With the rapid development of the satellite navigation industry, low-cost and high-precision Global Navigation Satellite System (GNSS) positioning has recently become a research hotspot. The traditional application of GNSS may be further extended thanks to the low cost of measuring instruments, but effective methods are also desperately needed due to the low quality of the data obtained using these instruments. Thus, in this paper, we propose the analysis and evaluation of the ambiguity fixed-rate and positioning accuracy of single-frequency Global Positioning System (GPS) and BeiDou Navigation Satellite System (BDS) data, collected from a low-cost u-blox receiver, based on the Constrained LAMBDA (CLAMBDA) method with a baseline length constraint, instead of the classical LAMBDA method. Three sets of experiments in different observation environments, including two sets of static short-baseline experiments and a set of dynamic vehicle experiments, are adopted in this paper. The experiment results show that, compared to classical LAMBDA method, the CLAMBDA method can significantly improve the success rate of the GNSS ambiguity resolution. When the ambiguity is fixed correctly, the baseline solution accuracy reaches 0.5 and 1 cm in a static scenario, and 1 and 2 cm on a dynamic platform.

Reliable and accurate carrier phase ambiguity resolution is the key to high-precision Global Navigation Satellite System (GNSS) positioning and application. With the fast development of modern GNSS, the increased number of satellites and ambiguities makes it hard to fix all ambiguities completely and correctly. The partial ambiguity fixing technique, which selects a suitable subset of high-dimensional ambiguities to fix, is beneficial for improving the fixed success rate and reliability of ambiguity resolution. In this contribution, the bootstrapping success rate, bounded fixed-failure ratio test, and the new defined baseline precision defect are used for the selection of the ambiguity subset. Then a model and data dual-driven partial ambiguity resolution method is proposed with the above three checks imposed on it, which is named the Triple Checked Partial Ambiguity Resolution (TC-PAR). The comprehensive performance of TC-PAR compared to the full-fixed LAMBDA method is also analyzed based on several criteria including the fixed rate, the fixed success rate and correct fixed rate of ambiguity as well as the precision defect and RMS of the baseline solution. The results show that TC-PAR could significantly improve the fixed success rate of ambiguity, and it has a comparable baseline precision to the LAMBDA method, both of which are at centimeter level after ambiguities are fixed.

This paper presents an analysis of regional terrestrial water storage (TWS) changes and drought characteristics in Southwest China, encompassing Sichuan Province, Chongqing Municipality, Yunnan Province, and Guizhou Province. Existing geodetic datasets, such as those from the Gravity Recovery and Climate Experiment (GRACE) and its successor satellites (GRACE Follow-On), as well as Global Navigation Satellite System (GNSS) data, face significant challenges related to limited spatial resolution and insufficient station distribution. To address these issues, we propose a novel inversion method that integrates GNSS and GRACE/GFO data by establishing virtual stations for GRACE/GFO data and determining the weight values between GNSS and GRACE/GFO using the Akaike Bayesian Information Criterion (ABIC). This method allows for estimating the TWS changes from December 2010 to June 2023 and monitoring drought conditions in conjunction with hydrometeorological data (precipitation, evapotranspiration, and runoff). The results show strong correlations between TWS changes from the joint inversion and GNSS (0.98) and GRACE/GFO (0.69). The Joint Drought Severity Index (Joint-DSI) indicates five major drought events, with the most severe occurring from July 2022 to June 2023, with an average deficit of 86.133 km³. Extreme drought primarily impacts Sichuan and Yunnan, driven by abnormal precipitation deficits. The joint inversion methodology presented in this study provides a practical approach for monitoring TWS changes and assessing drought characteristics in Southwest China. This paper leverages the complementary strengths of GNSS and GRACE/GFO data and offers new insights into regional water resource management and drought detection.

With the rapid development of global navigation satellite system (GNSS), GNSS data products have been widely used for high-precision positioning and navigation applications. They are typically downloaded from the international GNSS service (IGS) analysis centers and continuously operating reference stations (CORS). However, the conventional GNSS data download method is cumbersome, repetitive, and time-consuming, and it is challenging to meet the demands for rapid acquisition of multi-source data products. Therefore, we have developed a GNSS data download software with Python, which provides an interactive interface for the Windows or Linux operating system to realize the efficient and stable download for a large amount of GNSS data. The software includes five main function modules: Global IGS Data, Post-Processing Product, Regional CORS Data, Custom Download, and Data Decompression. It has the characteristics of diverse data products, map interaction support, and station information retrieval, which can meet the needs of different users.