APPLICATION OF AIRBORNE LASER SCANNER - AERIAL NAVIGATION A dissertation presented ...

124 Pages·2006·4.12 MB·English

by  Jacob Campbell

APPLICATION OF AIRBORNE LASER SCANNER - AERIAL NAVIGATION

A dissertation presented to
the faculty of
the School of Electrical Engineering and Computer Science
and the Russ College of Engineering and Technology

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

Jacob L. Campbell
February 24, 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
Russ Professor of Electrical Engineering and Computer Science

Dennis Irwin
Dean, Russ College of Engineering and Technology
CAMPBELL, JACOB L. Ph.D. February 24, 2006. Electrical Engineering and Computer Science
Application of Airborne Laser Scanner- Aerial Navigation (### pp.)
Directors of Dissertation: Maarten Uijt de Haag, Frank van Graas

This dissertation explores the use of an Airborne Laser Scanner (ALS) for various types of
aircraft Terrain-Referenced Navigation (TRN) techniques. Using the methods explored, an ALS-
based TERRain Aided Inertial Navigator (TERRAIN) was developed, flight tested, and shown
capable of providing meter-level positioning accuracy in real-time.

The ALS-based TRN techniques discussed are constrained to the information found in the terrain
shape domain. The techniques used and position solution characteristics of ALS TRN can vary
significantly from traditional radar altimeter-based TRN; these variations are primarily due to two
differences in the information contained ALS TRN verses traditional radar altimeter-based TRN.
The first difference being that traditional radar altimeter-based TRN sense the terrain contours
traversed in the along-track direction, whereas ALS TRN measures in the along-track and in the
cross-track direction. The second difference is that the ALS’s narrow laser beamwidth (typically
less than a milli-radian) has resolution sufficient to identify not only the ground, but objects on
the ground such as buildings; whereas, a the radar altimeter’s relatively large beamwidth
(anywhere between 3 degrees to 90 degrees) primarily senses the terrain. These differences
increase the spectral content of the ground measurement data in the ALS-based system thus
permitting high-accuracy position estimates.

The ALS TRN navigation techniques explored include a method which estimates the position
based on the best match between ALS data and a high resolution/accuracy terrain database.
Variations on this technique are discussed include a method to classify non-terrain and terrain
features from the ALS data, allowing for the use of features with large gradients (sharp edges),
such as buildings. Also explored is the certification path for a ALS-based landing system.

Approved by:
Maarten Uijt de Haag
Associate Professor of Electrical Engineering and Computer Science
and:
Frank van Graas
Russ Professor of Electrical Engineering and Computer Science
Acronyms.........................................................................................................................................9
Acknowledgements........................................................................................................................13
1. Introduction............................................................................................................................14
2. Background............................................................................................................................17
2.1. Terrain-Referenced Navigation History.......................................................................18
2.1.1. The Early Years, Analog Systems............................................................................18
2.1.2. Digital Age of Terrain Navigation...........................................................................20
2.1.3. Bayesian Approaches to Terrain-Referenced Navigation Research........................22
2.1.4. Beyond ‘Traditional’ Radar Altimeter Terrain-Referenced Navigation..................22
2.2. Survey of Terrain-Based Navigation Systems..............................................................25
2.2.1. ATRAN – Automatic Terrain Recognition And Navigation...................................25
2.2.2. TERCOM – TERrain COntour Matching................................................................26
2.2.3. SITAN – Sandia Inertial Terrain-Aided Navigation................................................28
2.2.4. SPARTAN – StockPot Algorithm Robust Terrain-Aided Navigation.....................29
2.2.5. TERPROM® – TERrain PROfile Matching.............................................................30
2.2.6. APALS® - Autonomous Precision Approach and Landing System.........................31
2.2.7. PTAN® - Precision Terrain Aided Navigation.........................................................31
2.3. Summary of Survey of Terrain-Based Navigation Systems.........................................33
2.4. System Characteristics: GPS, WAAS, INS, GPS-Aided INS, Calibrated-Coasting INS
34
2.4.1. GPS..........................................................................................................................34
2.4.2. WAAS......................................................................................................................35
2.4.3. Inertial Navigation...................................................................................................35
2.4.4. GPS-Aided Inertial Calibration................................................................................36
3. Airborne Laser Scanner & LIght Detection And Ranging (LIDAR) Mapping Systems.......40
3.1. ALS Characteristics and Operation..............................................................................40
3.1.1. ALS Laser Rangers..................................................................................................40
3.1.2. ALS Scanning mechanisms......................................................................................42
3.1.3. ALS Pointing Accuracy Characteristics...................................................................46
3.2. ALS in a LIDAR mapping System...............................................................................47
3.2.1. Laser Scanner Sensor Errors....................................................................................48
3.2.2. Kinematic GPS Sensor Errors..................................................................................49
3.2.3. GPS/IMU Orientation Sensor Errors........................................................................49
3.2.4. Total LIDAR mapping system Vertical & Horizontal System Errors.....................49
3.3. LIDAR Generated DSM...............................................................................................50
3.3.1. Reno, NV LIDAR Data............................................................................................53
3.3.2. Braxton County Data................................................................................................54
3.4. Laser Safety..................................................................................................................54
4. Airborne Laser Scanner-Based Terrain-Referenced Position Estimation..............................56
4.1. Vertical-based Agreement Metric................................................................................57
4.1.1. Radar Altimeter-Based Disparity Calculation..........................................................58
4.1.2. ALS-Based Disparity Calculation............................................................................59
4.2. ALS-Based Position Estimation...................................................................................60
4.2.1. Exhaustive Grid Search Position Estimation...........................................................62
4.2.2. Gradient-Based Search Position Estimation............................................................64
4.3. ALS Positioning over Reno, NV..................................................................................66
4.3.1. Initial Positioning Results........................................................................................69
5. Real-Time TERRAIN Approach System...............................................................................72
5.1. Characteristics of the TERRAIN Approach System....................................................74
5.1.1. TERRAIN Approach System Integrity....................................................................74
5.1.2. TERRAIN Approach System Availability...............................................................76
5.1.3. TERRAIN Approach System Continuity.................................................................78
5.2. Terrain-Referenced Position Solutions.........................................................................78
5.3. Inertial Velocity Error Estimation Using Integrated GPS Carrier Phase......................80
5.4. Proof-of-Concept Real-time TERRAIN Approach System Hardware Description.....82
5.4.1. NovAtel OEM 4/WAAS GPS Receiver...................................................................83
5.4.2. Honeywell HG1150 Navigation Grade Inertial Reference Unit (IRU)....................83
5.4.3. Riegl LMS-Q140i Airborne Laser Scanner.............................................................84
5.4.4. Data Collection/Distribution Computer...................................................................86
5.4.5. Navigation Computer...............................................................................................86
5.4.6. Display Computer....................................................................................................87
5.5. Flight Test Location and Test Plan...............................................................................88
5.6. TERRAIN Precision Approach System Performance..................................................90
6. Conclusions and Future Work...............................................................................................96
7. References..............................................................................................................................99
Appendix A- Reno, Nevada LIDAR Data Metadata...................................................................107
Appendix B.- Glimer County LIDAR Data Metadata.................................................................121

List of Tables
Table 1, Summary of ALS Position Estimates (1-s updates).........................................................70
Table 2, Summary of TERRAIN Position Accuracy on Approach, 900 ft HAT to DH, Eight
Approaches, Nine Minutes of Data................................................................................................94
Table 3, Summary of TERRAIN Position Accuracy at 50 ft DH, Eight Approaches (5323
measurements)...............................................................................................................................94

List of Figures

Figure 2-1, British H2S Air-to-Surface Radar, Image used with permission from
http://www.doramusic.com/Radar.htm, May 2005........................................................................19
Figure 2-2, A. H2S Scan Pattern, Image used with permission from
http://www.doramusic.com/Radar.htm, May 2005........................................................................19
Figure 2-3, Example of a Lissajous Laser Scan Pattern, X angle frequency = 6 Hz, Y angle
frequency = 7 Hz, PRF = 1500 pulse/sec.......................................................................................24
Figure 2-4, TERCOM System, figure adapted from [35]..............................................................27
Figure 2-5, SITAN System, figure adapted from [35]...................................................................28
Figure 2-6, feed-forward navigator design used in the implementation of the prototype real-time
TERRAIN approach system described in Chapter 5.....................................................................38
Figure 2-7, Kalman filter mechanization, figure adapted from [71] pp 219.................................39
Figure 3-1, Scan Pattern of an Oscillating Mirror Airborne Laser Scanner..................................43
Figure 3-2, Scan Pattern of a Rotating Mirror Airborne Laser Scanner........................................44
Figure 3-3, Scan Pattern of a Nutating Mirror Airborne Laser Scanner........................................45
Figure 3-4, Scan Pattern of a Nutating Mirror / Fiber Steered Airborne Laser Scanner...............45
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..........................................................................................................................................51
Figure 3-6, Range Plot Generated by Laser Scanner of the Inside of Ohio University AEC’s
Hanger, Color Index: Blue < 3 m, and Red > 25 m. (Note: Dark blue on wings and nose
indicates all laser energy absorbed, no range measurement available)..........................................52
Figure 3-7, Intensity Plot Generated from Laser Scanner of the Inside of Ohio University AEC’s
Hanger, Color Axis: Red = High Intensity Return, Blue = Low Intensity Return.........................53
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..........................................................................................................................................54
Figure 4-1, Parameters of a Radar Altimeter-Based Terrain Navigator........................................59
Figure 4-2, Parameters of an ALS-Based Terrain Navigator.........................................................60
Figure 4-3, SSE Surface for GPS time 314246 s of week 1229....................................................62
Figure 4-4, SSE Surface for GPS time 314246 s of week 1229....................................................63
Figure 4-5, Gradient Search for Minimum Error on the Sum of Squared Error Surface...............66
Figure 4-6, NASA Dryden DC-8 Flying Laboratory, Photo courtesy of NASA Dryden..............67
Figure 4-7, NASA Dryden DC-8 Cargo Bay LIDAR Installation.................................................68
Figure 4-8, Flight Path of an Approach into KRNO......................................................................68
Figure 4-9, Flight Trajectories during Laser Data Collection at KRNO........................................69
Figure 4-10, ALS Horizontal Position Estimate Error...................................................................70
Figure 5-1, TERRAIN Precision Approach System Position Estimator........................................73
Figure 5-2, Approach into St. Maarten Island. Approach over water would make the TERRAIN
approach system not available.......................................................................................................75
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.77
Figure 5-4, TERRAIN Precision Approach Hardware Diagram...................................................83
Figure 5-5, Honeywell HG1150 IRU installed just aft of right-seat pilot in the DC-3..................84
Figure 5-6, Scanning Parameters for LMS-Q140i with Average PRF = 10 kHz...........................85
Figure 5-7, DC-3Research Computer Rack...................................................................................87
Figure 5-8, DC-3 Cockpit with DELPHINS Guidance Display....................................................88
Figure 5-9, DC-3 on Short Final to Runway 19, K48I.................................................................89
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, Right- plan view with North up.......90
Figure 5-11, TERRAIN position – KGPS for one approach, HAT: Height Above Threshold.....91
Figure 5-12, Histogram of error in the TERRAIN approach system navigator output in the East
direction with best fit normal distribution overlay.........................................................................92
Figure 5-13, Histogram of error in the TERRAIN approach system navigator output in the North
direction with best fit normal distribution overlay.........................................................................93
Figure 5-14, Histogram of error in the TERRAIN approach system navigator output in the Up
direction with best fit normal distribution overlay.........................................................................93
Acronyms
AEC – Avionics Engineering Center (at Ohio University)
AFTI – Advanced Fighter Technology Integration
AGL – Above Ground Level
ALS – Airborne Laser Scanner
ALTM – Airborne Laser Terrain Mapper (Optech System)
APALS – Autonomous Precision Approach and Landing System
APD – Avalanche Photodiode
ATRAN – Automatic Terrain Recognition And Navigation
AWRS – Average Weighted Residual Squared
CAROTE – Correlation And Recognition Of Terrain Elevation
CEP – Circular Error Probability
CVN – Continuous Visual Navigation
DCD – Data Collection and Distribution computer
DCT – Discrete Cosine Transform
DURIP – Defense University Research Instrumentation Program
DME – Distance Measurement Equipment
DME-P – Precision Distance Measurement Equipment
DOP – Dilution Of Precision
DSM – Digital Surface Map
DSMAC – Digital Scene-Mapping Area Correlator
DTED – Digital Terrain Elevation Database
DTM – Digital Terrain Map
EGPWS – Enhanced Ground Proximity Warning System
ENU – East North Up
FAA – Federal Aviation Administration
FLOD – Forward Looking Obstacle Detection
FM-CW – Frequency Modulated Carrier Wave
GCAS – Ground Collision Avoidance System
GIS – Geographical Information System
GPS – Global Positioning System
HAT – Height Above Threshold
HDD – Heads Down Display
IAF – Initial Approach Fix
ILS – Instrument Landing System
IMU – Inertial Measurement Unit
INS – Inertial Navigation System
IRS – Inertial Reference System
IRU – Inertial Reference Unit
K48I – Braxton County Airport in West Virginia
KGPS – Kinematic Global Positioning System
KRNO – Reno, NV Airport
KUNI – Ohio University Airport in Albany Ohio
LAAS – Local Area Augmentation System
LADAR – LAser Detection And Ranging – or – Laser Radar
LaRC – NASA Langley Research Center
LCD – Liquid Crystal Display
LEP – Linear Error Probability
LIDAR – LIght Detection And Ranging
LLH – Latitude, Longitude, Height
LOS – Line Of Sight
LSO – Laser Scanner Origin
MAD – Mean Absolute Difference
MCMC – Monte Carlo Markov Chain
MSD – Mean Squared Difference
MSL – Mean Sea Level
MWx – Modified X-band Weather Radar
MLS – Microwave Landing System
NAV – NAVigation computer
NGS – National Geodetic Survey
POS – Position and Orientation System
PPI – Plan Position Indicator
PPS – Pulse Per Second
PRF – Pulse Repetition Frequency
PTAN – Precision Terrain Aided Navigation
RAM – Random Access Memory
RLG – Ring Laser Gyro