warfare

Follow our blogs and videos on Electronic Warfare with SkyRadar's Disturbance Filtering & Analysis solutions, the jammers and the Pulse Radar! SkyRadar is the only provider world-wide, providing manufacturer-agnostic ECM and ECCM training with simulators and real radars and jammers. Learn more about the simulator, range deception, angle deception, speed deception, radar lock on and major state of the art defense algorithms against malicious attacks.

Such defense is not only useful in a military context but also in a civil aviation setting. Increasingly speed radar jammers by trucks and cars disturb airport infrastructure. Also hybrid warfare is used to perturb critical infrastructure like airports and civil air surveillance and navigation services.

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