APPLICATION OF AIRBORNE LASER SCANNER

134 Pages·2006·4.39 MB·English

by  Jacob Campbell

APPLICATION OF AIRBORNE LASER SCANNER - AERIAL NAVIGATION

A dissertation presented to
the faculty of
the Russ College of Engineering and Technology of Ohio University

In partial fulfillment
of the requirements for the degree
Doctor of Philosophy

Jacob L. Campbell
June 2006
This dissertation entitled
APPLICATION OF AIRBORNE LASER SCANNER- AERIAL NAVIGATION

by
JACOB L. CAMPBELL

has been approved for
the School of Electrical Engineering and Computer Science
and the Russ College of Engineering and Technology by

Maarten Uijt de Haag
Associate Professor of Electrical Engineering and Computer Science

Frank van Graas
Fritz J. and Dolores H. Russ Professor of Electrical Engineering

Dennis Irwin
Dean, College of Engineering
Abstract
CAMPBELL, JACOB L., Ph.D., June 2006. Electrical Engineering
APPLICATION OF AIRBORNE LASER SCANNER- AERIAL NAVIGATION (134 pp.)
Directors of Dissertation: Maarten Uijt de Haag and Frank van Graas

This dissertation explores the use of an Airborne Laser Scanner (ALS) for use in aircraft Terrain-
Referenced Navigation (TRN). Position estimation techniques developed in this dissertation
enable the use of large sets of high accuracy ALS measurements to solve for position in real-time.
The explored techniques were then used to design, implement, and - for the first time ever - fly a
real-time ALS-based TERRain Aided Inertial Navigator (TERRAIN) precision approach system.
During the flight tests, the system provided meter-level horizontal and vertical positioning
accuracies in real-time.

The ALS-based TRN techniques discussed in the dissertation are constrained to the information
found in the terrain shape domain. The data acquisition, pre-processing, and position estimation
techniques of ALS TRN vary significantly from traditional radar altimeter-based TRN primarily
due to differences in the measurement mechanism used in both TRN systems. First, traditional
radar altimeter-based TRN senses the terrain contours traversed in the along-track direction,
whereas ALS-based TRN makes measurements in the along-track and in the cross-track
directions. The second difference is that the ALS laser’s milli-radian beamwidth has sufficient
resolution to identify not only the ground, but also objects on the ground such as buildings. A
radar altimeter with a beamwidth of several degrees can not observe the same level of detail.
These differences increase the spectral content of the ground measurement data in the ALS-based
system thus permitting high-accuracy position estimates.

The described ALS TRN navigation techniques include methods to estimate the position based on
the best match between ALS data and a high resolution/accuracy terrain database. Finally, the
dissertation explores the certification path for an ALS-based landing system.

Approved by:
Maarten Uijt de Haag
Associate Professor of Electrical Engineering and Computer Science

Frank van Graas
Fritz J. and Dolores H. Russ Professor of Electrical Engineering
To my parents -
for their examples of integrity and a positive outlook.
Acknowledgements
This dissertation would not have been possible without the help of many fellow co-
workers/students (which I prefer to call friends given all the good times we have had together
performing this research). I can honestly say that the experiences I have been part of and the
people I have met in the course of this research will be close to me for the rest of my life.

First, I thank my fellow office mates, Jeff Dickman, Lukas Marti, Andrey Soloviev, and Ananth
Vadlamani, for providing an excellent source of ideas during the countless discussions on the
research. I also thank them for helping with the development of equipment and flight tests. For
research support from NASA Langley I thank Steve Young, Rob Kudlinski, and Dan Baize who
made the LIDAR data collection effort in Reno, NV possible. For the Reno, NV DC-8 flight test
I thank the US Army for use of their LIDAR equipment, as well as the support staff from Optech
for their expertise on the installation and help in the LIDAR data processing. I also thank the
NASA DC-8 flying laboratory crew and support staff for their flexibility and help collecting the
data and NOAA for the use of a LIDAR generated terrain map of the Reno area. With respect to
the successful creation and testing of a proof-of-concept real-time laser scanner based approach
system I thank Dr. van Graas and Dr. Uijt de Haag for help with the development and funding. I
thank Jay Clark and his team at the Ohio University Airport for the customized installation of the
equipment in the DC-3 aircraft, and thank the DC-3 pilots, Dr. McFarland and Bryan Branham,
for their part in the successful flight tests at Braxton County Airport (K48I). I thank Delft
University of Technology for the use of their Synthetic Vision / Flight Director display, and I
thank the Canaan Valley Institute, specifically Sandra Frank, for providing the LIDAR data for
K48I. I also thank my Dad, Steve Campbell, for help with the survey of K48I.

I thank my Ph.D. committee members, Dr. Chris Bartone, Dr. Martin Molenkamp, and Dr. Jim
Rankin, for their ideas and guidance from the topic proposal through their reviewing of this
dissertation. And, I thank Dr. Mikel Miller for his support in editing my dissertation. Also, and
most importantly, I thank my Co-Advisors, Dr. Maarten Uijt de Haag and Dr. Frank van Graas
for the countless hours spent discussing the research in this dissertation, reviewing papers, and for
their examples not only as great advisors, but also as great people.

Finally I thank my wife, Nikki, for her support and love throughout my work on this dissertation,

and most importantly I thank God for giving me the strength to complete my Ph.D.
6
Table of Contents

Abstract............................................................................................................................................3
Acknowledgements..........................................................................................................................5
Acronyms / Abbreviations.............................................................................................................11
1. Introduction............................................................................................................................15
2. Background............................................................................................................................18
2.1. Terrain-Referenced Navigation History.......................................................................19
2.1.1. The Early Years, Analog Systems............................................................................19
2.1.2. Digital Age of Terrain Navigation...........................................................................21
2.1.3. Bayesian Approaches to Terrain-Referenced Navigation Research........................23
2.1.4. Beyond ‘Traditional’ Radar Altimeter Terrain-Referenced Navigation..................23
2.2. Survey of Terrain-Based Navigation Systems..............................................................26
2.2.1. ATRAN – Automatic Terrain Recognition And Navigation...................................26
2.2.2. TERCOM – TERrain COntour Matching................................................................27
2.2.3. SITAN – Sandia Inertial Terrain-Aided Navigation................................................29
2.2.4. SPARTAN – StockPot Algorithm Robust Terrain-Aided Navigation.....................30
2.2.5. TERPROM® – TERrain PROfile Matching.............................................................31
2.2.6. APALS® - Autonomous Precision Approach and Landing System.........................32
2.2.7. PTAN® - Precision Terrain Aided Navigation.........................................................33
2.3. Summary of Survey of Terrain-Based Navigation Systems.........................................34
2.4. System Characteristics: GPS, WAAS, INS, GPS-Aided INS, Coasting INS...............35
2.4.1. GPS..........................................................................................................................35
2.4.2. WAAS......................................................................................................................36
2.4.3. Inertial Navigation...................................................................................................36
2.4.4. GPS-Aided Inertial Calibration................................................................................37
3. Airborne Laser Scanner & LIght Detection And Ranging (LIDAR) Mapping Systems.......41
3.1. ALS Characteristics and Operation..............................................................................41
3.1.1. ALS Laser Rangers..................................................................................................41
3.1.2. ALS Scanning Mechanisms.....................................................................................43
3.1.3. ALS Pointing Accuracy Characteristics...................................................................47
3.2. ALS in a LIDAR Mapping System..............................................................................49
3.2.1. Laser Scanner Sensor Errors....................................................................................49
3.2.2. Kinematic GPS Sensor Errors..................................................................................50
3.2.3. GPS/IMU Orientation Sensor Errors........................................................................51
3.2.4. Total LIDAR Mapping System Vertical & Horizontal System Errors....................51
3.3. LIDAR Generated DSM...............................................................................................52
3.3.1. Reno, NV LIDAR Data............................................................................................55
3.3.2. Braxton County Data................................................................................................56
3.4. Laser Safety..................................................................................................................57
4. Airborne Laser Scanner-Based Terrain-Referenced Position Estimation..............................59
4.1. Vertical-Based Agreement Metric................................................................................60
4.1.1. Radar Altimeter-Based Disparity Calculation..........................................................61
4.1.2. ALS-Based Disparity Calculation............................................................................63
4.2. ALS-Based Position Estimation...................................................................................64
4.2.1. Exhaustive Grid Search Position Estimation...........................................................65
4.2.2. Gradient-Based Search Position Estimation............................................................67
7
4.3. ALS Positioning over Reno, NV..................................................................................71
4.3.1. Initial Positioning Results........................................................................................73
5. Real-Time TERRAIN Approach System...............................................................................77
5.1. Characteristics of the TERRAIN Approach System....................................................79
5.1.1. TERRAIN Approach System Integrity....................................................................80
5.1.2. TERRAIN Approach System Availability...............................................................81
5.1.3. TERRAIN Approach System Continuity.................................................................83
5.2. Terrain-Referenced Position Solutions.........................................................................84
5.3. Inertial Velocity Error Estimation using Integrated GPS Carrier Phase......................86
5.4. Proof-of-Concept Real-Time TERRAIN Approach System Hardware Description....88
5.4.1. NovAtel OEM 4/WAAS GPS Receiver...................................................................88
5.4.2. Honeywell HG1150 Navigation Grade IRU............................................................89
5.4.3. Riegl LMS-Q140i Airborne Laser Scanner.............................................................90
5.4.4. Data Collection/Distribution Computer...................................................................91
5.4.5. Navigation Computer...............................................................................................92
5.4.6. Display Computer....................................................................................................93
5.5. Flight Test Location and Test Plan...............................................................................94
5.6. TERRAIN Precision Approach System Performance..................................................96
6. Conclusions and Future Work.............................................................................................101
7. References............................................................................................................................104
Appendix A. Reno, Nevada LIDAR Data Metadata....................................................................113
Appendix B. Glimer County LIDAR Data Metadata..................................................................130
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List of Tables

Table 1, Summary of ALS position estimates (1-s updates)..........................................................76
Table 2, Summary of TERRAIN position accuracy on approach, 900 ft HAT to DH, eight
approaches, nine minutes of data......................................................................................99
Table 3, Summary of TERRAIN position accuracy at 50 ft DH, eight approaches......................99
9
List of Figures

Figure 1-1, Scan pattern of a downward-looking ALS terrain-referenced system........................16
Figure 2-1, British H2S air-to-surface radar, image used with permission from
http://www.doramusic.com/Radar.htm, May 2005....................................................20
Figure 2-2, A. H2S scan pattern, image used with permission from
http://www.doramusic.com/Radar.htm, May 2005....................................................20
Figure 2-3, Example of a Lissajous Laser Scan Pattern, X angle frequency = 6 Hz, Y
angle frequency = 7 Hz, PRF = 1500 pulse/s.............................................................25
Figure 2-4, TERCOM System, figure adapted from [35]..............................................................28
Figure 2-5, SITAN System, figure adapted from [35]...................................................................30
Figure 2-6, Feed-forward navigator design used in the implementation of the prototype
real-time TERRAIN approach system described in Chapter 5...................................39
Figure 2-7, Kalman filter mechanization, figure adapted from [71] pp 219.................................40
Figure 3-1, Scan pattern of an oscillating mirror airborne laser scanner.......................................44
Figure 3-2, Scan pattern of a rotating mirror airborne laser scanner.............................................45
Figure 3-3, Scan pattern of a nutating mirror airborne laser scanner.............................................46
Figure 3-4, Scan pattern of a nutating mirror / fiber steered airborne laser scanner......................47
Figure 3-5, Perspective view of Reno, NV, LIDAR data; LIDAR data height mapped to
point color, LIDAR data intensity mapped to point brightness. Image created
in QT Viewer™ software...........................................................................................53
Figure 3-6, Range plot generated by laser scanner of the inside of Ohio University AEC’s
hanger, color index: dark blue < 3 m, and dark red > 25 m. (Note: dark blue
on wings and nose indicates all laser energy absorbed, no range measurement
available)....................................................................................................................54
Figure 3-7, Intensity plot generated from laser scanner of the inside of Ohio University
AEC’s hanger, color axis: dark red = high intensity return, dark blue = low
intensity return............................................................................................................54
Figure 3-8, Perspective view of Reno, NV, LIDAR data; LIDAR data height mapped to
point color, LIDAR data intensity mapped to point brightness. Image created
in QT Viewer™ software...........................................................................................56
Figure 4-1, Parameters of a radar altimeter-based terrain navigator..............................................62
Figure 4-2, Parameters of an ALS-based terrain navigator............................................................63
Figure 4-3, SSE surface : GPS time 314246 s of week 1229 : 30x30 m search area, 1-m
spacing. Dark Blue: best DSM-ALS data agreement. Dark Red: least DSM-
ALS data agreement...................................................................................................66
Figure 4-4, SSE surface : GPS time 314246 s of week 1229 : 9x9 m search area, 0.3-m
spacing. Dark Blue: best DSM-ALS data agreement. Dark Red: least DSM-
ALS data agreement...................................................................................................66
Figure 4-5, Gradient search for minimum error on the sum of squared error surface (axis
in meters). Dark Blue: best DSM-ALS data agreement. Dark Red: least
DSM-ALS data agreement.........................................................................................70
Figure 4-6, NASA Dryden DC-8 Flying Laboratory, photo courtesy of NASA Dryden..............72
Figure 4-7, NASA Dryden DC-8 cargo bay LIDAR installation...................................................72
Figure 4-8, Flight path of an approach into KRNO.......................................................................73
Figure 4-9, Flight trajectories during laser data collection at KRNO............................................74
Figure 4-10, ALS horizontal position estimate error.....................................................................75
10
Figure 5-1, TERRAIN precision approach system position estimator..........................................78
Figure 5-2, Approach into St. Maarten Island. Approach over water would make the
TERRAIN approach system not available with a standard ALS system.
Source of photo: www.airliners.net............................................................................80
Figure 5-3, Theoretical probability density curve of a weather condition of severity x
occurring, the area of the shaded region represents probability of a landing
guidance system not available....................................................................................82
Figure 5-4, TERRAIN precision approach hardware diagram......................................................89
Figure 5-5, Honeywell HG1150 IRU installed aft of right-seat pilot in the DC-3........................90
Figure 5-6, Scanning parameters for LMS-Q140i ,average PRF = 10 kHz, scan angle = 60
deg..............................................................................................................................91
Figure 5-7, DC-3 research computer rack......................................................................................93
Figure 5-8, DC-3 cockpit with DELPHINS guidance display.......................................................94
Figure 5-9, DC-3 on short final to runway 19, K48I....................................................................95
Figure 5-10, Trajectories flown to K48I on January 14, 2005 during the flight testing of
the real-time TERRAIN approach system, Left- perspective view (approach
direction left to right), Right- plan view with North up (approach direction
from top to bottom)....................................................................................................95
Figure 5-11, TERRAIN position – KGPS for one approach, HAT: Height Above
Threshold....................................................................................................................96
Figure 5-12, Histogram of error in the TERRAIN approach system navigator output in
the East direction with best fit normal distribution overlay.......................................98
Figure 5-13, Histogram of error in the TERRAIN approach system navigator output in
the North direction with best fit normal distribution overlay.....................................98
Figure 5-14, Histogram of error in the TERRAIN approach system navigator output in
the Up direction with best fit normal distribution overlay.........................................99
Figure 6-1, Flight crew of the January 14, 2004 proof-of-concept TERRAIN flight test,
Left to right: Dave Barner, Mark’s Lunch (the bag), Mark Smearcheck,
Ananth Vadlamani, Jeff Dickman, Don Venable, Bryan Branham (Co-Pilot),
Dr. Richard McFarland (Pilot), Jacob Campbell. Not pictured but present on
the flight: Dr. Maarten Uijt de Haag. Also not pictured but essential to the
flight test: Dr. Frank van Graas, Jay Clark (Chief of Airborne Mobile
Laboratories), Kadi, Mac & Paul. Thanks guys!.....................................................103