优化水下传感器布局，提升对随机航迹船只的检测概率。
Near-optimal Sensor Placement for Detecting Stochastic Target Trajectories in Barrier Coverage Systems
- 将复杂航迹转换为点状表示，简化传感器部署计算。
- 基于历史船舶数据，使所有通过的船只被检测的概率最大化。
- 适用于海洋监控、海上安全等需要全覆盖感知的场景。
本文研究二维屏障覆盖系统中传感器的部署问题。目标是为遵循对数高斯柯西线过程的随机目标轨迹，计算近似最优的传感器位置。我们探索在变换空间中部署传感器的方法，其中线性目标轨迹被表示为点，虽简化了线过程处理，但传感器性能（即探测概率）的空间函数变得不直观。为展示该方法，我们聚焦于海底传感器的布置，以检测经过的船只。利用历史船舶数据进行数值实验，计算出能最大化所有穿越屏障区域船只被探测到概率的传感器位置。
原文摘要 · Abstract (English)
This paper addresses the deployment of sensors for a 2-D barrier coverage system. The challenge is to compute near-optimal sensor placements for detecting targets whose trajectories follow a log-Gaussian Cox line process. We explore sensor deployment in a transformed space, where linear target trajectories are represented as points. While this space simplifies handling the line process, the spatial functions representing sensor performance (i.e. probability of detection) become less intuitive. To illustrate our approach, we focus on positioning sensors of the barrier coverage system on the seafloor to detect passing ships. Through numerical experiments using historical ship data, we compute sensor locations that maximize the probability all ship passing over the barrier coverage system are detected.
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