Detecting and Neutralizing Mini-Drones

Sensors and Effectors against an Asymmetric Threat

By Ms

By Ms



, IT

Corporate Chief Scientist, ELT Group

 March 2018


Small (15–150 kg), mini (<15 kg), micro (<66 J energy state) Unmanned Aerial Systems (UAS)1 will drastically proliferate in the near future with rapidly advancing performance and functionalities. Progress in power storage, avionics miniaturization, materials and design methodologies, together with the availability of commercial or open source software applications, will enable increasingly smaller and cheaper platforms for a broadening range of possible uses. While such advanced technology means a huge opportunity for the military and industry, its alternative, sinister use for criminal and terrorist purposes is also no longer a fictitious risk. As many recent examples show, small UAS have become a real threat to both civil and military targets.

The detection, identification, and neutralization of such UAS flying near key infrastructure or sensitive areas (e.g. government buildings, high-profile event locations, prisons, military compounds) has therefore become a critical capability. So far, traditional countermeasures have demonstrated their weakness in this regard. Unconventional threats require more advanced solutions, and many industrial and government initiatives are rising to meet this new threat.

New developments such as advanced passive and active multispectral technologies seem most feasible to deal with the counter-UAS challenge. Multiple domain (electromagnetic, acoustic, electro-optic), multiple sensor (active radar, passive electromagnetic interceptors, acoustic sensors, infrared cameras), multiple jamming/deception system of systems, integrated via a dedicated command & control (C2) capability, are key elements within this approach. Last but not least, exploiting cyber capabilities is an important vector to counter the mini drone threat, though respective solutions are still immature. Superior knowledge, skills, and tools in the cyber domain will probably be the most decisive factor for a successful defence.

Too Small and Simple to be a Threat?

Drones are rapidly becoming ‘tools of the trade’ in many industries and could be categorized into segments of the market: Government (including Military), Enterprise (Corporations/Businesses) and Consumers (Personal/Hobbyist).

Since low-altitude drones fly only hundreds of feet above ground, they mostly operate outside traditional radar coverage used to track commercial aircraft. Also, military air defence radar systems are usually not designed to detect aircraft with such a small radar cross-section. In other words, there is an airspace segment neither under control of civil authorities nor military air power.

According to the 2016 Field Guide ‘Drones Operating in Syria and Iraq’ published by the Center for the Study of the Drones at Bard College (Annadale-On-Hudson, New York), ‘there are more drones, made in more countries, and flown by more groups, than in any other previous conflict’. Among the 38 different types of UAS, the institute counted at least eight recreational hobby drones and possibly six unidentified homemade models, asserting ‘the conflict marks the first time that hobby drones have been modified with explosives and turned into flying improvised explosive devices’.2

However, such use of mini-drones may not be limited to zones of war or conflict. The probability of threat proliferation to domestic areas combined with the inability of traditional airspace control and defence to effectively deal with such small and low-flying objects underline even more the pressing need for appropriate counter-UAS technology. Many companies have therefore created intense research & development programmes to provide effective solutions.

Drone Detection and Identification

Defending against small UAV threats is a complex issue since it is not only about eliminating the drone to prevent it from completing its mission. Successful defence must ensure the immediate detection and identification of the object prior to neutralizing it in a secure framework for the safety of the people on the scene as well as minimizing collateral damage. Given the physical and kinematic characteristics of the drone and the typical modes of use, a multiple sensor approach is necessary to improve the detection capability. Several options, each with their own strengths and weaknesses are currently being tested:

EM Sensors. Defence systems could exploit the sudden presence of radio signal used to send the commands from the pilot to the drone (uplink) and to send data and images from the drone to the command post (downlink). Those radio signals are transmitted on well-known and standardized frequencies, relatively easy to be intercepted with electronic surveillance in automatic mode, even though complex wave modulation is often superimposed to the carrier signal. Furthermore, passive geo-location techniques can be put in place to locate both the drone and the control station.

Active/Passive Radar. A sensor particularly devoted to the detection of aerial tracks is the radar. However, mini-drones are hard to detect and identify due to very low radar signatures (with a radar cross-section of the order of 0.01 m2). Furthermore, it is a tremendous challenge to distinguish the target from other objects particularly in an urban environment, with a high probability of false alerts. The challenges increase when trying to use passive (bi-static) radar.

Infrared Sensors. Together with electromagnetic sensors, other promising devices could be thermal cameras, usable under low visibility conditions and at night. Infrared sensors could reveal drones even in the presence of strong lighting due to the ability to locate thermal hotspots generated by motors. Such hotspots, located in fixed positions in relation to the structure of the drone, also contribute to automatic object identification by making use of IR image reference libraries.

Acoustic Sensors. During flight, drones generate noise both in the audible frequencies and in the ultrasounds. Acoustic sensors reveal the presence of mini-drones as well as helping to classify the target based on noise characteristics specific to the drone model. However, the operational range of acoustic sensors is limited to a few hundred metres. At longer distances, drones are lost in background noise. On the other hand, radars have a blind spot at shorter distances. This means the acoustic sensor, made up of an array of microphones, is the ideal complement to radar systems to cover both long and short ranges. Being relatively cheap, acoustic sensors are efficient tools for the continuous surveillance of particularly sensitive areas.

Drone Neutralization

Detection and identification are essential, but they are only the preliminary steps in solving the problem of removing the drone from the scene of illicit action and/or its neutralization. ‘Hard Kill’, or physical destruction options are limited to combat zones or an open field, where the consequences of falling wreckage, ordnance, or other harmful items are generally irrelevant. In an urban scenario, a different approach aiming at a ‘Soft Kill’ is preferable. The following options have currently been proven as feasible and effective:

Jamming. A first option is to affect previously detected and identified radio signals, which would sever control of the drone from the operator. Then it could be forced to land in a safe area or to crash without risking collateral damage. The simplest technique is to generate jamming signals against the control link, delivering enough power to negate the use of the electromagnetic spectrum. According to the programmed modes, the drone then automatically enters into fail-safe mode causing it to land or return home. This ‘brute force’ approach, however, requires generating a huge amount of electromagnetic power and broad spectrum jamming of the whole area, which may also result in the undesired suppression of friendly communications. A more sophisticated and selective technique is so-called ‘Smart Jamming’, which consists of jamming the control signal only in some specific timeslots, according to the specific protocol used by the radio remote control. The challenge is again to successfully detect the particular UAS control/steering signal, whose waveform and encoding then need to be compared with available data for correct identification. To this purpose, a library of control signal protocols must be previously obtained by laborious reverse engineering based on vested intelligence, which may pose additional challenges to the friendly forces in countering the threat.

GPS Spoofing. The most effective albeit complex technique is Global Positioning System (GPS) spoofing, provided the targeted UAS is using satellite navigation.3 Based on military capabilities designed to deceive adversary precision-guided munitions, the technique consists of first, seducing the UAV’s GPS receiver to recalculate its position and second, deviating its path in accordance with pre-planned countermeasures. To this end, a spoofing device transmits imitated satellite signals while deceiving the target with formally correct but false position data. This requires knowing the exact position and speed of the drone, which can be provided by a radar sensor. Precise scheduling of each spoofing phase is also needed to reduce the effectiveness of counter-countermeasures of certain smart, GPS-based guidance systems.

Direct Energy Weapons. In addition to these soft-kill techniques, weapons are being developed that produce a high-power microwave electromagnetic pulse which is highly effective against electronic equipment. With a specifically shaped antenna or emitter, the energy can be focused to produce effects within a confined area and limited range. Under certain circumstances such weapons could ideally complement the other techniques to neutralize small drones.

Sensors and countermeasures would need to be coordinated and integrated, so they interface via a Mobile Ad-Hoc Network (MANET) with a C2 station, typically with a man-in-the-middle, with an intuitive and easy to use interface.


Michael Blades, research director at market research firm Frost & Sullivan, says that a year ago the anti-drone industry was too new to even offer a market estimate. But things have changed, and quickly. The anti-drone business is worth ‘between $ 500 million and a billion dollars right now’. Blade isn’t alone in his thinking; other market firms project growth rates as high as 26 percent, with market values hitting $ 1.5 billion by 2023. ’I think double-digit growth is a foregone conclusion‘, says Blades, ‘just because they’re starting from almost zero right now.’4

Many companies worldwide are proposing solutions in this emerging field, even if a lot of Research and Development activity is still ongoing and no vendor is able to demonstrate the maturity of a ‘total weapon’. From US to Russia, including across Europe, announcements of new solutions and experimental results are published every day. ELT Group, the Italian EW house, is conducting trials of its solution named Anti-Drone Interception Acquisition Neutralization (ADRIAN), which includes hacking activity against the processor on board the threat.5

In any case, every proposed solution, modular and scalable according to the operational scenarios and the needs of the final user, is several times more complex than the threat, requiring a plethora of assets deployed. Controlling these assets will require highly-qualified and best-trained operators, whose mission preparation needs to be much more professional and sophisticated compared to the relative simplicity of the threat. The costs of the defence could therefore be magnitudes higher than the cost of the attack.6 This is really asymmetric warfare.

According to the official NATO UAS Classification, small, mini and micro drones are subcategories of Class I. See Allied Tactical Publication ATP-, ‘UAS Tactical Pocket Guide’. Oct. 2016. Table 1, p.1–2.
Dan Oettinger. ‘Drones Operating in Syria and Iraq’ (Field Guide). Center for the Study of Drones, Bard College. Dec. 2016. Online at:
Miniaturization does not only apply to UAS platforms, but also on-board electronic equipment of any kind. Size reduction does therefore not limit the use of GPS technology, as shown on the open drone market, though other methods of navigation (e.g. based on recognized terrain and objects) for small/mini/micro drones have been developed.
Tim Wright. ‘Anti-Drone Technology Could Become a Billion-Dollar Business’. 26 Jul. 2017. Online at:, accessed 26 Sep. 2017.
To hack the on board processor, a strong activity of reverse engineering is needed to discover the particular vulnerability that can be exploited pending the type of processor used. Exploitation of the vulnerability will require access to the functionalities of the target via the control link. Hacking UAS is difficult but possible, proven, and effective under certain conditions.
Counter-UAS system prices may vary between 250,000 € and 1,000,000 € depending on the specific configuration and features. A serious threat UAS may only cost between 5,000 and 25,000 €.
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Corporate Chief Scientist, ELT Group

Daniela Pistoia has a degree in Electronic Engineering and a diploma for Executive Management. In 1988 she began her career at Alenia Marconi Systems as an Engineer for Missile Systems and led the company’s RF Sensor Simulation and Design Studies. Having worked from 2000–2002 as the Head of Advanced Concepts and System Studies in the Seeker Division of MBDA, she joined Elettronica (ELT) in 2003. As Vice President for Research and Advanced Systems Design, she developed and managed ELT’s product portfolio related to cyber, EW, radar and electro-optical systems. Since 2013 she has been appointed as ELT Corporate Chief Scientist and Head of Product Innovation & Advanced EW Systems. She is author of numerous technical research papers and a regular speaker at international events.

Information provided is current as of March 2018

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