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E-raamat: Pedestrian Inertial Navigation with Self-Contained Aiding

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"This book is dedicated to the topic of self-contained aiding techniques in pedestrian inertial navigation. It begins with an introduction that presents the general concept of navigation including major navigation and aiding techniques. Chapter 2 describes inertial navigation implementation, where Inertial Measurement Units (IMUs) are utilized for navigation purposes. Chapter 3 presents an error analysis in the strapdown inertial navigation. Chapter 4 discusses the zero-velocity update (ZUPT) aided inertial navigation algorithm. Chapter 5 presents ranging techniques for navigation compensation. This includes both foot-to-foot ranging and inter-agent ranging. The book concludes with a technological perspective on self-contained pedestrian inertial navigation with an outlook for development of the Ultimate Navigation Chip (uNavChip) technology"--

Explore an insightful summary of the major self-contained aiding technologies for pedestrian navigation from established and emerging leaders in the field 

Pedestrian Inertial Navigation with Self-Contained Aiding delivers a comprehensive and broad treatment of self-contained aiding techniques in pedestrian inertial navigation. The book combines an introduction to the general concept of navigation and major navigation and aiding techniques with more specific discussions of topics central to the field, as well as an exploration of the future of the future of the field: Ultimate Navigation Chip (uNavChip) technology. 

The most commonly used implementation of pedestrian inertial navigation, strapdown inertial navigation, is discussed at length, as are the mechanization, implementation, error analysis, and adaptivity of zero-velocity update aided inertial navigation algorithms. The book demonstrates the implementation of ultrasonic sensors, ultra-wide band (UWB) sensors, and magnetic sensors. Ranging techniques are considered as well, including both foot-to-foot ranging and inter-agent ranging, and learning algorithms, navigation with signals of opportunity, and cooperative localization are discussed. Readers will also benefit from the inclusion of: 

  • A thorough introduction to the general concept of navigation as well as major navigation and aiding techniques 
  • An exploration of inertial navigation implementation, Inertial Measurement Units, and strapdown inertial navigation 
  • A discussion of error analysis in strapdown inertial navigation, as well as the motivation of aiding techniques for pedestrian inertial navigation 
  • A treatment of the zero-velocity update (ZUPT) aided inertial navigation algorithm, including its mechanization, implementation, error analysis, and adaptivity 

Perfect for students and researchers in the field who seek a broad understanding of the subject, Pedestrian Inertial Navigation with Self-Contained Aiding will also earn a place in the libraries of industrial researchers and industrial marketing analysts who need a self-contained summary of the foundational elements of the field. 

Author Biographies xi
List of Figures
xiii
List of Tables
xix
1 Introduction
1(16)
1.1 Navigation
1(1)
1.2 Inertial Navigation
2(3)
1.3 Pedestrian Inertial Navigation
5(4)
1.3.1 Approaches
6(1)
1.3.2 IMU Mounting Positions
7(1)
1.3.3 Summary
8(1)
1.4 Aiding Techniques for Inertial Navigation
9(4)
1.4.1 Non-self-contained Aiding Techniques
9(1)
1.4.1.1 Aiding Techniques Based on Natural Signals
9(1)
1.4.1.2 Aiding Techniques Based on Artificial Signals
10(1)
1.4.2 Self-contained Aiding Techniques
11(2)
1.5 Outline of the Book
13(1)
References
13(4)
2 Inertial Sensors and Inertial Measurement Units
17(20)
2.1 Accelerometers
17(4)
2.1.1 Static Accelerometers
17(2)
2.1.2 Resonant Accelerometers
19(2)
2.2 Gyroscopes
21(7)
2.2.1 Mechanical Gyroscopes
21(1)
2.2.2 Optical Gyroscopes
22(1)
2.2.2.1 Ring Laser Gyroscopes
22(1)
2.2.2.2 Fiber Optic Gyroscopes
23(1)
2.2.3 Nuclear Magnetic Resonance Gyroscopes
24(1)
2.2.4 MEMS Vibratory Gyroscopes
24(1)
2.2.4.1 Principle of Operation
25(1)
2.2.4.2 Mode of Operation
25(2)
2.2.4.3 Error Analysis
27(1)
2.3 Inertial Measurement Units
28(4)
2.3.1 Multi-sensor Assembly Approach
28(1)
2.3.2 Single-Chip Approach
29(1)
2.3.3 Device Folding Approach
30(1)
2.3.4 Chip-Stacking Approach
31(1)
2.4 Conclusions
32(1)
References
32(5)
3 Strapdown Inertial Navigation Mechanism
37(10)
3.1 Reference Frame
37(1)
3.2 Navigation Mechanism in the Inertial Frame
38(2)
3.3 Navigation Mechanism in the Navigation Frame
40(1)
3.4 Initialization
41(4)
3.4.1 Tilt Sensing
42(1)
3.4.2 Gyrocompassing
43(1)
3.4.3 Magnetic Heading Estimation
44(1)
3.5 Conclusions
45(1)
References
45(2)
4 Navigation Error Analysis in Strapdown Inertial Navigation
47(18)
4.1 Error Source Analysis
47(8)
4.1.1 Inertial Sensor Errors
48(3)
4.1.2 Assembly Errors
51(2)
4.1.3 Definition of IMU Grades
53(1)
4.1.3.1 Consumer Grade
54(1)
4.1.3.2 Industrial Grade
54(1)
4.1.3.3 Tactical Grade
55(1)
4.1.3.4 Navigation Grade
55(1)
4.2 IMU Error Reduction
55(2)
4.2.1 Six-Position Calibration
55(2)
4.2.2 Multi-position Calibration
57(1)
4.3 Error Accumulation Analysis
57(5)
4.3.1 Error Propagation in Two-Dimensional Navigation
58(3)
4.3.2 Error Propagation in Navigation Frame
61(1)
4.4 Conclusions
62(1)
References
63(2)
5 Zero-Velocity Update Aided Pedestrian Inertial Navigation
65(14)
5.1 Zero-Velocity Update Overview
65(3)
5.2 Zero-Velocity Update Algorithm
68(5)
5.2.1 Extended Kalman Filter
68(2)
5.2.2 EKF in Pedestrian Inertial Navigation
70(1)
5.2.3 Zero-Velocity Update Implementation
70(3)
5.3 Parameter Selection
73(3)
5.4 Conclusions
76(1)
References
76(3)
6 Navigation Error Analysis in the ZUPT-Aided Pedestrian Inertial Navigation
79(24)
6.1 Human Gait Biomechanical Model
79(4)
6.1.1 Foot Motion in Torso Frame
80(1)
6.1.2 Foot Motion in Navigation Frame
80(1)
6.1.3 Parameterization of Trajectory
81(2)
6.2 Navigation Error Analysis
83(10)
6.2.1 Starting Point
83(1)
6.2.2 Covariance Increase During Swing Phase
84(3)
6.2.3 Covariance Decrease During the Stance Phase
87(1)
6.2.4 Covariance Level Estimation
88(4)
6.2.5 Observations
92(1)
6.3 Verification of Analysis
93(6)
6.3.1 Numerical Verification
93(1)
6.3.1.1 Effect of ARW
93(2)
6.3.1.2 Effect of VRW
95(1)
6.3.1.3 Effect of RRW
95(1)
6.3.2 Experimental Verification
96(3)
6.4 Limitations of the ZUPT Aiding Technique
99(1)
6.5 Conclusions
100(1)
References
101(2)
7 Navigation Error Reduction in the ZUPT-Aided Pedestrian Inertial Navigation
103(18)
7.1 IMU-Mounting Position Selection
104(6)
7.1.1 Data Collection
105(1)
7.1.2 Data Averaging
105(2)
7.1.3 Data Processing Summary
107(2)
7.1.4 Experimental Verification
109(1)
7.2 Residual Velocity Calibration
110(5)
7.3 Gyroscope O-Sensitivity Calibration
115(2)
7.4 Navigation Error Compensation Results
117(2)
7.5 Conclusions
119(1)
References
119(2)
8 Adaptive ZUPT-Aided Pedestrian Inertial Navigation
121(20)
8.1 Floor Type Detection
121(9)
8.1.1 Algorithm Overview
122(1)
8.1.2 Algorithm Implementation
123(1)
8.1.2.1 Data Partition
123(1)
8.1.2.2 Principal Component Analysis
124(1)
8.1.2.3 Artificial Neural Network
125(2)
8.1.2.4 Multiple Model EKF
127(2)
8.1.3 Navigation Result
129(1)
8.1.4 Summary
130(1)
8.2 Adaptive Stance Phase Detection
130(8)
8.2.1 Zero-Velocity Detector
131(1)
8.2.2 Adaptive Threshold Determination
131(4)
8.2.3 Experimental Verification
135(1)
8.2.4 Summary
136(2)
8.3 Conclusions
138(1)
References
139(2)
9 Sensor Fusion Approaches
141(1)
9.1 Magnetometry
141(1)
9.2 Altimetry
142(1)
9.3 Computer Vision
143(2)
9.4 Multiple-IMU Approach
145(1)
9.5 Ranging Techniques
146(1)
9.5.1 Introduction to Ranging Techniques
147(1)
9.5.1.1 Time of Arrival
147(1)
9.5.1.2 Received Signal Strength
147(1)
9.5.1.3 Angle of Arrival
148(1)
9.5.2 Ultrasonic Ranging
149(1)
9.5.2.1 Foot-to-Foot Ranging
150(1)
9.5.2.2 Directional Ranging
150(3)
9.5.3 Ultrawide Band Ranging
153(1)
9.6 Conclusions
154(1)
References
154(5)
10 Perspective on Pedestrian Inertial Navigation Systems
159(4)
10.1 Hardware Development
159(2)
10.2 Software Development
161(1)
10.3 Conclusions
161(1)
References
162(1)
Index 163
YUSHENG WANG, PhD, received the B.Eng. degree (Hons.) in engineering mechanics from Tsinghua University, Beijing, China, in 2014 and the Ph.D. degree in mechanical and aerospace engineering from the University of California, Irvine, CA, in 2020. His research interests include the development of silicon-based and fused quartz-based MEMS resonators and gyroscopes, and pedestrian inertial navigation development with sensor fusion. He is currently working at SiTime Corporation as an MEMS Development Engineer.

ANDREI M. SHKEL, PhD, has been on faculty at the University of California, Irvine since 2000, and served as a Program Manager in the Microsystems Technology Office of DARPA. His research interests are reflected in over 300 publications, 42 patents, and 3 books. Dr. Shkel has been on a number of editorial boards, including Editor of IEEE/ASME JMEMS, Journal of Gyroscopy and Navigation, and the founding chair of the IEEE Inertial Sensors. He was awarded the Office of the Secretary of Defense Medal for Exceptional Public Service in 2013, and the 2009 IEEE Sensors Council Technical Achievement Award. He is the President of the IEEE Sensors Council and the IEEE Fellow.
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