系统梳理2020年以来无人机侦测与识别技术的演进，展望未来发展方向。
Advance and Refinement: The Evolution of UAV Detection and Classification Technologies
- 融合雷达、射频、光学、声学多传感器数据提升侦测能力
- 人工智能与机器学习显著提升系统准确率与效率
- 适合安防、空管领域研究人员参考
本文详细分析了2020年至今无人飞行器（UAV）侦测与分类系统的进展。涵盖了雷达、射频、光学和声学传感器等多种侦测方法，并强调通过复杂的传感器融合技术实现集成应用。深入探讨了驱动无人机侦测与分类的核心技术，重点关注其精度与作用范围。此外，论文讨论了人工智能与机器学习领域的最新创新，阐明其对提升系统准确率与效率的影响。最后，文章预测了未来无人机侦测技术的进一步发展，预计将进一步提升系统性能与可靠性。
原文摘要 · Abstract (English)
This review provides a detailed analysis of the advancements in unmanned aerial vehicle (UAV) detection and classification systems from 2020 to today. It covers various detection methodologies such as radar, radio frequency, optical, and acoustic sensors, and emphasizes their integration via sophisticated sensor fusion techniques. The fundamental technologies driving UAV detection and classification are thoroughly examined, with a focus on their accuracy and range. Additionally, the paper discusses the latest innovations in artificial intelligence and machine learning, illustrating their impact on improving the accuracy and efficiency of these systems. The review concludes by predicting further technological developments in UAV detection, which are expected to enhance both performance and reliability.
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