Facing the challenges posed by "low-altitude, slow-speed, small-sized" (LSS) UAVs, the highly integrated UAV laser strike system stands out as a key defense solution. Comprising core modules like detection & identification system, 2D turntable, and laser emission system, it follows a streamlined "detect-identify → track-aim → laser-damage" workflow. This not only boosts the defense system’s response speed and interception efficiency but also ensures rapid, precise, and effective strikes against LSS UAVs.
Core Tech Focus: Detection & Identification
The traditional detection & identification process works in four steps: sensor data collection → signal processing & target detection → in-depth analysis & feature extraction → algorithm-based classification. Today, this tech has evolved into a diversified system, with three mainstream paths: radar detection, radio monitoring, and photoelectric detection. These technologies complement each other, forming a reliable technical support network for LSS UAV detection across various scenarios.
1.1.1 Radar Detection
Radar detection, a widely used mainstream tech, works by transmitting electromagnetic waves and analyzing UAV echo signals via the Doppler shift effect to calculate position, speed, and other key data. Its strengths lie in high positioning accuracy and long detection range. However, it has clear drawbacks: vulnerable to electromagnetic interference; low-altitude elevation blind spots (see Figure 4) that weaken echoes of LSS UAVs, leading to false/missed alarms or even failure in detecting hovering UAVs; and easy misjudgment due to similar Doppler characteristics between birds and UAVs.
1.1.2 Radio Monitoring
Most UAVs (civilian and some military) rely on radio signals for communication, command reception, and data transmission (video, images, telemetry). Radio monitoring leverages spectrum sensing (a core cognitive radio tech) to detect unique RF signals between UAVs and ground controllers, initially confirming UAV presence. It then uses RF fingerprinting to extract signal features for accurate classification. A key advantage: analyzing captured control signals can reveal UAV flight status, operational intent, and even operator info. Limitations: limited detection performance for long-distance/low-power UAVs; ineffective against silent UAVs (no RF transmission); and high misjudgment risk due to overlapping UAV frequency bands with other civilian/public wireless signals.
1.1.3 Photoelectric Detection
Photoelectric technology converts physical quantities into optical signals, then uses photoelectric devices and circuits for target detection. Long-range early warning photoelectric radar—integrating HD visible light imaging, short-wave infrared detection, wide-spectrum sensing, and Beidou positioning—enables all-weather, 24/7 target monitoring and tracking. It has two main types: ① Visible light tracking (uses HD cameras to capture UAV images for recognition via image algorithms); ② Infrared tracking (uses infrared cameras to detect UAV heat signatures—any object above absolute zero emits infrared, and UAV batteries/motors generate distinct heat during flight, a key identification marker).
Despite its potential, photoelectric detection faces practical challenges: weak infrared radiation from small LSS UAVs causes long-distance detection difficulties and missed targets; overlapping infrared features with birds, kites, and balloons lead to false identification; and urban obstacles (buildings, trees) block infrared signals, reducing efficiency and limiting use in dense urban areas. Thus, its accuracy and adaptability need scenario-specific optimization.
Practical Application: Synergistic Tech Integration
Currently, radar detection and radio monitoring are widely used in mainstream LSS UAV detection due to high maturity and strong adaptability, while photoelectric detection serves as an auxiliary tool. For comprehensive detection, the industry generally adopts the "radar + photoelectric" integrated scheme, combining the three technologies for synergistic effect. Multi-source data fusion further enhances detection accuracy and reliability for LSS UAVs.
