ID	原文	译文
3473	实测数据分析结果证明，所提方法相比基于单一特征提取方法和经典多特征提取方法有更高的准确率，使用室外典型场景多径衰落信道模型对辐射源信号进行了处理，所提模型仍可进行有效识别，能够适用于复杂无线信道环境的应用。	Based on the measurement andanalysis of the actual signals, the experimental results show that the method has higher accuracy than the single featurevextraction method. The multipath fading channel has been used to simulate the outdoor propagation environment, and the method has certain generalization performance to adapt to the complex wireless channel environments.
3474	为解决绝大多数研究未充分考虑位置对隐私预算的敏感程度以及轨迹形状带来的影响，使发布的轨迹可用性较差的问题，提出了基于相对熵和 K-means 的形状相似差分隐私轨迹保护机制。	To solve the problem that most studies had not fully considered the sensitivity of location to privacy budgetand the influence of trajectory shape, which made the usability of published trajectory poor, a shape similarity differential privacy trajectory protection mechanism based on relative entropy and K-means was proposed.
3475	首先，根据地理空间的拓扑关系，利用相对熵计算真实位置对隐私预算的敏感程度，设计了位置敏感的隐私级别实时计算算法，并与差分隐私预算结合建立了一个新的隐私模型。	Firstly, according to the topological relationship of geographic space, relative entropy was used to calculate the sensitivity of real location to pri-vacy budget, a real-time calculation method of location sensitive privacy level was designed, and a new privacy modelwas built in combination with differential privacy budget.
3476	其次，通过 K-means 算法对发布位置进行聚类，得到与真实位置方向最相似的发布位置集合，并引入 Fréchet 距离衡量发布轨迹与真实轨迹的相似性，提升发布轨迹的可用性。	Secondly, K-means algorithm was used to cluster the release position to obtain the release position set that was most similar to the real position direction, and Fréchet distance was in-troduced to measure the similarity between the release track and the real track, so as to improve the availability of the re-lease track.
3477	通过对真实数据集的实验表明，所提轨迹保护机制与其他方法相比在轨迹可用性方面有明显的优势。	Experiments on real data sets show that the proposed trajectory protection mechanism has obvious advantages in trajectory availability compared with others.
3478	为解决无人机在数据收集过程中的路径规划问题，将其分为全局路径规划和局部路径规划。	To solve the problem of path planning of UAV data collection, it was generally be divided into global pathplanning and local path planning.
3479	针对全局路径规划，将其建模为一个定向问题，定向问题是背包问题和旅行商问题 2 种经典优化问题的组合。	For global path planning, it was modeled as an orientation problem, which was a com-bination of two classical optimization problems, the knapsack problem and the traveling salesman problem.
3480	采用指针网络深度学习对该模型进行求解，并在无人机能量约束下得到其服务节点集合及服务顺序。	The pointernetwork of deep learning was used to solve the model to obtain the service node set and service order under the energyconstraint of the UAV.
3481	针对局部路径规划，基于无人机接收到节点的参考信号强度，通过深度 Q 网络学习对无人机局部飞行路径进行规划，使无人机逼近节点位置并服务各节点。	In terms of the local path planning, the reference signal strength (RSS) of the sensor node receivedby UAV was employed to learn the local flight path of UAV by deep Q network, which enabled the UAV to approach andserve the nodes.
3482	仿真结果表明，所提方案能够在无人机能量约束下有效提升其数据收集的收益。	Simulation results show that the proposed scheme can effectively improve the revenue of UAV data col-lection under the energy constraint of UAV.