用摄像头协同雷达，让无人机监测更准更省资源。
A Camera-Cooperative ISAC Framework for Multimodal Non-Cooperative UAVs Sensing
- 摄像头粗扫+雷达精感，形成互补感知闭环。
- 减少71%波束转向开销，跟踪开销降低1.69%-11.15%。
- 适合需要高效感知与通信共存的6G安防场景。
非合作无人机的检测对集成感知与通信（ISAC）系统构成重大挑战，源于单一模态感知的固有局限及感知与通信资源共享的竞争。为此，本文提出一种新型相机协同式ISAC（CC-ISAC）框架，通过多模态感知实现高效的无人机波束转向与跟踪。该框架利用摄像头进行粗粒度空域监控，结合ISAC完成细粒度高精度感知，构建互补感知环路，提升感知准确率与资源效率。核心包含两个模块：（1）视觉-回波数据对齐（V2EDA）模型，通过交叉注意力机制对齐视觉与回波域特征；（2）基于多模态融合的状态估计（MMFE）模型，融合历史多模态数据与当前观测以实现鲁棒状态估计。在DeepSense 6G数据集上的大量评估表明，该框架平均降低71%波束转向开销，跟踪开销减少1.69%-11.15%，同时保持高角度估计精度。CC-ISAC有效缓解了感知与通信间的资源竞争，实现了可靠的无人机监视，并释放大量系统资源用于其他通信任务，是ISAC系统设计的实用进展。
原文摘要 · Abstract (English)
The detection of non-cooperative unmanned aerial vehicles (UAVs) presents significant challenges for Integrated Sensing and Communication (ISAC) systems due to the inherent limitations of single-modal perception and the competition for shared communication and sensing resources. To address these challenges, this paper proposes a novel Camera-Cooperative ISAC (CC-ISAC) framework that employs multimodal sensing to enable efficient UAV beam steering and tracking. The proposed framework employs cameras for coarse-grained airspace monitoring and utilizes ISAC for fine-grained, high-precision sensing, forming a complementary perception loop that enhances both sensing accuracy and resource efficiency. Within this framework, two key modules are developed: (1) a Vision-to-Echo Data Alignment (V2EDA) model that aligns visual and echo-domain features through cross-attention mechanisms, and (2) a Multimodal Fusion-Based Estimation (MMFE) model that integrates historical multimodal data with current observations for robust state estimation. Extensive evaluations conducted on the DeepSense 6G dataset demonstrate that the proposed framework achieves an average reduction of 71% in beam steering overhead and 1.69-11.15% in tracking overhead while maintaining high angular estimation accuracy. The CC-ISAC framework effectively mitigates resource contention between sensing and communication, enabling reliable UAV surveillance while freeing substantial system resources for additional communication tasks, thereby representing a practical advancement in ISAC system design.
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