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Application of Anti-Drone Technology in Border Defense Security

2025-08-27

Demand Analysis

With technological advancements and the growing affordability of drones, the speed and scale of their adoption worldwide in recent years have been remarkable. People no longer cast surprised glances at the machines flying overhead; however, this widespread use has brought a concomitant challenge: borders and high-risk areas are frequently subjected to close-range reconnaissance and harassment by drones, with the threat of terrorist attacks even looming. As a result, border defense and the security of critical locations face relatively severe risks.

It is well-known that some countries have long borderlines and complex surrounding geopolitical environments. Alongside the rapid economic development of certain nations, many other countries, as well as malicious individuals and entities, have maintained a covetous gaze on a specific country, frequently conducting harassment and reconnaissance along its borders. Furthermore, some key protected targets are often at risk of smuggling or human trafficking. Criminals leverage portable and highly efficient drones to carry out close-range reconnaissance, posing a significant threat to normal social order. In response to this situation, the border defense forces responsible for border security are confronted with extremely urgent challenges, while also placing higher demands on manufacturers that produce anti-drone systems.

Analysis of Anti-Drone Detection Technology

The anti-drone industry began to develop gradually around 2015, with its development timeline slightly lagging behind that of drones themselves. Driven by strong market demand, a wide variety of anti-drone methods and approaches have emerged in succession. Below is a brief analysis combined with diagrams (Note: "图标" is assumed to refer to "diagrams" for contextual logic; adjust to "charts" if specifically referring to data charts).

The anti-drone system is mainly divided into two core modules: detection and countermeasure.

1. Detection Module

The detection module is composed of one or a combination of the following components:

Radio Detection: Captures and analyzes radio signals transmitted between drones and their remote controllers (e.g., 2.4GHz/5.8GHz civilian frequency bands, dedicated industrial drone frequencies) to identify drone presence, location, and model.
Radar Detection: Uses radar systems (such as micro-Doppler radar, phased-array radar) to detect low-altitude, small-sized drone targets, especially effective in complex environments (e.g., night, fog, or areas with optical obstructions) where other detection methods may fail.
Optical Detection: Relies on optical sensors (including visible-light cameras, infrared thermal imagers) to visually track drones, enabling real-time video monitoring and target recognition, often used in conjunction with radar for "detection + confirmation" verification.
Backend System: Integrates data from radio, radar, and optical detection devices, providing functions such as target trajectory mapping, threat level classification, and alarm triggering, serving as the "brain" of the detection module.

2. Countermeasure Module

The countermeasure module primarily focuses on technologies to neutralize detected drones, with the following main types:

Electromagnetic Jamming: The most mainstream countermeasure method currently, which disrupts the normal operation of drones by interfering with their communication links (drone-remote controller) or positioning signals (GPS/Beidou).
- It is divided into broadband jamming and precision jamming: The key difference between the two lies in power output—broadband jamming covers a wide frequency range (suitable for countering multiple types of drones simultaneously) but requires higher power, while precision jamming targets specific frequencies (with lower power consumption and less interference to non-target signals). Common "anti-drone guns" fall into this category.
Laser Strike: Uses directed laser beams to destroy drone components (e.g., motors, batteries) or disable their sensors, featuring high precision and rapid response, but is currently limited by factors such as effective range (mostly within 3 kilometers) and susceptibility to weather (e.g., rain, fog weakening laser intensity).
Net Capture: Physically traps drones using projectile-launched nets (from ground-based devices or interceptor drones), allowing for the recovery of drones as evidence (suitable for scenarios where avoiding drone debris damage is required, such as near residential areas or key facilities).
GPS Spoofing: Sends false GPS positioning signals to drones, misleading them into deviating from their original flight paths (e.g., forcing them to land in a designated area) instead of directly destroying them. This method is highly targeted but requires accurate control of signal strength to avoid interfering with other legitimate GPS users.

At present, radio jamming remains the dominant countermeasure method in the market, thanks to its advantages of mature technology, low cost, wide application range, and adaptability to most consumer-grade and industrial-grade drones.

Backend Control Center

The central control system is built on an Ethernet architecture and consists of four components: the integrated control system, detection control system, photoelectric control system, and jamming control system. Its main equipment includes switches, servers, output terminals, cabinets, and operation consoles, all centrally installed in the security room.

Integrated Control System: Primarily displays real-time screens of detection devices and their control modules, providing an overview of the entire system’s operational status.
Photoelectric Tracking System: Mainly shows visible-light and infrared thermal imaging footage. It uses visual algorithms to identify and judge unknown aerial objects (UAOs) flying in the air, enabling visual confirmation of detected targets.
Jamming Control System: Focuses on displaying the status of jamming systems and supports switching between manual jamming and automatic jamming modes, allowing operators to intervene or activate automated countermeasures as needed.

The equipment configuration of each subsystem must meet the requirements for the smooth operation of the entire system. Meanwhile, to facilitate monitoring, the display terminals of the three subsystems (integrated control, photoelectric tracking, and jamming control) are centrally placed on the operation console

Radio Detection

Radio detection is a passive electromagnetic monitoring method that identifies targets by monitoring specific frequency bands. It features strong targeting capabilities, remains unaffected by irrelevant targets, and only responds to objects that actively emit radio signals.

Typically, the drone communication frequency bands targeted for monitoring include 420MHz~450MHz, 840MHz~845MHz, 900MHz~930MHz, 1430MHz~1444MHz, 2400MHz~2450MHz, and 5700MHz~5850MHz. By monitoring specific frequency bands, frequencies, and signal types, radio detection provides a basis for frequency surveillance.

Radar Detection

Radar works by actively emitting modulated radio signals, which reflect off targets to generate specific echo signals. Through relevant algorithms, it derives target attributes including size, distance, azimuth, and speed. Radar echoes capture reflected signals from all surrounding objects; fixed objects are eliminated and signals from specific targets are isolated via relevant technical means (a signal processing process), which places high demands on signal processing capabilities. If a target’s radar cross-section (RCS) is too small, the radar’s recognition accuracy will decrease. Typically, the detection range of radar is far greater than that of radio detection and jamming systems.

Optical Detection

Optical detection tracks and identifies aerial targets using high-resolution cameras. It must rely on other auxiliary means: for example, azimuth and altitude information provided by radar, or azimuth information from radio signals, which is transmitted to the corresponding direction via a pan-tilt unit. The aerial targets (whether drones, birds, balloons, or sky lanterns) are then identified either manually or through artificial intelligence (AI) technology.

Recommendations and Applications

Currently, radio detection dominates drone detection applications. This is because radio detection offers greater intelligence, supports a range of complex functions such as unattended operation, and provides robust early warning capabilities. It enables engineered deployment in fixed-area locations, making it relatively suitable for deployment in complex urban environments with strong practical combat value. Meanwhile, when deployed along borders, it can realize multi-station networked detection, boasting high feasibility.

Furthermore, with the improvement of performance, the previously separate detection modules and countermeasure modules are gradually integrated—a trend toward the development of integrated detection-and-countermeasure systems. This integration enhances usability: once an unauthorized drone (“black flight” drone) is detected, countermeasures can be activated quickly, resulting in high timeliness.

Along border lines, drones are often spotted, but their operating frequency bands remain unknown—making it impossible to determine which frequency bands to use for jamming. Therefore, there is an urgent need for passive spectrum detection of such drones. Unlike radar, which actively emits signals, passive spectrum detection offers greater concealment and avoids alerting the target (lit. “stirring up the grass and startling the snake”). In practical combat scenarios, radio detection and jamming thus hold distinct advantages.

News

Cases

Application of Anti-Drone Technology in Border Defense Security

Demand Analysis

Analysis of Anti-Drone Detection Technology

1. Detection Module

2. Countermeasure Module

Backend Control Center

Radio Detection

Radar Detection

Optical Detection

Recommendations and Applications

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