台湾地籍测量的新挑战:结合 CORS 数据和在线 PPP 服务的可行性分析

IF 1.2 Q4 REMOTE SENSING Journal of Applied Geodesy Pub Date : 2024-07-26 DOI:10.1515/jag-2024-0036
M. Ho, Ta-Kang Yeh, Tung-Shan Liao, Y. Chung
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引用次数: 0

摘要

全球导航卫星系统的相对定位是一项历史悠久的测量标准,通常需要高昂的人力和设备成本。在线精确点定位(PPP)最大程度地降低了这些成本,是一种具有成本效益的替代方法。然而,从 ITRF2014 到 TWD97[2010] 坐标系的过渡带来了独特的挑战。本研究利用 2018 年连续运行基准站(CORS)数据评估了五种 PPP 服务(AUSPOS、OPUS、CSRS-PPP、magicGNSS 和 RTX-PP)的功效。根据七参数转换,我们系统地比较了这些服务,以确定满足台湾大地测量需求的最佳解决方案。我们的分析表明,RTX-PP 性能优越,可在 24 小时内达到 1 厘米的精度,在 1 小时内达到 4 厘米的精度。即使从 2018 年 9 月 9 日起的短时间观测间隔内,大多数站点也达到了这些精度标准。然而,由于 GNSS 数据质量的变化,超过 6 厘米精度阈值的可能性为 24.1%。针对这一问题,我们采用G-Nut软件对各区域的台站数据质量进行分析,根据数据比和周期滑移推荐台站选择,以有效提高PPP解算精度。
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A new challenge for cadastral surveying in Taiwan: feasibility analysis using combination on CORS data and online PPP service
Relative GNSS positioning, a longstanding measurement standard, often incurs high manpower and equipment costs. Online Precise Point Positioning (PPP) presents a cost-effective alternative by minimizing these expenses. However, transitioning from the ITRF2014 to the TWD97[2010] coordinate system presents unique challenges. This study evaluates the efficacy of five PPP services – AUSPOS, OPUS, CSRS-PPP, magicGNSS, and RTX-PP – using 2018 Continuously Operating Reference Stations (CORS) data. Following a seven-parameter transformation, we systematically compared these services to identify the optimal solution for Taiwan’s geodetic survey needs. Our analysis reveals that RTX-PP offers superior performance, achieving 1 cm accuracy over 24 h and 4 cm accuracy over 1 h. Most stations met these accuracy standards, even during short observation intervals from September 9, 2018. Nonetheless, there is a 24.1 % likelihood of exceeding the 6 cm accuracy threshold due to variations in GNSS data quality. To address this, we employed G-Nut software to analyze station data quality across regions, recommending station selection based on data ratio and cycle slips to improve PPP solution accuracy effectively.
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来源期刊
Journal of Applied Geodesy
Journal of Applied Geodesy REMOTE SENSING-
CiteScore
2.30
自引率
7.10%
发文量
30
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