AI 中文总结
本文针对协作式集成感知与通信场景，提出分离关联确认、状态优化与残差恢复的协作融合方法，经实验验证可提升检测率、降低错误输出占比并减小位置误差。
AI 中文摘要
协作式集成感知与通信（ISAC）可为无人机（UAV）、道路车辆以及自动导引车（AGV）等工业移动机器人提供共享态势感知支持。然而多径效应可能使节点达成虚拟目标的共识，同时有用的弱回波却未被利用。本文提出一种协作融合方法，该方法将关联确认、状态优化与残差恢复分离开来。所采用的蜂窝参考信号模型可适配任意节点数量、三维运动、单站与双站链路、干扰参数以及相关误差。我们刻画了在有界偏差与额外节点仍会存在的共享反射体模糊性下的报告可区分性。极小极大估计可生成定向弱报告优化，该优化能保留已确认的关联并限制对偏差敏感的创新；采集过程则考虑了请求与上传成本。受控实验结合了无人机在第三代合作伙伴计划（3GPP）随机信道模型以及代表旧金山的射线追踪环境下的评估。在后者环境中，匹配预算的融合将可观测站点选择的检测率从88.75%提升至92.46%，并将错误输出占比从11.06%降至0.40%。相较于最强的全频段固定站点，常见检测目标的90百分位位置误差从8.54米降至3.50米。关联控制、局部拒绝消融实验以及优化研究明确了这些增益的来源。
英文摘要
Cooperative integrated sensing and communication (ISAC) can support shared situational awareness for unmanned aerial vehicles (UAVs), road vehicles, and industrial mobile robots such as automated guided vehicles (AGVs). Yet multipath can make nodes agree on a virtual target while useful weak echoes remain unexploited. This paper develops cooperative fusion that separates association confirmation, state refinement, and residual recovery. A cellular reference signal model accommodates arbitrary node counts, three-dimensional motion, monostatic and bistatic links, nuisance parameters, and correlated errors. We characterize report distinguishability under bounded bias and shared-reflector ambiguities that survive additional nodes. Minimax estimation yields directional weak-report refinement that preserves confirmed associations and limits bias-sensitive innovations; acquisition accounts for request and upload costs. Controlled experiments accompany UAV evaluations under a Third Generation Partnership Project (3GPP) stochastic channel model and a ray tracing environment representing San Francisco. In the latter environment, matched-budget fusion raises detection from observable site selection's 88.75% to 92.46% and reduces the false-output fraction from 11.06% to 0.40%. Against the strongest full-band fixed site, the 90th-percentile position error on commonly detected targets falls from 8.54 to 3.50 m. Association controls, local rejection ablations, and refinement studies distinguish the sources of these gains.
Comments13 pages, 10 figures, 4 tables
