MOBILE ROBOT NLOS LOCALIZATION TECHNIQUE IN WIRELESS SENSOR NETWORK
Nan Hu, Xifeng Guo, Yu Ying
Shenyang Jianzhu University
Copyright © 2020 by Cayley Nielson Press, Inc.
ISBN: 978-1-7348822-3-0
Cayley Nielson Press Scholarly Monograph Series Book Code No.: 210-10-9
US$180.50
Preface
Due to the availability of such low energy cost sensors, micro processor and radio frequency circuitry for information transmission, there is a wide and rapid diffusion of wireless sensor network (WSN). Since the sensor node is equipped with sensing, processing, and communication modules, the WSN can be used in smart environment for some practical purposes. And WSN is the basic infrastructure of many smart environmental monitoring applications.
Mobile robots have long been playing a vital role in WSNs. As one of the key technologies of WSN, the localization of mobile robot is one of the hottest issues in researches of WSN. The accuracy localization results can be achieved when the propagation environment is line of sight (LOS). However, NLOS (Non-line-of-sight) propagation phenomenon of signals is ubiquitous in practical application environments, and will decrease the accuracy of localization algorithms considerably. NLOS propagation is one of the most important factors affecting the accuracy of mobile robot localization for WSN. In this book, the mobile robot localization issue under NLOS environment is deeply discussed and researched with the view of improving the localization accuracy of mobile robot under NLOS environment.
In chapter 1, the non-parametric location estimation in rough wireless environments for wireless sensor network is introduced. The chapter 2 is about the essential ones of a mobile robot localization method based on a robust Extend Kalman Filter and improved M-Estimation in NLOS environment. In chapter 3, the essential ones of the vote selection mechanisms and probabilistic data association-based NLOS mobile robot localization algorithm is introduced. The chapter 4 is about the essential ones of a novel mobile robot localization method for distributed sensor network with NLOS mitigation is presented. The chapter 5 is about the indoor mobile robot localization in wireless sensor network under the unknown NLOS errors. The last chapter, a robust tracking algorithm based on probability data association for wireless sensor network is presented.
I wanted to thank the authors of the book chapters, especially Zhichao Xue, Ke Xu, Hongwei Li, Rui Zhang, Rui Men, Jialin Sun, Xiyang Liu, Xiaoxi Tian because they offered to the technology of the wireless sensor networks applied to many areas of the latest progress and the existing challenges.
Nan Hu
Shenyang Jianzhu University
Shenyang,Liaoning, China
July 20,2020
Contents
Preface................................................................................................................I
Chapter 1 Non-Parametric Location Estimation in Rough Wireless Environments for Wireless Sensor Network................1
1.1 Introduction........................................................................................................2
1.2 Problem Statement....................................................................................................5
1.2.1 Signal Model........................................................................................................5
1.2.2 Gaussian Mixture Distributions......................................................................................7
1.3 Proposed Method........................................................................................................9
1.3.1 General Concept......................................................................................................9
1.3.2 Kalman Prediction....................................................................................................11
1.3.3 GMD and Multiple Models Combination..................................................................................13
1.3.4 Kalman Update and Location Estimation................................................................................15
1.4 Performance Evaluation and Analysis....................................................................................16
1.5 Conclusions............................................................................................................22
Chapter 2 A Mobile Robot Localization Method Based on a Robust Extend Kalman Filter and Improved M-Estimation in NLOS Environment..23
2.1 Introduction............................................................................................................24
2.2 Related Work............................................................................................................26
2.3 The Architecture of the Proposed Algorithm..............................................................................28
2.4 Proposed Method..........................................................................................................30
2.4.1 System Model............................................................................................................30
2.4.2 Improved Extend Kalman Filter..........................................................................................31
2.4.3 Improved Nearest Neighbor Variable Estimation Localization Algorithm....................................................35
2.5 Simulation Results........................................................................................................40
2.6 Conclusions..............................................................................................................49
Chapter 3 Vote Selection Mechanisms and Probabilistic Data Association-based NLOS Mobile Robot Localization Algorithm........50
3.1 INTRODUCTION..............................................................................................................50
3.2 Architecture of Proposed Algorithm........................................................................................55
3.3 NLOS Localization Based on Voting Selection Mechanisms....................................................................57
3.3.1 System Model............................................................................................................57
3.3.2 Measurement data preprocessing based on voting selection mechanisms......................................................58
3.3.3 Probabilistic data association algorithm based on voting selection mechanisms............................................62
3.3.4 Linear least square algorithm based on the selection of beacon node......................................................68
3.4 Simulation and Experiment Results..........................................................................................70
3.4.1 Simulation Results........................................................................................................70
3.4.2 Experiment Results........................................................................................................79
3.5 Conclusions................................................................................................................88
Chapter 4 A Novel Mobile Robot Localization Method for Distributed Sensor Network with Non-Line-of-Sight Error Mitigation........89
4.1 Introduction................................................................................................................89
4.2. Background.................................................................................................................93
4.2.1 System Model..............................................................................................................93
4.2.2 Probabilistic Data Association Method......................................................................................97
4.3. Proposed NLOS Localization Method............................................................................................98
4.4. Simulation Results..........................................................................................................103
4.5. Conclusions.................................................................................................................111
Chapter 5 Indoor Mobile Robot Localization in Wireless Sensor Network under Unknown NLOS Errors..................................113
5.1 Introduction..................................................................................................................113
5.2 System Model..................................................................................................................117
5.3. Implementation of the Proposed Algorithm......................................................................................118
5.3.1 Likelihood Matrix based Correction..........................................................................................119
5.3.2 Kalman Filter..............................................................................................................121
5.3.3 H-infinity Filter..........................................................................................................123
5.3.4 Mixed Filter and Location Estimation........................................................................................125
5.4 Performance Evaluation........................................................................................................126
5.4.1 The NLOS errors obey Gaussian distribution..................................................................................130
5.4.2 The NLOS errors obey Uniform distribution....................................................................................133
5.4.3 The NLOS errors obey Exponential distribution................................................................................135
5.5 Conclusions....................................................................................................................135
Chapter 6 A Robust Tracking Algorithm Based on Probability Data Association for Wireless Sensor Network............................136
6.1 Introduction....................................................................................................................137
6.2 Problem Statement................................................................................................................142
6.2.1 Signal Model....................................................................................................................142
6.2.2 A Brief Introduction Existing Methods..........................................................................................144
6.3 Proposed Method................................................................................................................147
6.3.1 General Concept..............................................................................................................147
6.3.2 Interaction..................................................................................................................148
6.3.3. Model matching...............................................................................................................149
6.4 Experiment and Result Analysis..................................................................................................160
6.4.1. Gaussian distribution........................................................................................................162
6.4.2. Uniform distribution..........................................................................................................168
6.4.3. Exponential distribution......................................................................................................172
6.4.4. Experimental results..........................................................................................................176
6.5. Conclusions......................................................................................................................179
References..........................................................................................................................181
Readership
This book should be useful for students, scientists, engineers and professionals working in the areas of optoelectronic packaging, photonic devices, semiconductor technology, materials science, polymer science, electrical and electronics engineering. This book could be used for one semester course on adhesives for photonics packaging designed for both undergraduate and graduate engineering students.
