In a previous blog we covered why drones are such a big concern across many industries. The next logical question is what can be done about the threat and is it possible to prevent drone incursions?
As the name suggests, drone detection is a technology designed to identify and pinpoint the presence of a drone or Uncrewed Aerial Vehicle (UAV) through the utilization of electronic sensors and antennas.
Various technologies contribute to this capability, such as Radio Frequency (RF), radar, Electro-Optical/Infrared(EO/IR), or acoustic systems.
Most commercial Uncrewed Aerial Systems (UAS) (the drone and its controller), including custom and kit drones, utilize various wireless communication protocols such as Wi-Fi, Frequency Hopping Spread Spectrum (FHSS), Wideband FM (WBFM), or proprietary methods.
These communications primarily take place over Industrial, Scientific, and Medical (ISM) bands, with some operating in Amateur radio bands or LTE bands.
In the typical communication flow, a drone controller transmits an uplink with control commands to the UAV. In response, the UAV sends a downlink carrying video and telemetry data back to the controller or connected device. This makes RF-based UAS detection technologies highly reliable and serves as the only method for detecting the pilot/controller as they can effectively detect both the uplink and downlink of UAS.
Certain RF-based systems use the approach of decoding and demodulating the UAV’s downlink to pinpoint the location of both the UAV and the pilot.
Watch: 3 Problems with Drone Detection Systems that Decode and Demodulate in 1 Minute
Alternatively, other RF-based systems employ location methods that adhere to Federal wiretapping laws, such as spectrum sensing, to identify the presence of both the UAV and its controller. In any case, since the pilot is the origin of potential threats, it becomes crucial to consistently and accurately detect and locate the pilot before their drone takes flight whenever possible.
An RF-based system exhibits rapid detection, identifying the UAV and pilot controller as soon as they are activated, indicating the presence of the uplink, downlink, or both.
Unlike other systems dependent on line of sight, the RF system operates effectively even without direct visibility to the target. However, it is noteworthy that environmental RF interference may potentially impede the speed of detection.
Radar systems operate by detecting Radar Cross-Section (RCS), generated when the drone encounters RF pulses emitted by the radar. This necessitates the drone to be within the line of sight of the radar and continuously moving in one direction (typically approaching or departing).
While radar systems swiftly detect the presence of a drone once it's up in the air and moving, the time taken to determine its legitimacy is longer compared to RF-based systems.
Advanced radar technologies leverage micro-doppler signatures from the rotating propellers of specific drone types, such as quadcopters.
Similar to radar systems, an Electro-Optical/Infrared (EO/IR) system requires the drone to be within the line of sight.
Environmental factors like extreme temperature, fog, or rain can influence the detection speed and reliability of an EO/IR system.
Acoustic drone detection systems rely on unique sound signatures produced by the motors of a drone.
The detection speed is mainly limited by the type of the drone, its environment and distance to the acoustic sensors.
The detection range of an RF-based system can be anywhere from several kilometers to tens of miles and is influenced by various factors, including the maximum signal strength of the UAV and its controller, frequency of the signal, surrounding RF environments and the specific RF technology deployed.
Generally, a demodulation and decoding-based RF system is more susceptible to negative impacts from interference, resulting in a reduced range compared to a spectrum sensing-based RF system.
Taking the DJI Phantom 4 as an example, a spectrum sensing based system can detect it at a range of approximately 5 km in a low-interference environment.
In high-interference areas, such as urban settings, this range might decrease to 2-3 km for a spectrum sensing RF system.
However, in such challenging conditions, the demodulation and decoding-based RF system will likely experience more substantial range loss, potentially leading to detection failures.
Radar systems can effectively detect drones at distances ranging from hundreds of meters to several kilometers.
The specific range achieved depends on variables like the size, material, and speed of the drone.
Using the DJI Phantom 4 as a reference, a radar system usually has a detection range of around 1.5 km.
The detection range of EO/IR systems is typically more limited compared to RF and radar systems, influenced by factors such as camera quality and prevailing weather conditions.
A mid-range EO/IR drone detection system often has a detection range of 1.5 km.
Acoustic sensors offer a maximum detection range less than 1 km, providing coverage within a constrained distance compared to other systems.
The effectiveness of an acoustic sensor array can be impacted by factors such as background noise and wind direction, which may reduce the practical range in certain conditions.
Be aware that some RF-based systems infringe on privacy laws by decoding and demodulating private UAV signals to extract sensitive information like the serial number or exact GPS coordinates, which violates Federal wiretapping laws.
Legitimate RF-based systems compliant with regulations can provide the following information:
Since September 2022, drone manufacturers are required to comply with Remote ID, broadcasting identification messages from takeoff to shutdown, including but not limited to:
A radar-based system typically offers:
Newer radar technologies may leverage micro-Doppler signatures, unique radar reflections caused by rotating drone components like propellers, providing additional insights into the type of drone.
EO/IR systems primarily offer visual confirmation of a drone. To enhance capabilities, they are often integrated with other systems like RF or radar.
These systems capture visual data enabling identification of:
Acoustic drone detection systems provide azimuthal information on the incoming drone's direction and its distance. Depending on unique sound signatures, they might also offer information on size or model.
The choice of drone detection technology depends on several factors, including your specific use case, the level of threat you're addressing, budget considerations, and your acceptable risk tolerance.
For detecting a majority of off-the-shelf drones and their controllers, an RF-based system proves highly effective. However, it's important to note that some RF-based systems may rely on a product library that requires manual updates as new drones enter the market or might be limited to detecting drones from specific manufacturers. The acceptance of such limitations plays a crucial role in determining your risk tolerance.
If your requirement extends to detecting radio-silent, fully autonomous drones, a combination of RF and radar systems is recommended.
Additionally, integrating an Electro-Optical/Infrared (EO/IR) system can enhance the overall detection capabilities by providing visual information on the detected drone or the pilot located by the other systems.
This multi-layered approach ensures a more comprehensive and adaptable drone detection solution tailored to diverse threat scenarios and operational needs.