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2023 | Book

Resilient Fusion Navigation Techniques: Collaboration in Swarm

Authors: Rong Wang, Zhi Xiong, Jianye Liu

Publisher: Springer Nature Singapore

Book Series : Unmanned System Technologies

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About this book

This book describes the resilient navigation techniques under the background of collaboration in swarm. The significance of this work is that it focuses on the navigation enhancement by collaboration in swarm rather than ground infrastructure, which exploit potentialities of swarm in GNSS restricted environment.

Although unmanned swarm is receiving greater attention, both through theoretical research and through increasing mention in the industrial developments, the navigation promotion by effective and efficient collaboration remains largely unexplored. While my scholarly work has explored some of the modeling, error characteristic, fusion algorithm, fault detection, and isolation aspects of the “adaptive navigation system” (such as the navigation system of robots and ground vehicles, aircrafts, aerospace vehicles, and unmanned aerial vehicles), the present book proposes the specialized investigation on the navigation with the resilient character, which could maintain the performance by essential collaboration with members in swarm in GNSS degradation environment.

This book focused on the resilient navigation techniques under the background of collaboration in swarm. The key techniques of collaborative resilient navigation are proposed, including the collaboration framework, collaborative observation modeling, geometry optimization, integrity augmentation, and fault detection. The experiments are also carried out to validate the effectiveness of the corresponding techniques.

Table of Contents

Frontmatter
Chapter 1. Introduction
Abstract
Aerial swarms are a development trend for future unmanned systems, and they show significant advantages for improving navigation accuracy and reliability. Unlike in traditional airborne and ground-based navigation augmentation, unmanned swarms can achieve resilient navigation fusion capabilities through intermember collaboration. This chapter discusses the advantages of an aerial swarm and the benefits of introducing collaboration in the swarm. The sensors used for relative observation in an aerial swarm are introduced. The existing research work related to collaborative resilient navigation as well as fault-tolerant navigation technology with collaboration is introduced through a literature overview. The motivations of this book are discussed, and the organization of the content is described.
Rong Wang, Zhi Xiong, Jianye Liu
Chapter 2. Collaborative Resilient Navigation Frameworks
Abstract
There are several possible structures for the organization of the members of an aerial swarm, indicating different collaborative relationships. Meanwhile, there are different frameworks for fusing observations in collaborative navigation. These structures and frameworks determine the various approaches for realizing resilient navigation fusion through collaboration in an aerial swarm. This chapter discusses the leader–follower, parallel, and hierarchical collaborative navigation structures. Additionally, collaborative localization-based and collaborative observation-based fusion frameworks for resilient navigation are proposed.
Rong Wang, Zhi Xiong, Jianye Liu
Chapter 3. Modelling for Resilient Navigation via Collaboration
Abstract
The modelling of observations and errors is the foundation of resilient navigation fusion. The relative observations that can be introduced into collaborative resilient fusion vary with the available relative measurement sensors. Therefore, it is necessary to perform modelling in accordance with the constraint properties of different relative observations of navigation parameters. This chapter discusses the modelling of collaborative observations as well as the corresponding error covariance, presenting approaches based on range measurements, range difference measurements, bearing-only measurements, and vector-of-sight measurements. In these analyses, modelling is carried out for both the hierarchical and parallel navigation structures of an aerial swarm.
Rong Wang, Zhi Xiong, Jianye Liu
Chapter 4. Collaborative Localization-Based Resilient Navigation Fusion
Abstract
The collaborative localization-based framework is one of the typical approaches used to realize resilient navigation fusion. In this approach, the relative observations from collaborating anchor members are first utilized to solve for the locations of label members who suffer from navigation degradation, and the results are then fused with the local measurements of these label members to realize navigation augmentation. This chapter discusses collaborative localization algorithms. The online estimation of the collaborative localization covariance is investigated. Resilient fusion models and processes for obtaining collaborative localization solutions are introduced with simulated examples.
Rong Wang, Zhi Xiong, Jianye Liu
Chapter 5. Collaborative Observation-Based Resilient Navigation Fusion
Abstract
The collaborative observation-based framework is another typical approach for realizing resilient navigation fusion. In this approach, the relative observations from collaborating anchor members are directly fused with the local measurements without performing localization first. On the basis of collaborative observation modelling, this chapter discusses collaborative observation-based navigation algorithms with hierarchical and parallel collaborative navigation structures. Simulated examples for both situations are also provided.
Rong Wang, Zhi Xiong, Jianye Liu
Chapter 6. Collaborative Geometry Optimization in Resilient Navigation
Abstract
The geometry of the collaborating partners is one of the factors that influence the effectiveness of collaborative resilient navigation. In this chapter, an improved geometric dilution of precision is introduced to quantitatively evaluate geometric configurations in collaborative resilient navigation fusion. The influence of geometry on the accuracy of collaborative resilient navigation fusion is discussed in both the GNSS-augmented and GNSS-denied situations. Geometry optimization algorithms based on a geometric analysis method and an algebraic search method are proposed, with simulated examples.
Rong Wang, Zhi Xiong, Jianye Liu
Chapter 7. Collaborative Integrity Augmentation in Resilient Navigation
Abstract
Navigation integrity is critical for the reliability of aerial swarms. The geometric configuration of the selected partners for collaboration has a significant impact on the effectiveness and efficiency of the collaborative integrity enhancement. In this chapter, an improved protection level is introduced to quantitatively evaluate navigation integrity in collaborative resilient navigation fusion. The influence of geometry on integrity in collaborative resilient navigation fusion is discussed in both the GNSS-augmented and GNSS-denied situations. Integrity optimization algorithms based on the geometric analysis method and the algebraic search method are proposed, with simulated examples.
Rong Wang, Zhi Xiong, Jianye Liu
Chapter 8. Collaborative Fault Detection in Resilient Navigation
Abstract
Fault diagnosis is a key component of navigation integrity assurance for aerial swarms. The redundancy of a navigation system is enhanced with the introduction of observations from optimally configured collaborative partners, thus improving the capabilities of fault detection, identification, and isolation. In this chapter, fault detection, identification, and exclusion based on collaborative integrity augmentation are discussed. Multifault detection based on multiple hypothesis solution separations in collaborative resilient navigation fusion for an aerial swam is proposed, with simulated examples.
Rong Wang, Zhi Xiong, Jianye Liu
Chapter 9. Summary and Scope
Abstract
Resilient fusion techniques for collaborative navigation in aerial swarms is an exciting area of research, and much work remains to be explored in the future. In this chapter, the research presented in this book is summarized, and the conclusions are comprehensively discussed. An outlook on the trends of development in research on collaborative resilient navigation fusion is discussed, and recommendations for future work are provided.
Rong Wang, Zhi Xiong, Jianye Liu
Metadata
Title
Resilient Fusion Navigation Techniques: Collaboration in Swarm
Authors
Rong Wang
Zhi Xiong
Jianye Liu
Copyright Year
2023
Publisher
Springer Nature Singapore
Electronic ISBN
978-981-19-8371-9
Print ISBN
978-981-19-8370-2
DOI
https://doi.org/10.1007/978-981-19-8371-9

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