发表机构
College of Mathematics and Statistics, Northwest Normal University（西北师范大学数学与统计学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对移动传感器对固定无线电源的定位问题，提出基于三圆盘滤波和最小包围圆的方法，通过蒙特卡洛搜索优化任务时间，实验验证平均60.40秒且成功率100%。
AI 中文摘要
我们考虑使用具有有界方位角误差和未知接收半径（在已知范围内）的移动传感器，对固定全向无线电源进行定位和移除。目标是在固定继续策略下最小化预期剩余行动时间，同时保证在传感模型下的接收和源移除。三圆盘滤波器确保接收，最小包围圆证明覆盖所有方位角一致的源位置。蒙特卡洛样本平均搜索通过完整任务时间（包括行进、读数、终端服务和有限回退扫描）对有限候选集进行排序，回退扫描确保在所述假设下完成。在参考案例中，5000次独立验证任务平均耗时60.40秒（近似95%置信区间：[59.96, 60.84]秒），相对于规定的横向点节省19.39%，相对于短行进点节省0.79%。所有25,000次跨五个初始几何形状的选定点验证任务均成功，平均完成时间低于两种规定设计。同网格目标消融表明，仅最小化行进或读数次数可能增加平均完成时间。
英文摘要
We consider the localization and removal of a stationary omnidirectional radio source using a mobile sensor with bounded bearing errors and an unknown reception radius within known bounds. The objective is to minimize expected remaining action time under a fixed continuation policy while guaranteeing reception and source removal under the sensing model. A three-disk filter ensures reception, and a minimum enclosing circle certifies coverage of all bearing-consistent source positions. Monte Carlo sample-average search ranks a finite candidate set by complete mission time, including travel, readings, terminal service, and a finite fallback scan that ensures completion under the stated assumptions. In the reference case, 5000 independent validation missions average 60.40 s (approximate 95\% confidence interval: [59.96, 60.84] s), saving 19.39\% relative to a prescribed lateral point and 0.79\% relative to a short-travel point. All 25,000 selected-point validation missions across five initial geometries succeed, with lower mean completion times than both prescribed designs. A same-grid objective ablation shows that minimizing travel or reading count alone can increase mean completion time.
Comments7 pages, 7 figures, 3 tables
