以三維向量空間資訊進行都會區衛星可視性分析

Abstract

全球導航衛星系統（Global Navigation Satellite System，GNSS）提供全時性、全天候的連續及高精度三維位置與時間資訊，已被廣泛運用在測量工程與其他日常用途。然而，當地面點位受遮蔽物阻礙時，會嚴重干擾訊號傳遞，進而降低到衛星定位精度，若能針對這些遮蔽區域進行事前評估，就能設計適當的程序或替代方案，以確保或彌補測量成果品質。然而，此類分析牽涉到測站與周邊環境的複雜關係計算，分析過程費時耗力。本研究便以衛星可視性分析原理為主軸，引入空載光達點雲資料並結合二維建物成果圖進行真實地形遮蔽分析，並使用點雲柱狀分層法將遮蔽物儲存至建物向量式資料庫，再納入衛星軌道計算後求出衛星相對於測站的關係，即可計算出單一測站於一日內之PDOP預測值，進而求得出該日最佳觀測時刻。由數值實驗驗證顯示，使用本研究提出之分析流程約可達90%以上的預測衛星顆數正確率，而在時間效率上相較未經處理的原始點雲，速度快約11,000~36,000倍，證實本研究得以提出一套適用於大範圍區域的衛星可視性以及定位品質評估之可行方案。

Global Navigation Satellite System (GNSS) is a matured modern technique for spatial data acquisition, and it has been widely used in the surveying field as well as in other engineering applications. However, how to make sure the accuracy of satellite positioning is still a crucial research topic. While the line between a satellite and a receiver on the ground is blocked by obstacles, the signal of satellite will be interfered. It will lead to bad accuracy of satellite positioning. Because topographic effects are considered the main factor that directly block signal transmission between satellites and receivers, this study integrated aerial borne LiDAR point clouds and a 2D building boundary map to provide reliable 3D spatial information to analyze topographic effects. Using such vector data not only reflected high-quality GNSS satellite visibility calculations, but also significantly reduced data amount and processing time. For this reason, the research aims to analyze the satellite visibility, which can simultaneously possess an efficient and reliable data acquisition without wasting time and human efforts. This study proposes using superimposed column method to analyze GNSS receivers’ surrounding environments. The experiment result shows that using the superimposed column method can achieve a prediction accuracy of more than 90%, and the time efficiency is about 11,000~36,000 times faster than the original point cloud. It is confirmed that this study can propose a set of feasible solutions suitable for satellite visibility and positioning quality assessment in a large area.