Track Ⅵ

Advances in Low-Altitude and Maritime Target Detection and Environmental Sensing (Submission Deadline: November 10, 2026) 低空与海面目标检测与环境感知前沿进展

Chair:	Co-chair:

Wei Zhou	Yunlong Yang
Anhui University, China	Donghua University, China

Topics:
Low-altitude/sea-surface target detection, tracking, and recognition (低空/海面目标探测、跟踪与识别) Clutter modeling, statistical characterization, and simulation (杂波建模、统计特性分析与仿真) Radar target detection in complex clutter and interference environments (复杂杂波与干扰环境下的雷达目标探测) Constant false alarm rate detection (恒虚警检测) Multi-dimensional signal feature extraction and target characterization (多维信号特征提取与目标特征表征) Deep learning and machine learning for radar target and environment sensing (面向雷达目标与环境感知的深度学习与机器学习) Multi-sensor data fusion for target sensing in complex environments (复杂环境下目标感知的多传感器数据融合) Cognitive radar and adaptive waveform design for low-altitude and sea-surface scenarios (面向低空与海面场景的认知雷达与自适应波形设计) New radar architectures and array signal processing technologies (新型雷达体制与阵列信号处理技术) Radar systems, real-time embedded processing platforms, and specialized electronic devices (雷达系统、实时嵌入式处理平台与专用电子设备)

Summary:
Low-altitude and sea-surface environments represent some of the most challenging scenarios for radar and sensing systems. Low-altitude targets, such as unmanned aerial vehicles (UAVs), low-flying aircraft, and birds, typically exhibit small radar cross-sections (RCS) and are often embedded in strong ground clutter and multipath reflections. Similarly, sea-surface targets, including vessels and marine objects, are obscured by dynamic and non-stationary sea clutter that varies with sea state, wind, and weather conditions. Furthermore, various types of intentional and unintentional electromagnetic interference further degrade detection performance. Effectively detecting, tracking, and recognizing targets amid such complex clutter and interference environments remains a critical and enduring research challenge. This track invites original research contributions on new algorithms, technologies, and applications for the sensing of low-altitude and sea-surface targets, as well as the characterization and mitigation of ground clutter, sea clutter, and various types of interference. Topics of interest encompass clutter modeling and analysis, target detection and recognition algorithms, anti-jamming techniques, machine learning and deep learning approaches, as well as novel system architectures and engineering implementations. The session aims to provide a forum for researchers from academia and industry to exchange ideas, share recent advances, and explore future directions in this important field.

低空与海面环境是雷达与感知系统面临的最具挑战性的场景之一。低空目标（如无人机、低空飞行器、飞鸟等）通常具有较小的雷达散射截面积（RCS），且往往淹没在强地杂波和多径反射之中。同样，海面目标（包括舰船和海上物体）被随海况、风力和气象条件动态变化的非平稳海杂波所遮蔽。此外，各类有意和无意的电磁干扰进一步降低了探测性能。如何在上述复杂杂波与干扰环境中有效实现目标的探测、跟踪与识别，始终是一个关键且极具挑战性的研究难题。本专题征集面向低空与海面目标感知以及地杂波、海杂波和各类干扰特征表征与抑制的新算法、新技术和新应用的原创研究论文。征稿主题涵盖杂波建模与分析、目标探测与识别算法、抗干扰技术、机器学习与深度学习方法，以及新型系统架构与工程化应用等。本专题旨在为学术界和工业界的研究人员提供交流思想、分享最新进展、探讨未来方向的学术平台。