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With the gradual development and modernization of satellite navigation systems, using observation information from multi-GNSS has become one of the hot-spot issues in recent years. Multi-system loose combinations form double-difference observation equations within their respective systems, and the positioning effect is improved. However, the interchangeability and compatible interoperability between global navigation satellite systems (GNSS) cannot be truly realized. At the same time, when the number of visible satellites decreases abruptly, the positioning performance deteriorates sharply. This paper focuses on the GNSS multi-system tight combination relative positioning technique, gives a mathematical model of multi-system tight combination relative positioning considering differential inter-system bias (DISB), and analyzes the time-varying characteristics of DISB at overlapping and non-overlapping frequencies among GPS/Galileo, GPS/BDS, and GPS/QZSS in terms of receiver brand, temperature, and receiver restart. The GNSS tight combination relative positioning performance is verified by static data from Curtin University and dynamic data measured at Taiyuan University of Technology. The results show that compared with loose combination, the ambiguity-fixed rate increases from 62.18% to 97.60% for static data and from 74.97% to 99.53% for dynamic data when the elevation mask angle is 50°, resulting in a significant improvement in positioning performance.

A satellite altimetry mission can measure high-precision sea surface height (SSH) to recover a marine gravity field. The reference gravity field model plays an important role in this recovery. In this paper, reference gravity field models with different degrees are used to analyze their effects on the accuracy of recovering gravity anomalies using the inverse Vening Meinesz (IVM) method. We evaluate the specific performance of different reference gravity field models using CryoSat-2 and HY-2A under different marine bathymetry conditions. For the assessments using 1-mGal-accuracy shipborne gravity anomalies and the DTU17 model based on the inverse Stokes principle, the results show that CryoSat-2 and HY-2A using XGM2019e_2159 obtains the highest inversion accuracy when marine bathymetry is less than 2000 m. Compared with the EGM2008 model, the accuracy of CryoSat-2 and HY-2A is improved by 0.6747 mGal and 0.6165 mGal, respectively. A weighted fusion method that incorporates multiple reference models is proposed to improve the accuracy of recovering gravity anomalies using altimetry satellites in shallow water. The experiments show that the weighted fusion method using different reference models can improve the accuracy of recovering gravity anomalies in shallow water.

A dynamic gravimeter with an atomic interferometer (AI) can perform absolute gravity measurements with high precision. AI-based dynamic gravity measurement is a type of joint measurement that uses an AI sensor and a classical accelerometer. The coupling of the two sensors may degrade the measurement precision. In this study, we analyzed the cross-coupling effect and introduced a recovery vector to suppress this effect. We improved the phase noise of the interference fringe by a factor of 1.9 by performing marine gravity measurements using an AI-based gravimeter and optimizing the recovery vector. Marine gravity measurements were performed, and high gravity measurement precision was achieved. The external and inner coincidence accuracies of the gravity measurement were ±0.42 mGal and ±0.46 mGal after optimizing the cross-coupling effect, which was improved by factors of 4.18 and 4.21 compared to the cases without optimization.

In response to the lack of specific demonstration and analysis of the research on the necessity of the Lie group strapdown inertial integrated navigation error model based on the Euler angle, two common integrated navigation systems, strapdown inertial navigation system/global navigation satellite system (SINS/GNSS) and strapdown inertial navigation system/doppler velocity log (SINS/DVL), are used as subjects, and the piecewise constant system (PWCS) matrix, based on the Lie group error model, is established. From three aspects of variance estimation, the observability and performance of the system with large misalignment angles for low, medium, and high accuracy levels, traditional error model, Lie group left error model, and right error model are compared. The necessity of research on Lie group error model is analyzed quantitatively and qualitatively. The experimental results show that Lie group error model has better stability of variance estimation, estimation accuracy, and observability than traditional error model, as well as higher practical value.