A Robust Adaptive Extended Kalman Filter Based on an Improved Measurement Noise Covariance Matrix for the Monitoring and Isolation of Abnormal Disturbances in GNSS/INS Vehicle Navigation

Article Remote Sensing

Feature-based GNSS positioning error consistency optimization for GNSS/INS integrated system

Xiaoji Niu et al.

Summary: This study focuses on optimizing GNSS error estimation based on machine learning to improve the consistency with the actual positioning error and the reliability of the GNSS/INS integrated system.

GPS SOLUTIONS (2023)

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Article Remote Sensing

Robust state and protection-level estimation within tightly coupled GNSS/INS navigation system

Shuchen Liu et al.

Summary: To address the issues of satellite signal disturbances and poor parametrization in urban environments, an innovative scheme based on extended H-infinity filter and zonotope is proposed for high-rate and highly accurate vehicle-state estimation and protection-level generation. Experimental results demonstrate significant advantages of this scheme over the conventional extended Kalman filter in terms of navigation accuracy and robustness under various GNSS measurement parametrizations and environmental circumstances. The zonotope-based protection-level calculation is proven to be valid, computationally affordable, and feasible for real-time implementations.

GPS SOLUTIONS (2023)

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Article Environmental Sciences

Outlier Detection Based on Nelder-Mead Simplex Robust Kalman Filtering for Trustworthy Bridge Structural Health Monitoring

Liangliang Hu et al.

Summary: Structural health monitoring (SHM) is essential for the safety of aging bridges. Global Navigation Satellite Systems (GNSS) can provide valuable spatiotemporal information for effective bridge structural health monitoring (BSHM), but GNSS measurements often have outliers that can significantly affect the accuracy and reliability of BSHM. Previous studies have explored the integration of multi-rate Kalman filter (MKF) with adaptive algorithms for accurate BSHM, but frequent parameter adjustments are still required. This study proposes an outlier detection method using a robust multi-rate Kalman filter (RMKF) to improve the accuracy of BSHM using GNSS and accelerometer data.

REMOTE SENSING (2023)

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Article Environmental Sciences

A Multi-GNSS/IMU Data Fusion Algorithm Based on the Mixed Norms for Land Vehicle Applications

Chen Jiang et al.

Summary: This paper proposes a mixed norm-based data fusion algorithm for GNSS/INS integrated navigation systems. The algorithm is tested and compared with conventional filtering algorithms using land vehicle data collected through multi-GNSS and IMU systems. The results show improved precision and reduced influence of outlying measurements and uncertain noises. Additionally, the algorithm introduces an open issue for geodetic applications with mixed norms.

REMOTE SENSING (2023)

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Article Remote Sensing

Adaptive non-holonomic constraint aiding Multi-GNSS PPP/INS tightly coupled navigation in the urban environment

Sixiang Cheng et al.

Summary: The non-holonomic constraint (NHC) is a classical motion-based model for land vehicle precise point positioning (PPP)/inertial navigation system (INS) tightly coupled model. However, the conventional NHC stochastic model cannot adapt to the changing satellite observation conditions in the urban environment. This paper proposes a novel NHC stochastic model considering the changing observation conditions to prevent filtering error divergence and improve filtering stability in the urban environment.

GPS SOLUTIONS (2023)

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Article Engineering, Aerospace

A novel method of ambiguity resolution and cycle slip processing for single-frequency GNSS/INS tightly coupled integration system

Dashuai Chai et al.

Summary: The paper proposes a method of ambiguity resolution and cycle slip processing with INS aiding, which shows optimal ambiguity fixing rate and positioning performance. The algorithm can effectively detect and accurately repair cycle slips, even when GPS, GLONASS, and BDS are interrupted.

ADVANCES IN SPACE RESEARCH (2022)

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Article Environmental Sciences

An Algorithm to Assist the Robust Filter for Tightly Coupled RTK/INS Navigation System

Zun Niu et al.

Summary: The Real-Time Kinematic (RTK) positioning algorithm is a promising technique for high-precision positioning, but its performance can degrade in areas with poor GNSS conditions. This study proposes an improved algorithm, called Robust Kalman Filter (RKF), for RTK coupling with Inertial Navigation System (INS). The algorithm introduces the use of Carrier-to-Noise Ratio (CNR) for outlier detection and achieves improved accuracy compared to the traditional RKF. The majority of the code is also made open source on GitHub.

REMOTE SENSING (2022)

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Article Remote Sensing

New time-differenced carrier phase approach to GNSS/INS integration

Yi Mao et al.

Summary: The accuracy of navigation information is crucial for modern transport systems. Conventional integrated GNSS/IMU algorithms often suffer from low-quality GNSS measurements in urban environments. In this study, we propose a TDCP-controlled GNSS/IMU integration scheme that provides more accurate estimates of position changes.

GPS SOLUTIONS (2022)

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Article Engineering, Electrical & Electronic

Residual Attention Network-Based Confidence Estimation Algorithm for Non-Holonomic Constraint in GNSS/INS Integrated Navigation System

Yimin Xiao et al.

Summary: The integration of GNSS and INS is widely used for land vehicle navigation, but fails to provide reliable results under GNSS-denied conditions. Deep learning has been introduced to improve positioning accuracy during GNSS outage, with attention mechanism playing a key role in noise covariance estimation for optimal filtering fusion.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2021)

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Article Remote Sensing

Performance evaluation of the filters with adaptive factor and fading factor for GNSS/INS integrated systems

Chen Jiang et al.

Summary: The study compares the performance of filters with adaptive and fading factors in the GNSS/INS integrated system, showing that the filter with the adaptive factor is more likely to avoid filter divergence and achieve stable performance in high-dimensional nonlinear problems. Theoretical analysis is conducted to understand the differences between these filters and their impact on the overall performance.

GPS SOLUTIONS (2021)

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Article Geochemistry & Geophysics

Integer-estimable FDMA model as an enabler of GLONASS PPP-RTK

Baocheng Zhang et al.

Summary: PPP-RTK combines PPP and RTK techniques, utilizes the IE-FDMA model to address integer ambiguity in GLONASS PPP-RTK, and deals with inter-frequency biases in various network configurations.

JOURNAL OF GEODESY (2021)

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Article Geochemistry & Geophysics