AI 中文总结
本文评估了伽利略项目多站点全天域红外相机阵列的三角测量能力，提出基于加权最小二乘的瞬时定位流水线，利用ADS-B飞机标定，验证了位置和速度精度，并确定了识别完备性阈值。
AI 中文摘要
伽利略项目在内华达州拉斯维加斯附近运营三个自主多相机观测站点，站点间基线距离分别为2公里和10公里，旨在刻画穿越天空的自然和人造物体种群，从而隔离出任何不符合这些种群的异常事件。每个站点配备一个由八台长波红外（LWIR）相机组成的阵列，这些相机布置在固定的圆顶状结构（IR-Dalek）中，提供360°方位角覆盖。我们报告了三个阵列的调试情况，并介绍了基于它们构建的三角测量流水线。由于我们的目标不被假定遵循任何特定轨迹，我们偏离了流星研究中标准的参数拟合方法，而是在每个时间步将瞬时三维位置估计为到同时视线的最小加权距离平方和的点，其中每台相机按其自身的指向不确定性和到目标的距离进行加权。我们描述了内参和外参标定流程，该流程在长波红外视场中缺乏恒星或固定地标的情况下，使用自动相关监视-广播（ADS-B）飞机作为参考源，以及多传感器航迹关联方案，该方案决定哪些探测属于同一目标。利用一周的数据（2026年5月24日至30日；1650相机小时，2.1×10^8次探测和5.3×10^6条航迹），我们对照ADS-B记录验证了恢复的位置、速度和加速度，对于从三个站点解算的飞机，99%的距离恢复在5%以内，对于从单站点对解算的飞机，83%的距离恢复在5%以内；速度恢复在5%以内的比例分别为78%和63%。我们表征了阵列的识别完备性，该完备性由表观尺寸决定：50%识别阈值位于1.8像素的表观翼展处。
英文摘要
The Galileo Project operates three autonomous multi-camera observing sites near Las Vegas, Nevada, separated by baselines of $2$ and $10\,$km, with the goal of characterizing the populations of natural and human-made objects that cross the sky and thereby isolating any event that fits none of them. Each site carries an array of eight long-wave infrared (LWIR) cameras arranged in a fixed dome-like structure, an IR-Dalek, providing $360^{\circ}$ azimuthal coverage. We report the commissioning of the three arrays and present the triangulation pipeline built on them. Because our targets are not assumed to follow any particular trajectory, we depart from the parametric fits standard in meteor work and estimate the instantaneous three-dimensional position at each time step as the point that minimizes the weighted sum of squared distances to the simultaneous lines of sight, weighting each camera by its own pointing uncertainty and by its range to the object. We describe the intrinsic and extrinsic calibration procedure, which uses Automatic Dependent Surveillance-Broadcast (ADS-B) aircraft as reference sources in the absence of stars or fixed landmarks in the LWIR field of view, and the multi-sensor track association scheme that decides which detections belong to the same object. Using one week of data (2026 May 24-30; $1{,}650$ camera-hours, $2.1\times10^{8}$ detections and $5.3\times10^{6}$ tracks), we validate the recovered positions, speeds and accelerations against ADS-B records, recovering distances to within $5$% for $99$% of the aircraft solved from three sites and for $83$% of those solved from a single site pair and speeds to within $5$% for $78$% and $63$% of them respectively. We characterize the identification completeness of the array, which is set by apparent size: the $50$% identification threshold falls at $1.8$ pixels of apparent wingspan.
Comments25 pages, 16 figures, submitted to the scientific journal Sensors
