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

Liu, Shuchen; Wang, Kaizheng; Abel, Dirk

doi:10.1007/s10291-023-01447-z

Cited by 12 publications

(5 citation statements)

References 22 publications

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“…The classical EKF and LS methods had almost identical worse performances. In [60], the authors compared the standard GNSS/INS EKF integrated integrity monitoring scheme with a novel approach based on the Extended H-infinity Filter (EHF) and PL calculation using zonotope. The comparison is made for the scenarios in which the filters are initialized with bad parameters, in which the EHF is clearly advantageous.…”

Section: Hybrid and Multi-methods Integrity Monitoringmentioning

confidence: 99%

Recent Advances in Sensor Integrity Monitoring Methods—A Review

2022

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In face of the high complexity of modern systems and the increasing reliance on technology, the strategies and methods to evaluate the integrity of systems and the information they provide are of great importance. The use of sensors to provide important information in various applications has become ubiquitous, which puts more pressure on the accuracy of sensor measurements. In the navigation field, in particular, the integrity of positioning information provided by sensors can be critical, as failures can lead to fatalities and catastrophic damages. Extensive research has been done into methods to assess and improve the integrity of positioning information provided by GNSS receivers, led by the high safety requirements in the aviation field. More recently, a shift into the research of integrity solutions suitable for the challenging positioning requirements of autonomous vehicles in urban environment has been a trend. There have been extensive advancements in developing integrity monitoring algorithms for GNSS and navigation in general. However, these methods have not been sufficiently extended into other types of sensors, and the development of integrity methods outside the navigation field have been scarce and scattered. This work aims to provide an overview of recent advances in the integrity monitoring field, including research outside the navigation domain. The goal is to give an introduction to the integrity monitoring concept to a broader audience, as these techniques have been highly specialized by GNSS experts and navigation related research, fostering multi-disciplinary approaches and creative use of existing methods in different areas and applications.

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Section: Hybrid and Multi-methods Integrity Monitoringmentioning

confidence: 99%

Recent Advances in Sensor Integrity Monitoring Methods—A Review

2022

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“…Selected references [5] for The state transition matrix 1 F (t) and the driving matrix 1 G (t), while 1 W (t) represents the vector of system noise.…”

Section: Enhanced Error State Equation For Ins/gnss System By Expert ...mentioning

confidence: 99%

Multi-vehicle cooperative combined navigation system based on GNSS visual inertia

Huang,

Xu,

Xia

et al. 2024

Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024)

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This paper delineates a comprehensive framework for an integrated multi-sensor navigation system that boasts high precision and robustness. The fusion of various subsystems, including GNSS, INS, vision sensors, and multi-vehicle cooperative mechanisms, is facilitated through a federated Kalman filter algorithm. This integration enables the navigation system to maintain stable and precise positioning amidst diverse and challenging scenarios, including GNSS-compromised and visually obstructed environments. Moreover, the synergy of multi-vehicle collaboration significantly augments the accuracy of the system. Empirical evaluations demonstrate that our hybrid method enhances positioning error accuracy by 25% over traditional GNSS/INS integrated navigation systems.

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“…Then, maximum likelihood estimation [24], variational Bayesian estimation [25], and convolutional neural networks (CNN) [26] are also used for Kalman filter optimization to dynamically approximate measurement noise. Finally, other filtering methods [27] are also considered as integrated navigation filters. Moreover, some studies have proposed using artificial intelligence methods to assist GNSS/ INS integrated navigation when GNSS signals are interrupted [28].…”

Section: Introductionmentioning

confidence: 99%

A robust integrated navigation optimization method for USV in signal occlusion environment

Lou,

Liu,

et al. 2024

Phys. Scr.

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Unmanned surface vehicles (USV) can use global navigation satellite systems (GNSS) and inertial navigation systems (INS) for combined positioning and navigation. However, buildings such as port facilities and bridges blocking GNSS signals will increase the error in the discriminator output in the GNSS vector tracking loop and reduce positioning accuracy. Meanwhile, due to the cumulative error in the inertial navigation system, the credibility of the navigation results when the signal is blocked is further reduced. In this regard, this study proposes a robust integrated navigation optimization method. Specifically, the RTS smoothing optimized Kalman filter is used to constrain the carrier phase error and code phase error output by the discriminator, which can dynamically adjust the gain of the vector tracking loop, thereby improving the signal tracking capability. Simultaneously, the prediction results of the gated recurrent unit (GRU) network optimized based on the attention mechanism are combined with the inertial navigation system to improve navigation accuracy. Furthermore, an adaptive Kalman filter is utilized as the integrated navigation filter. The actual path of the carrier refers to the navigation solution of the existing receiver. In the open environment, the proposed optimization method reduces horizontal positioning error and speed error by 44.7% and 37.1% respectively compared with existing methods. Simultaneously, it can effectively improve the robustness of positioning in signal obstruction environments. The proposed integrated navigation method provides new possibilities for optimizing USV navigation solutions.

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

Cited by 12 publications

References 22 publications

Recent Advances in Sensor Integrity Monitoring Methods—A Review

Recent Advances in Sensor Integrity Monitoring Methods—A Review

Multi-vehicle cooperative combined navigation system based on GNSS visual inertia

A robust integrated navigation optimization method for USV in signal occlusion environment

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