DayStar
Diurnal Star Tracking for Balloon-borne Attitude Determination
Preliminary Design Review
October 12, 2011
University of Colorado
Aerospace Engineering Sciences
Jed Diller
Aaron Holt
Michael Skeen
Kevin Dinkel
Tyler Murphy
Nick Truesdale
Zach Dischner
Sara Schuette
Andrew Zizzi
Briefing Overview and Content
Purpose: The Preliminary Design Review will introduce the DayStar system
options and demonstrate the feasibility of the chosen design solutions.
Objectives Overview
Background, Project Goals and Requirements, and Concept of Operations
Michael Skeen
Development and Assessment of System Design Options
System Architecture Options, Trade Studies, and Selected Design
Nick Truesdale
System Design-To Specifications
System Requirements and Verification, Supporting System Modeling
Nick Truesdale
Development and Assessment of Subsystem Design Options
Subsystem Modeling and Preliminary Design
Andrew Zizzi, Jed Diller, Sara Schuette
Project Feasibility Analysis and Risk Assessment
Project Feasibility Justifications and Risk Assessment and Mitigation
Andrew Zizzi, Jed Diller, Sara Schuette
Project Management Plan, including personal Health and Safety
Organization, Schedule, Budget, Work Breakdown Structure, and Health and Safety Plan
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Michael Skeen
Project
Management
Plan
10/12/2011
2
Objectives Overview
Michael Skeen
10/12/2011
3
Background
[1]
• Balloon-Borne Observatories:
– Eventual goal: Operate 1-meter telescope
from a balloon platform with Hubble
Space Telescope performance
– Sunrise: Sun-imaging 1-meter UV
telescope, 0.05 arcsecond angular
resolution[1]
• Attitude Determination:
– ST5000 (University of Wisconsin)[2]
commonly used on sounding rocket
[2]
• 0.5 arcsecond RMS accuracy
• Saturated 20 minutes before sunrise on highaltitude balloon flight
– Needed:
• Increased accuracy
• Operation in daytime conditions
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
4
Project Goals and Requirements
• The DayStar team will develop a prototype star tracking system
capable of providing pointing knowledge to a diurnal, lighter-than-air
platform. DayStar will improve on current attitude determination
devices used on balloon payloads by providing daytime operational
capabilities and an improved nighttime accuracy of 0.1 arcseconds
RMS.
Requirement
Description
0.PRJ.1
DayStar shall provide better than or equal to 0.1 arcsecond 1-σ RMS
pointing knowledge during nighttime observation.
0.PRJ.2
DayStar shall provide better than or equal to 1 arcsecond 1-σ RMS pointing
knowledge during daytime observation (goal of 0.1 arcseconds).
0.PRJ.3
DayStar shall produce data compatible with ST5000 attitude determination
software.
0.PRJ.4
DayStar shall demonstrate adaptability to a high-altitude balloon
environment.
Nighttime: Ambient sky brightness ≤ 2 kilo-Rayleighs
Daytime: Ambient sky brightness ≤ 86,000 kilo-Rayleighs
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
5
Flight Concept of Operations
Launch
Start-Up
Star Tracking Operations
Capture Image
Determine Star Centroid Locations
Compute and Output Attitude
Shutdown
Touch-Down
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
6
Development and Assessment
of System Design Options
Nick Truesdale
10/12/2011
7
System Architecture
System architecture is defined by customer to be a star tracker.
Optics
Imaging
CDH
• Task: Focus starfield
onto CMOS sensor.
• Task: Provide images for
processing.
• Task: Convert images to
attitude solution.
• Key Components:
• Key Components:
• Key Components:
 5x7 degree FOV
 Internal field stop and
external baffle
 Red Filter
 5.5 megapixels
 Improved red performance
 Ultra-low read noise
 Star detection/rejection
 Star Centroiding
• Stretch Goals:
 Star identification
Attitude Solution
Structures
• Task: Provide structural support and integration of functional subsystems.
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
8
Trade Space Diagram (TSD)
Star Tracker
Centroiding
Optics
Imaging
CDH
Telescope
Camera
Star Detection
Refractor
CCD
Average Plus STD
Reflector
CMOS
Median Absolute
Deviation (MAD)
Catadioptric
CCD Array
Robust MAD
(roboMAD)
Parabolic Fit
Static Flight
Configurable
Gaussian Fit
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Center of Gravity
(CoG)
Robust CoG
(roboCoG)
Intensity Weighted
Centroiding (IWC)
Robust IWC
(roboIWC)
Project
Management
Plan
10/12/2011
9
Functional Block Diagram (FBD)
Structure
Optics
Reimaging
System
Filter
Imaging
FPGA
Briefing Overview
Objectives
Overview
Objective
Lens
System
Design
Options
External
Baffle
Power
Management
MicroController
Flash Memory
CMOS Sensor
Field
Stop
Interfaces
CDH
Key
Memory
Power
Processor
Data
Storage
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Light
Project
Management
Plan
10/12/2011
10
System Design-To
Specifications
Nick Truesdale
10/12/2011
11
Accuracy Requirements
• Project requirements:
Requirement
Description
Parent Req. Verification
0.PRJ.1
DayStar shall provide better than or equal to 0.1 arcsecond 1-σ RMS
pointing knowledge during nighttime observation.
Customer
Test
0.PRJ.2
DayStar shall provide better than or equal to 1 arcsecond 1-σ RMS pointing
knowledge during daytime observation (goal of 0.1 arcseconds).
Customer
Test
Parent Req.
Verification
• System requirements:
Requirement
Description
1.SYS.1
The DayStar system shall be able to image the sky.
0.PRJ.1,
0.PRJ.2
Test
1.SYS.2
The DayStar system shall image a minimum of 20 stars per frame having a
SNR of at least 6.0 at nighttime.
0.PRJ.1
Test,
Analysis
1.SYS.3
The DayStar system shall image a minimum of 8 stars per frame having a
SNR of at least 6.0 at daytime.
0.PRJ.2
Test,
Analysis
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
12
Accuracy Modeling
• Key values:
– Minimum number of stars per frame
• 8 at daytime, 20 at nighttime
• Required by CDH statistical accuracy test
– Minimum signal to noise ratio
• 6.0 for daytime and nighttime
• Required by CDH identification and centroiding
accuracy tests
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
13
Accuracy Modeling
Number of stars in field of view by magnitude
• How many stars
do we see?
70
Nighttime
Daytime
Ideal
60
– Nighttime
Number of stars
50
• ~78 stars
40
– Daytime
30
• ~18 stars
• Both satisfy
requirements
20
10
0
4
4.5
5
5.5
6
Magnitude
6.5
7
7.5
8
Data from [3], [4]
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
14
Interface Requirements
• Project requirements:
Requirement
Description
Parent Req.
Verification
0.PRJ.3
DayStar shall produce data that is compatible with ST5000[5] attitude
determination software.
Customer
Test, Analysis
0.PRJ.4
DayStar shall demonstrate adaptability to a high-altitude balloon
environment.
Customer
Test, Analysis
• System requirements:
Requirement
Description
Parent Req.
Verification
1.SYS.5
The DayStar system shall adhere to the HASP ICD for the mass, power
and data resources allocated to two large class payloads.
0.PRJ.4
Test,
Inspection
1.SYS.6
The DayStar system shall output attitude information at a frequency
of 10 Hz with the required accuracy.
0.PRJ.3
Test
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
15
Interface Analysis
• Key Values:
– ICD Specifications
• 40kg, 150W at 30V, and 9600 baud downlink
• Easily met
– Telescope mass < 10 kg
– Computer power < 80W
– Minimum data output rate
• 10 Hz is the ST5000 operating speed
• Encompasses frame rate, image transfer and processing
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
16
Development and Assessment
of Subsystem Design Options
Andrew Zizzi
Jed Diller
Sara Schuette
10/12/2011
17
Algorithms – Design-To Specs
Subsystem Requirements:
Requirement
Description
Parent Requirement
Method
Verification
2.CDH.1
The CDH system shall be able to detect
stars in the image.
1.SYS.2
1.SYS.3
Analysis, Test
2.CDH.2
The CDH system shall produce star
centroids to a 1” RMS accuracy during
nighttime.
1.SYS.2
Analysis, Test
2.CDH.3
The CDH system shall produce star
centroids to a 5” RMS accuracy during
daytime.
1.SYS.3
Analysis, Test
Verification of Requirements:
“At a given
SNR, how well
do we know
our attitude?”
Briefing Overview
Objectives
Overview
=
“How well do
we know our
attitude from
our centroids?”
System
Design
Options
Design-To
Specifications
×
“How well can
we locate what
we detect?”
Subsystem
Design
Options
Feasibility
and Risk
Assessment
×
“What SNR
stars can we
detect?”
Project
Management
Plan
10/12/2011
18
Algorithms – Software Flow
Minimum requirements for success
Image
Star
Detection
Centroid
Stars
Output
Centroid
Vectors
Star
Catalog
Search
Output
Inertial
Coordinates
Stretch goals / ST5000 interface
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
19
Algorithms – Trade Study Results
Algorithm:
Methods:
Evaluation Criteria:
Star Detection
Ave + STD[5], MAD[6], roboMAD[6], Static
Flight Configurable
Robustness at low SNR, Speed,
Complexity, False Identifications
Star Centroiding
CoG, IWC[7][8], Gaussian Fit[6], Parabolic
Fit[6], roboCoG[6], roboIWC
Accuracy, Speed, Complexity,
Robustness against noise
Lost-in-Space
Differential Voting[9], Planar Triangle[10],
Pyramid Angle[8], FOCAS Triangles[11],
Grid Method[12]
Performance with low star count,
Speed, Complexity, Memory,
Convergence Probability
Attitude
Determination
Q-Method[13], Triad Method[13],
QUEST[13], Newton-Rhapson Method[13]
Accuracy, Speed, Complexity
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
20
Algorithms – Star Detection
Percent of 7th Magnitude Stars Detected During the Day
100
90
90
Overexposed Region
80
Exposure Time [ms]
Method:
100
70
70
60
60
Target
Region
50
40
Briefing Overview
Objectives
Overview
System
Design
Options
50
40
30
30
20
20
Underexposed Region
10
Results:
1. 7th magnitude stars are detected 90% of
the time with an exposure between ~30
and ~70 ms blurred over 16 to 36 pixels
80
10
Design-To
Specifications
20
30
70
60
50
40
Blur [pixels subtended]
Subsystem
Design
Options
Feasibility
and Risk
Assessment
80
90
Project
Management
Plan
Percent of Stars Detected
Purpose:
1. Test algorithm’s ability to define the star
detection intensity limit
2. Define min/max blurring factor and
min/max exposure time for best star
detection performance
10
100
0
10/12/2011
21
Algorithms – Centroid Accuracy
Purpose:
1. Choose the most suitable centroiding
method
2. Define min/max blurring factor and
min/max exposure times for best
centroiding performance
Method:
Centroid Errors for Various Methods vs. Blur (67 ms Exposure)
4
CoG
IWC
Gaussian Fit
Parabolic Fit
roboCoG
roboIWC
Intensity (raw counts)
Generated Star Subtended Over 25 pixels, SNR of 7
Centroid RMS Error [arcseconds]
3.5
3
7th Magnitude Star
During the Day
2.5
2
Target
Region
1.5
1
0.5
0
0
10
20
30
40
50
60
70
Blur [pixels subtended]
80
90
100
Results:
1. Robust IWC method chosen
2. Star needs to be subtended over 16 – 36
pixels to achieve < 0.5” RMS accuracy
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
22
Algorithms – Attitude Accuracy
Actual Star
Vectors
10,000
Monte Carlo
trials
Perturbed Star
Vectors
ST5000 Attitude
Transformation
Algorithm[14]
Objectives
Overview
0.10"
0.50"
0.70"
0.90"
1.10"
1.30"
0.9
0.8
0.7
0.6
RMS
RMS
RMS
RMS
RMS
RMS
0.5
0.4
0.3
0.1”
Requirement
0.2
0.1
LSF Attitude
Results:
 0.1” RMS attitude accuracy is attainable at
various centroiding accuracies:
1. 6 stars at 0.5” RMS accuracy
2. 15 stars at 0.9” RMS accuracy
3. 25 stars at 1.1” RMS accuracy
Briefing Overview
Number of Stars vs. RMS Attitude Accuracy for Various Centroid Accuracies
RMS Attitude Error (arcseconds)
Purpose:
 Define how centroiding accuracy
influences attitude accuracy
 Define how number of stars in FOV
changes attitude accuracy
Method:
System
Design
Options
0
5
Design-To
Specifications
Subsystem
Design
Options
10
15
20
Number of Stars
Feasibility
and Risk
Assessment
25
Project
Management
Plan
30
35
10/12/2011
23
Algorithms – Hardware Solutions
Requirements:
1. Minimum Data Transfer Rate From sCMOS: 664 bits/s
2. Maximum CPU Power Dissipation: ~40 W
3. Minimum Data Storage: ~10 GB
4. Minimum Onboard Memory: ~6 GB
5. Maximum Price: $1,840.0
Consumer Grade Desktop Hardware
• Pros: Simplicity, Computation Speed, Memory, Price
• Cons: Power Draw, sCMOS Interface Options
Low Power Desktop Hardware
• Pros: Simplicity, Power Draw, Price
• Cons: sCMOS Interface Options, Computation Speed, Memory
Embedded Computer Hardware (PC/104 or AVR)
• Pros: Power Draw, sCMOS Interface Options, Rugged
• Cons: Complexity, Price, Computation Speed, Memory
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
24
Imaging Subsystem
star light
sensor
algorithms computer
electronics
1001101
digital output
voltage
imaging subsystem
•
•
•
•
Light to voltage to digital output
Will not saturate during daytime (unlike ST5000)
Sense enough stars for algorithms
Light to digital output at 10Hz
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
25
Imaging Requirements
Requirement
Description
Parent Requirement
Method Verification
2.IMG.1
The imaging system shall detect 4th-8th magnitude
stars diurnally without saturating.
1.SYS.1
Test
2.IMG.2
The imaging system shall detect 4th-8th (TBR)
magnitude stars having a SNR of at least 10 (TBR)
during nighttime operation.
1.SYS.2
Test
2.IMG.3
The imaging system shall detect 4th-6th (TBR)
magnitude stars having a SNR of at least 10 (TBR)
during daytime operation.
1.SYS.3
Test
2.IMG.4
The imaging system shall provide image data at a rate
of no less than 10Hz.
1.SYS.6
Test
2.IMG.5
The imaging system shall output digital data
compatible with the algorithms computer hardware.
1.SYS.4
Test
2.IMG.6
The imaging system should capture and provide
measurement and diagnostic data relating to image
capture.
1.SYS.7
Inspection
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
26
Imaging Trade Results
•
•
•
•
CCD vs. CMOS vs. CCD Array
Historical knowledge says CCD
Modern CMOS wins for implementation and speed
sCMOS likely candidate
–
–
–
–
Briefing Overview
5.3 megapixel
100 fps in camera
Low read noise
Increased red
spectrum performance
Objectives
Overview
System
Design
Options
Traditional
APS
CCD
(CMOS)
Uniqueness
1
8
Cost
5
5
Speed
3
10
Noise
9
6
Implementation
3
7
Modularity
1
8
Quantum Efficiency
9
5
Total
4.84
7.02
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
CCD
Array
Weight
7
9
6
9
1
1
9
6.13
Project
Management
Plan
1.0
1.2
2.0
1.4
2.0
.6
1.8
10
10/12/2011
27
6th Magnitude Star
4th Magnitude Star
sCMOS
Signal To Noise Ratio > 10
for 4th-6th Magnitude Stars
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Total Signal + Noise < Saturation
(30,000 e- per pixel)
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
28
Imaging Model: SNR
Purpose:
1. Make sure sensor can detect
enough stars during day
2. Sense 4th-6th magnitude stars
(1.IMG.3)
Method:
- SNR modeling
- Signal: star - background
- Noise: star, background, sensor
- sCMOS sensor assumed
- Blurring vs. megapixels (5.5 Mp
known to work)
- Blurring vs. exposure time
(shown)
Results:
1. Can sense 4th-6th magnitude
stars with SNR > 10
2. Exposure time minimum found
to be 30ms
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
29
Imaging Model: Saturation
Purpose:
1. Make sure sensor does not
saturate for 4th-8th magnitude
stars (1.IMG.1)
Method:
- Signal from 4th magnitude star,
back ground, sensor noise [e-]
- 30,000 e-/pixel well depth
- sCMOS sensor assumed
- Blurring vs. megapixles (5.5 Mp
known to work)
- Blurring vs. Exposure time
(shown)
Results:
1. Do not saturate for exposure
times less than 0.1 s.
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
30
Optics - Components
• Optics subsystem will consist of three parts:
– Telescope – designed by Equinox Interscience, built
by Equinox and DayStar
– External light baffle – designed and built by DayStar
– Sensor Container – designed and built by DayStar
baffle
Briefing Overview
Objectives
Overview
System
Design
Options
Sensor
container
telescope
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
31
Optics – Design-To Specs
Reference
Requirement
Flowdown
Verification
2.OPT.1
The DayStar optics system shall have a 5 degree by
7 degree field of view.
1.SYS.5
Test,
Analysis
2.OPT.2
The DayStar optics system shall focus an image on
the imaging sensor.
1.SYS.1
Inspection
2.OPT.3
The DayStar optics system shall block out 66%
(TBR) of the total incident light on the objective
lens.
1.SYS.4
Analysis
2.OPT.4
The DayStar optics system shall adhere to the ICD.
1.SYS.6
Inspection
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
32
Optics – Telescope Type
Refractor
Reflector
Catadioptric
Weight
[%]
Score
Weighted Score
Score
Weighted Score
Score
Weighted Score
Aperture Size
10
5
0.5
7
0.7
8
0.8
Total Weight
5
2
0.1
5
0.25
8
0.4
Length
5
4
0.2
8
0.4
7
0.35
Complexity
5
8
0.4
5
0.25
2
0.1
Errors
20
7
1.4
3
0.6
8
1.6
Machinability
10
5
0.5
6
0.6
3
0.3
Cost
2.5
4
0.1
6
0.15
5
0.125
Ease of
Baffling
20
8
1.6
9
1.8
1
0.2
Thermal
2.5
6
0.15
4
0.1
4
0.1
Maintenance
10
8
0.8
3
0.3
8
0.8
FOV
10
8
0.8
1
0.1
8
0.8
100
6.55
5.25
5.575
Best Option: Refractor
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
33
Optics – Refractor Type
• Two possible designs getting from objective
lens to first focal plane:
– One objective lens bends light onto focal plane
• Long design
• Easier to build
[15]
– Step down design with multiple lenses
• Shorter
• Much more complicated,
out of scope of class
Chosen design: One objective lens
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Nikkor 300mm f/2.0 EDIF [16]
Project
Management
Plan
10/12/2011
34
Optics – Telescope Design
Objective Lens
Field stop
Filter
Possible
intermediate
lenses
Second
focal
plane
Reimaging
system
• Field stop limits field of view
• Reimaging system demagnifies image to match sensor size at second
focal plane
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
35
Optics – External Light Baffle
• Reduce the incident light on the objective lens
• Will be placed in front of the objective lens
• Amount of light allowed through objective
lens determined by length and diameter of
baffle design
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
36
Project Feasibility Analysis
and Risk Assessment
Andrew Zizzi
Jed Diller
Sara Schuette
10/12/2011
37
Technical Risks
Risk:
Severity:
Mitigation:
Off Ramp:
Material Handling
High
ESD Training, confirm access to appropriate
workspaces/environments, use engineering
grade sensors for prototyping
Outside source assembles board
components, use of less valuable
components when possible
Peripheral Hardware
Integration
High
Obtain instruction/assistance from
professionals versed in imaging electronics,
investigate existing hardware solutions
Purchase COTS digital camera to
capture images
Interface to ST5000
Medium
Contact, lay out interface requirements,
and plan testing procedure with Jeff
Percival
Use online star identification tool and
conduct attitude transformation to
verify RMS accuracy
Hardware
Procurement Lead
Time
Medium
Order large lead-time components early
(e.g. sCMOS), plan margin into schedule
Continue development (and test, if
possible) with engineering grade
components
Insufficient test
facilities
Medium
Testing can be performed at Equinox
Interscience
Additional testing could also be
performed at SwRI
Insufficient Optical
Design Knowledge
Low
Optics expert at Equinox Interscience (Russ
Mellon) will advise the Daystar team
Telescope design has already been
outsourced to Equinox Interscience
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
38
Algorithms – Feasibility Through Analysis
Nighttime
0.1” RMS
attitude
accuracy
with 20 stars
Daytime
Requirement
1.0” RMS
attitude
accuracy
with 8 stars
“At a given
SNR, how well
do we know
our attitude?”
Briefing Overview
Objectives
Overview
Attitude Accuracy
>
Worst case
attitude of
0.05” accuracy
with 20 stars
>
Worst case
attitude of
0.1” accuracy
with 8 stars
=
“How well do
we know our
attitude from
our centroids?”
System
Design
Options
Design-To
Specifications
Centroiding Accuracy Star Detection
×
Centroid stars
up to 0.5”
accuracy
×
Centroid stars
up to 0.5”
accuracy
×
“How well can
we locate what
we detect?”
Subsystem
Design
Options
Feasibility
and Risk
Assessment
×
Detect 100%
of stars up to
8th magnitude
×
Detect 90% of
stars up to 7th
magnitude
×
“What SNR
stars can we
detect?”
Project
Management
Plan
10/12/2011
39
Algorithms – Feasibility Through Research and Experience
Research:
 All algorithms weighed in trades are based on methods utilized in astronomical
image analysis
 The chosen algorithms have been proven on other startracking devices
Experience:
 Team experience in various multi-processed, multi-threaded embedded satellite
software designs and implementations
 Team experience in data structure formation, computer systems, robotics, and
algorithms analysis
[17]
[14]
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
40
Prototyping: Imaging Sensor
Breadboard:
• Package Converter
• 168 pin LCC to DIP
package
• Power Supplies
• 5 DC Voltage
Supplies
• 82 Pins
• Control Signals
• Integration with
chosen CDH system
• 9 Digital Signals
• Data Product
• 12 Image Signals
Briefing Overview
Objectives
Overview
System
Design
Options
Imaging Interface
FPGA
USB to personal
computer
Microcontroller
Key
Power
Imaging Board
Data
Light
Engineering
Grade CMOS
Sensor
Design-To
Specifications
Subsystem
Design
Options
Power
Management
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
41
Imaging Feasibility
Problem
Feasibility
Sensing During Worst
Case Scenarios
Models show we can see 8th magnitude stars during the day and
do not saturate with 4th magnitude. Easily meet star number
requirements.
Sensor Acquisition
Adequate sensor exists. Firm quote from supplier. ($5000 new,
$500 engineering grade)
Peripheral Hardware
And Sensor Integration
Have skills to design printed circuit board and integrate sensor.
Have programming skills to use FPGA.
Possibility of sending circuitry to professionals for assembly.
Communication with
Algorithms Computer
Available resources more than adequate to read and process
sensor data.
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
42
Optics – Lenses
• Telescope designed for COTS lenses
– Objective lens from Istar Optical [18]
• Anastigmatic, achromatic
• TALL POLE: Lens may take too long to get
• MITIGATION: Backup 127 mm f/8 lens can
be substituted with limited design changes
– Intermediate lenses and relay lenses from
Edmund Optics [19]
• Achromatic doublets of various sizes
• Standard lenses available for immediate
shipment
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
43
Optics – Facilities
• Telescope design contracted through Equinox
• Equipment at Equinox
– Machining
• Knee mill x2, engine lathe, band saw, lathe, drill press
– Optical alignment tools
• Collimator, 1951 USAF resolution test chart
– Gimbaled test setup
• Can match Earth’s rotation
• Test FOV, aberrations
[20]
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
44
Testing/Verification
Test
Requirements
Verified
Description
Success Criteria
Varied Sky
Brightness
Table Test
1.SYS.1
DayStar will image the sky from evening to morning. • Images don’t
Images will be correlated with brightness readings
saturate below
to determine operational limits.
‘daytime’ flux value
Gimbaled
Star Tracking
Test
0.PRJ.1
0.PRJ.2
1.SYS.2
1.SYS.3
Using a precisely gimbaled stand that tracks the
Earth’s rotation, DayStar will track a single patch of
sky to determine statistical accuracy.
ST5000
Interface Test
0.PRJ.3
1SYS.4
• LIS solution can be
Data produced by DayStar during the Gimbaled Star
acquired
Tracking Test will by sent to University of Wisconsin
• Attitude solution
to be run through the ST5000 software.
output
Speed Test
1.SYS.6
DayStar will be run to determine total operating
speed of components and the system.
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
• 0.1” for ‘nighttime’
• 1” for ‘daytime’
• 10 Hz data output
Project
Management
Plan
10/12/2011
45
Project Management Plan
Including Personal Health and Safety
Michael Skeen
10/12/2011
46
Team Organization
Customer
Dr. Eliot Young
Advisors
Dr. Palo, Dr. Kroehl,
Russ Mellon, Kim
Ennico
CFO
Tyler
Murphy
Optics
Lead: Sara Schuette
Aaron Holt
Tyler Murphy
Briefing Overview
Objectives
Overview
Project Manager
Mechanical/Electrical
Systems
Michael Skeen
Electrical/Software
Systems
Nick Truesdale
Lead Safety
Engineer
Aaron Holt
Lead Testing
Engineer
Zach Dischner
Structures
CAD/ Fabrication
Lead: Tyler Murphy
Aaron Holt
Michael Skeen
System
Design
Options
Design-To
Specifications
Electronics
Embedded Systems
Lead: Zach Dischner
Jed Diller
Aaron Holt
Power Electronics
Lead: Nick Truesdale
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Software
Lead: Kevin Dinkel
Firmware Lead: Jed Diller
Algorithms Lead: Andrew
Zizzi
Project
Management
Plan
10/12/2011
47
Team Composition
Team Member
Leadership Position
MyersBriggs
Skills
Jed Diller
Firmware Lead
ENTJ
Software Architecture, Microcontrollers
Kevin Dinkel
Software Lead
INTJ
Software Architecture, Image Processing,
Project Management, Thermal Analysis
Zach Dischner
Embedded System Lead
Testing Lead
ENTJ
Embedded Electronics, Software
Architecture
Aaron Holt
Safety Officer
INTJ
Optics, Software, CAD, Embedded Systems
Tyler Murphy
CAD/Fabrication Lead
CFO
INTJ
CAD/Fabrication, FEA, Project Management,
Systems Engineering, Payload Integration
Sara Schuette
Optics Lead
ISTJ
Optics, High-Altitude Environment
Michael Skeen
Project Manager
Mechanical/Electrical Systems
INTJ
Project Management, Systems Engineering,
Analog Electronics, CAD/Fabrication
Nick Truesdale
Electrical/Software Systems
Power Electronics Lead
ENTJ
Systems Engineering, Embedded Electronics,
Software Architecture, Power Electronics
Andrew Zizzi
Algorithms Lead
INTJ
Image Processing, Algorithms Analysis, HighAltitude Environment, Data Structures
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
48
Work Breakdown Structure
MGMT
SYS
STR
OPT
EPS
CDH
Documentation
Requirement
Verification
Requirement
Verification
Requirement
Verification
Requirement
Verification
Financial Budget
Testing
Requirement
Verification
Testing
Power Budget
Image Sensor
Embedded
Electronics
Power Regulation
Testing
Testing
Mass Budget
Budget Upkeep
(Mass, Power,
Data)
WBS
Facilities/Tool
Arrangements
Component
Mounting
Telescope
Package
Wiring Harness
Optics Baffling
Interface
Definitions
Review and
Report
Coordination
System
Modeling
CAD /
Fabrication
Thermal Analysis
Alignment
Diagnostic
Sensors *
Environmental
Factors*
Coarse Attitude
Sensor *
Testing
Data Budget
Centroiding
Algorithm
Star Tracking
Algorithm
System Timing &
Control
Data Storage
LIS Algorithm *
* Stretch Goal Responsibility
Briefing Overview
Mechanical
Electrical
Software
25%
37.5%
37.5%
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
49
Fall Schedule
October 2011
SUN
MON
9
23
TUE
10
24
WED
THU
FRI
SAT
SUN
MON
TUE
WED
THU
FRI
SAT
1
2
3
4
5
6
7
8
18
19
20
21
22
11
12
13
14
15
16
17
25
PDR
26
27
28
29
30
31
November 2011
SUN
MON
TUE
WED
THU
FRI
SAT
SUN
MON
TUE
WED
THU
FRI
2
3
4
5
6
7
8
9
10
11
12
17
18
19
20
21
22
23
24
25
26
14
15
16
27
28
29
30
Prototype
Hardware Sourcing
Prototype Assembly
SAT
1
13
Detailed Subsystem
Design
CDR Preparations
FFR Writing
CDR
December 2011
SUN
MON
TUE
WED
THU
FRI
SAT
SUN
WED
THU
FRI
SAT
2
3
4
5
6
7
8
9
10
18
19
20
21
22
23
24
12
13
14
15
16
17
25
FFR
26
27
28
29
30
31
Objectives
Overview
TUE
1
11
Briefing Overview
MON
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Hardware Sourcing
‘Flight’ Software
Development
Project
Management
Plan
10/12/2011
50
Spring Schedule
January 2012
SUN
MON
TUE
WED
THU
FRI
SAT
SUN
MON
TUE
WED
THU
FRI
SAT
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
February 2012
SUN
MON
TUE
WED
THU
FRI
1
12
13
14
15
26
27
28
29
SAT
2
16
SUN
3
MON
4
17
18
TUE
WED
THU
FRI
MON
TUE
WED
5
6
7
8
9
10
11
19
IR 1
20
21
22
23
23
25
Electronics Testing
Machining
THU
FRI
1
SAT
2
SUN
3
11
12
13
14
15
16
17
25
26
27
28
29
30
31
MON
TUE
4
5
18
IR 2
19
WED
6
20
THU
7
21
FRI
8
22
SAT
9
23
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
System Integration
and Checkout
10
24
AIAA
Briefing Overview
‘Flight’ Software
Development
Optics Testing
SAT
March 2012
SUN
Hardware Sourcing
Feasibility
and Risk
Assessment
System Testing and
Requirements
Verification
Project
Management
Plan
10/12/2011
51
Spring Schedule (2)
April 2012
SUN
MON
TUE
WED
THU
FRI
SAT
SUN
MON
TUE
WED
THU
FRI
SAT
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Symp.
SPR
SPR Preparation
May 2012
SUN
MON
System Testing and
Requirements
Verification
TUE
WED
1
THU
2
FRI
3
FPR Writing
SAT
4
5
FPR
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
52
Financial Budget
Structures
Optics supplemental costs*
Material
Fasteners
Specialized Tools
Thermal
TOTAL
$
$ 1,000.00
$ 200.00
$ 300.00
$ 200.00
$ 1,700.00
* Customer has a pre-existing $10,000 contract in place with an
optics subcontractor for all labor and component costs
SYS (2 Hardware Sets)
Testing Equipment
TOTAL
$
$
980.00
980.00
CDH (2 Hardware Sets)
Processor
Motherboard
Memory
Testing Hardware
Hard Drive (Solid State)
TOTAL
$
$
$
$
$
$
360.00
600.00
320.00
200.00
360.00
1,840.00
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Electronics (4 Board Revisions)
Fairchild sCMOS Sensor
Engineering Grade Sensor (x2)
Prototyping sCMOS Sensor
Sensor Peripheral Electronics
Peripheral Test Equipment
FPGA Development Board
Power Regulation Components
PCB s
Static Supplies
TOTAL
Total Budget
Structures
Electronics
CDH
SYS
TOTAL
Margin ($)
Margin (%)
Subsystem
Design
Options
Feasibility
and Risk
Assessment
$ 5,000.00
$ 1,000.00
$
500.00
$
500.00
$
300.00
$
280.00
$
500.00
$
528.00
$
100.00
$ 8,708.00
$ 20,000.00
$ 1,700.00
$ 8,708.00
$ 1,840.00
$
980.00
$ 13,228.00
$ 6,772.00
33.86%
Project
Management
Plan
10/12/2011
53
Facilities and Resources
• Equinox Interscience
– Optics Advisor / Designer: Russ Mellon
– Optics – specific machining capabilities
– Precision gimbaled testing stand
• SwRI
– Testing facilities
– Imaging Advisor: Kim Ennico
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
54
Health and Safety
• Personal Safety
– Methanol used to clean optics lenses
• Gloves must be worn, avoid contact with eyes
– Soldering poses burn risk
• Proper training
– Telescope and baffling will be large and heavy
• Minimum of 2 lifting personnel, flat table workspace
• Hardware Safety
– Lenses could potentially be scratched
• Minimal cleaning, handling
– sCMOS sensor and other electronics are ESD sensitive
• ESD training, ESD safe workspaces and locked storage containers
– Transportation Risks
• Payload must be tied down during transportation, lens covers
employed
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
55
Conclusions
• DayStar: prototype star tracker system designed to improve on
current balloon attitude determination methods
– Daytime operation on at balloon platform at 35 km atltitude
– 0.1 arcsecond RMS nighttime accuracy
• Completed work:
– Characterization of high-altitude environment,
– System-wide modeling of signal and error propagation
– Subsystem performance modeling
Item
Requirement
Estimated Performance
Nighttime Accuracy
≤ 0.1 arcsecond RMS
0.05 arcsecond RMS
Daytime Accuracy
≤ 1.0 arcsecond RMS
0.1 arcsecond RMS
System Budgets
HASP ICD
40% Mass margin, 43%
Power Margin
Financial Budget
30% Margin
34.8% Margin
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
56
Acknowledgements
Project Customer
External Advisors
• Dr. Eliot Young, SwRI
• Russ Mellon, Equinox Interscience Inc.
• Kim Ennico, NASA Ames, SwRI
• Dr. Herbert Kroehl , NOAA
PAB Advisor
• Dr. Scott Palo
CU Faculty and Staff
PAB Members
•
•
•
•
•
•
Dr. Jean Koster – Course Coordinator
Dr. Dale Lawrence
Dr. Xinlin Li
Matt Rhode
Hank Scott
Trudy Schwartz
Briefing Overview
Objectives
Overview
System
Design
Options
Design-To
Specifications
•
•
•
•
Dr. Penina Axelrad
Dr. Nikolaus Correll
Dr. Eric Frew
Dr. Hanspeter Schaub
Course Assistant
• Kyle Kemble
Subsystem
Design
Options
Feasibility
and Risk
Assessment
Project
Management
Plan
10/12/2011
57
Questions?
10/12/2011
58
References
"Sunrise." Sunrise: Balloon-Borne Telescope. Web. 2 Oct. 2011.
<http://star.mpae.gwdg.de/Sunrise/>.
[2] "ST5000: Next Generation Star Tracker." University of Wisconsin-Madison. Web.
<http://www.sal.wisc.edu/st5000/mk2/intro/st5000_final2007.pdf>.
[3] Zombeck, Martin V. Cambridge University Press Handbook of Space Astronomy
and Astrophysics, Second Edition, pp. 76-78, 2001.
[4]Van Rhijn, P.J., “The Number of Stars Between Definite Limits of Proper Motion,
Visual Magnitude and Galactic Latitude for Spectral Class.” Publications of the
Kapteyn Astronomical Laboratory Groningen, vol. 36, pp.1-16, 1925.
[5] Wong, Chin L. "Implementation of the Pyramid Star Identification Technique."
Thesis. Brown University, 2007. PDF.
[6] Young, Eliot. “chsphot.py”. (python centroiding suite).
[7] Vyas, Akondi., Boopashree, M. B., and Prasad B. R. “Optimization of Existing
Centroiding Algorithms for Shack Hartmann Sensor”. Proceeding of the National
Conference on Innovative Conputational Intelligence & Security Systems. Sonal
College of Technology, Salem, April 3-4, 2009. Pp. 400-405.
[8] Vyas, Akondi., Boopashree, M. B., and Prasad B. R. “Performance of Centroiding
Algorithms at Low Light Level Conditions in Adaptive Optics”. International
Conference on Advances in Recent Technologies in Communication and Computing,
2009.
[1]
10/12/2011
59
References (2)
[9]
Kolomenkin, Michael., Polak, Sharon., Shimshoni, Ilan., Lindenbaum, Michael. “A
Geometric Voting Algorithm for Star Trackers”. IEEE.
[10\ Cole, Craig L., and John L. Crassidis. “Fast Star Pattern Recognition Using Planar
Triangles.” Web. < http://www.acsu.buffalo.edu/~johnc/star_id06.pdf >.
[11] Valdes, Francisco G., Campusano, Luis E., Velasquez, Juan D., and Stetson, Peter
B. “FOCAS Automatic Catalog Matchong Algorithm.” Publication of the
Austonomical Society of the Pacific. November 1995.
[12] Choon-Suk Oh, Hyanjae Lee., and Bang, Hyochoong. “Modified Grid Algorithm
for Star Pattern Identification by Using Star Trackers”. Korea Advances Institute of
Science and Technology. IEEE 2003.
[13] Wertz. “Chapter 4: Attitude Determination”. Chris Hall. March 18, 2003.
<http://www.dept.aoe.vt.edu/~cdhall/courses/aoe4140/attde.pdf>.
[14] Percival, J. W., Jaehnig, K. P., and Nordsieck, K. H. “The ST5000: A Low-Cost Star
Tracker for Sounding Rockets, Balloons and Class D Satellites”. University of
Wisconsin, Madison <http://www.sal.wisc.edu/st5000/mk2/intro/aas-2008.pdf>.
[15] "Refracting Telescopes." Education.com. Web. 07 Oct. 2011.
<http://www.education.com/study-help/article/physics-help-refracting-telescopes/>.
[16] "Nikkor 300mm F/2.0s ED-IF Super- Telephoto Lens." Web. 7 Oct. 2011.
<http://www.mir.com.my/rb/photography/companies/nikon/nikkoresources/telephotos/3
00mmedif20/index.htm>.
10/12/2011
60
References (3)
[17]
"Ball Aerospace & Technologies Corp." Web. 8 Oct. 2011.
<http://www.ballaerospace.com/page.jsp?page=104>
[18] "ISTAR Optical - Objective Lenses Achromatic Anastigmatic." ISTAR
Optical. Web. 07 Oct. 2011. <http://istar-optical.com/istar_019.htm>.
[19] "Achromatic Lenses - Edmund Optics." Optics, Imaging, and Photonics
Technology - Edmund Optics. Web. 07 Oct. 2011.
<http://www.edmundoptics.com/products/displayproduct.cfm?productID=174
9>.
[20] "Special Projects." Equinox Interscience, Inc. Web. 08 Oct. 2011.
<http://www.eisci.com/specproj.html>.
[21] “sCMOS_CIS2051_DATASHEET.pdf”. BAE Systems, 2011
[22] Light Path in a Cassegrain Telescope. Digital image. Reflecting Telescope.
Web. <http://en.wikipedia.org/wiki/Reflecting_telescope>.
[23] Refractor Telescope Diagram. Digital image. Web.
<http://www.daukas.com/Geoscience/MAtour/AST/background.html>.
[24] Light Path in a Schmidt–Cassegrain. Digital image. Catadioptric System.
Web. <http://en.wikipedia.org/wiki/Catadioptric_system>.
10/12/2011
61
Supplemental Content
Systems
Algorithms
Imaging
Optics
10/12/2011
62
Project Requirements
Requirement
Description
Parent
Requirement
Method of
Verification
0.PRJ.1
DayStar shall provide better than or equal to 0.1
arcsecond 1-σ RMS pointing knowledge during
nighttime observation.
Customer
Test
0.PRJ.2
DayStar shall provide better than or equal to 1
arcsecond 1-σ RMS pointing knowledge during
daytime observation (goal of 0.1 arcseconds).
Customer
Test
0.PRJ.3
DayStar shall produce data compatible with
ST5000[5] attitude determination software.
Customer
Test, Analysis
0.PRJ.4
DayStar shall demonstrate adaptability to a highaltitude balloon environment.
Customer
Test, Analysis
10/12/2011
63
System Requirements
Requirement
Description
1.SYS.1
The DayStar system shall be able to image the sky without saturating.
1.SYS.2
Parent
Method of
Requirement Verification
0.PRJ.1, 0.PRJ.2
Test
The DayStar system shall be able to identify one specific star from images captured at
nighttime.
0.PRJ.1
Test
1.SYS.3
The DayStar system shall image a minimum of 20 stars per frame having a SNR of at
least 6.0 at nighttime.
0.PRJ.1
Test, Analysis
1.SYS.4
The DayStar system shall image a minimum of 8 stars per frame having a SNR of at least
6.0 at daytime.
0.PRJ.2
Test, Analysis
1.SYS.5
The DayStar system shall be able to compute star locations from a captured image in a
format compatible with the ST5000[5] lost-in-space software.
0.PRJ.3
Test
1.SYS.6
The DayStar system shall adhere to the High Altitude Student Platform (HASP) Interface
Control Document (ICD)[6] for the mass, power, and data resources allocated up to two
large class payloads.
0.PRJ.4
Test,
Inspection
1.SYS.7
The DayStar system shall output attitude information at a frequency of 10 Hz with the
required accuracy.
0.PRJ.4
Test
1.SYS.8
The DayStar system should have a capability to measure diagnostic data at multiple
locations on the system.
0.PRJ.4
Test,
Inspection
1.SYS.9
The DayStar system will provide attitude knowledge at an accuracy of less than or equal
to 1 degree in cases where the body spin rate exceeds the star tracker capability.
0.PRJ.4
Test,
Inspection
10/12/2011
64
Post-PDR TSD
Star Tracker
Optics
Imaging
Refractor
CMOS
External
Baffling
Filter
Frame
Grabbing
CDH
Algorithms
Data
Transfer
Hardware
Computer
Number of
baffles
Longpass
FPGA
(Parallel)
USB 3.0
Consumer
grade
Size
Bandpass
AVR
(Serial)
Firewire
Low Power
CPU
(Serial)
I2C
Embedded
10/12/2011
65
Algorithms – Star Detection Trade
Star Detection Trade (DFS Intensity Limit)
Avg + STD[5]
MAD[6]
roboMAD[6]
Flight
Configurable
Trade
Elements
Weights
5
7
9
6
8
3
8
7
4
6
4
9
5.8
6.5
7
3
10
9
3
5.35
Robustness at
Low SNR
Algorithm
Speed
Simplicity
Robustness
Against False
Identifications
Total
0.4
0.25
0.1
0.25
1
10/12/2011
66
Algorithms – Centroid Trade
CoG
IWC[7][8]
roboCoG[6]
roboIWC[6]
Gaussian Fit[6]
Parabolic Fit[6]
Centroiding Algorithms Trade Study
6
10
10
6
7
9
10
7
7
9
8
8
8
9
7
8
9
4
5
9
9
4
5
9
Trade Elements Accuracy
Weights
0.4
7.4
7.8
7.7
7.85
7.35
7.35
Algorithm
Speed
Simplicity
Robustness to
Noise
Total
0.25
0.1
0.25
1
10/12/2011
67
Algorithms – LIS Trade
LIS Algorithms Trade Study
Differential Voting
Method[9]
4
6
2
7
9
5.1
Planar Trangle Method[10]
7
7
6
6
6
6.4
Pyramid Angle Method[8]
9
5
9
9
5
7.4
FOCAS Method[11]
Grid Method[12]
3
3
6
6
5
3
7
8
9
8
5.9
5.4
Trade Elements
Low # of
Stars
Algorithm
Speed
Simplicity
Low Memory
Usage
Robustness of
Convergence
Total
Weights
0.1
0.3
0.3
0.2
0.1
1
10/12/2011
68
Algorithms – Attitude Determination Trade
Attitude Determination Trade
Q-Method[13]
Triad Method[13]
QUEST[13]
Newton-Rhapson
Method[13]
Trade Elements
Weights
8
5
7
7
9
9
8
9
6
7.7
7
7.4
9
5
5
7
Accuracy Algorithm Speed Simplicity
0.5
0.3
0.2
Total
1
10/12/2011
69
Algorithms – Thermal Analysis
Background:
 HASP payload flew in Fall 2009 with ~10 W
processor – only reached 40 C
Assumptions:
1. Emissivity ≤ 0.90 and absorptivity ≥ 0.10
2. Thermal resistance of heat sink ≥ 0.1
3. Radiator area of 0.049 m2 (based on HASP
payload dimensions)
Method:
 Steady state 1D thermal analysis
Desired
Range
Max Power Dissipation (W)
Purpose:
 Determine power range for CDH processor
Results:
 Maximum heat dissipation: 38 W (30.5 W with
20% margin)
 Better power dissipations (40+ W) are possible
with a lower α / higher ε coating or a larger
radiator.
10/12/2011
70
Algorithms – Data Transfer Budget
Image Size:
 11 bits/pixel -> assume padded to 16 bits/pixel
 2160 x 2560 pixels
 12 bits/pixel * 2160 * 2560 pixel / image = 66,335,200 bits/image
Frequency Requirement:
 10 image/s minimum = 0.1 s/image maximum
 66,335,200 bits/image * 10 image/s = 663,352,000 bits/s
Standard Data Transfer Methods (Maximums):
 USB 2.0 = 480 Mbit/s
 USB 3.0 = 5 Gbit/s
 FireWire = 3.2 Gbit/s
Resulting Data Transfer Speeds:
 USB 2.0: 66,335,200 bits/image / 480*106 bit/s = 0.1382 s/image
 USB 3.0: 66,335,200 bits/image / 5*109 bit/s
= 0.0133 s/image
 FireWire: 66,335,200 bits/image / 3.2*109 bit/s = 0.0207 s/image
10/12/2011
71
Algorithms – Data Rate / Storage Budget
Data Product Size:
 Maximum of 100 viewable stars/image in FOV
 1 3 value vector per star
 8 bytes of data storage per vector value
 Data frequency of 10 image/s
 Maximum Data Rate = 100 stars/image * (8*3) bytes/star * 10 image/s = 24 kB/s
Standard Flight <= 48 hrs:
 Minimum ST Data Storage = 24 kB/s * 48 hr/flight * 3600 s/hr = 4.15 GB
Add Data for OS and H&S:
 OS / filesystem storage = ~1.0 GB
 H&S Data = ~0.5 GB
 30% Margin
 Total Data Storage = 1.3*(4.15+0.5+1.0) = 8.645 GB
10/12/2011
72
Algorithms – Onboard Memory Budget
Database Size Calculation
Assumptions:
 ~217,000 stars total that are >= magnitude 9.5
 All angles will be stored from every star to every other between 2 to 6 degrees
away
 Each angle requires 32 bytes of data
Calculations:
 In a 6 degree FOV there are: (1-cos(6 degees))/2* 217,000 stars
 In a 2 degree FOV there are: (1-cos(2 degees))/2* 217,000 stars
Result:
 Database size = 0.5 * 32 bytes * 776272 stars * (cos(6 degrees) – cos(2 degrees))
 Database size = 3.668 GB
Adding OS memory and margin:
 0.5 GB memory for OS and software operation
 Add 30% margin to be safe
 Total Memory >= (3.668+0.5)*1.3 = 5.4184 GB
10/12/2011
73
Algorithms – Gnomic Tangent Plane Correction
FOV exaggerated
for clarity
PROBLEM: Projecting the spherical sky onto a flat sensor
generates distortions in the star centroid locations that can not
be neglected due to the centroiding accuracy requirements of
this project
RESULTS:
Mitigation: Static 2D look-up table will be constructed with
corrected pixel locations which will be accessible to the star
identification and centroiding algorithms in constant time
9” maximum error
10/12/2011
74
Algorithms – Star Detection 8th Magnitude @ Day
100
100
25
3.5
90
90
3
80
60
15
50
40
10
30
20
5
2.5
70
60
2
50
1.5
40
30
1
20
0.5
10
10
10
20
30
40
50
60
70
Blur [pixels subtended]
80
90
100
0
Signal to Noise Ratio
70
Exposure Time [ms]
20
Percent of Stars Detected
Exposure Time [ms]
80
10
20
30
40
50
60
70
Blur [pixels subtended]
80
90
100
10/12/2011
75
Algorithms – Star Detection 7th Magnitude @ Day
100
100
100
90
90
90
80
80
80
70
70
60
60
50
50
40
40
30
30
20
20
20
10
10
10
8
7
10
20
30
40
50
60
70
Blur [pixels subtended]
80
90
100
60
5
50
4
40
3
30
Signal to Noise Ratio
Percent of Stars Detected
Exposure Time [ms]
Exposure Time [ms]
6
70
2
1
0
10
20
30
40
50
60
70
Blur [pixels subtended]
80
90
100
10/12/2011
76
Algorithms – Star Detection 6th Magnitude @ Day
100
100
100
90
90
90
80
80
80
70
70
60
60
50
50
40
40
16
14
60
10
50
8
40
6
30
30
30
20
20
20
10
10
10
10
20
30
40
50
60
70
Blur [pixels subtended]
80
90
100
0
Signal to Noise Ratio
Exposure Time [ms]
Percent of Stars Detected
Exposure Time [ms]
12
70
4
2
10
20
30
70
60
50
40
Blur [pixels subtended]
80
90
100
10/12/2011
77
100
100
20
90
90
90
18
80
80
80
16
70
70
70
14
60
60
60
12
50
50
40
40
30
30
20
20
20
10
10
10
10
20
30
70
60
50
40
Blur [pixels subtended]
80
90
100
0
50
10
40
8
30
Signal to Noise Ratio
100
Percent of Stars Detected
Exposure Time [ms]
Exposure Time [ms]
Algorithms – Star Detection 5th Magnitude @ Day
6
4
2
10
20
30
40
50
60
70
Blur [pixels subtended]
80
90
100
10/12/2011
78
100
90
90
90
80
80
80
70
70
60
60
50
50
40
40
60
40
10
30
20
20
20
10
10
10
30
40
50
60
70
Blur [pixels subtended]
80
90
100
0
15
50
30
20
20
70
30
10
25
Signal to Noise Ratio
100
Exposure Time [ms]
100
Percent of Stars Detected
Exposure Time [ms]
Algorithms – Star Detection 4th Magnitude @ Day
5
10
20
30
70
60
50
40
Blur [pixels subtended]
80
90
100
10/12/2011
79
Algorithms – Attitude Accuracy (Higher Centroid Accuracies)
RMS Attitude Error (arcseconds)
10
1.00" RMS
3.00" RMS
5.00" RMS
8.00" RMS
10.00" RMS
15.00" RMS
8
6
4
2
0
0
5
10
15
20
Number of Stars
25
30
35
10/12/2011
80
Algorithms – Centroid Accuracy 4th Mag @ Day
Computer Operations for Various Methods vs. Blur (67 ms Exposure)
Centroid Errors for Various Methods vs. Blur (67 ms Exposure)
500
1.4
CoG
IWC
Gaussian Fit
Parabolic Fit
roboCoG
roboIWC
1
450
Computer Operation [counts]
Centroid RMS Error [arcseconds]
1.2
0.8
0.6
0.4
0.2
0
CoG
IWC
Gaussian Fit
Parabolic Fit
roboCoG
roboIWC
400
350
300
250
200
150
100
0
10
20
30
40
50
60
70
Blur [pixels subtended]
80
90
100
50
0
10
20
30
40
50
60
70
Blur [pixels subtended]
80
90
100
10/12/2011
81
Algorithms – Centroid Accuracy 5th Mag @ Day
Centroid Errors for Various Methods vs. Blur (67 ms Exposure)
Computer Operations for Various Methods vs. Blur (67 ms Exposure)
0.9
450
CoG
IWC
Gaussian Fit
Parabolic Fit
roboCoG
roboIWC
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
CoG
IWC
Gaussian Fit
Parabolic Fit
roboCoG
roboIWC
400
Computer Operation [counts]
Centroid RMS Error [arcseconds]
0.8
350
300
250
200
150
100
50
0
10
20
30
70
60
50
40
Blur [pixels subtended]
80
90
100
0
0
10
20
30
40
50
60
70
Blur [pixels subtended]
80
90
100
10/12/2011
82
Algorithms – Centroid Accuracy 6th Mag @ Day
Computer Operations for Various Methods vs. Blur (67 ms Exposure)
Centroid Errors for Various Methods vs. Blur (67 ms Exposure)
400
1.8
CoG
IWC
Gaussian Fit
Parabolic Fit
roboCoG
roboIWC
1.4
1.2
CoG
IWC
Gaussian Fit
Parabolic Fit
roboCoG
roboIWC
350
Computer Operation [counts]
Centroid RMS Error [arcseconds]
1.6
1
0.8
0.6
300
250
200
150
100
0.4
50
0.2
0
0
0
10
20
30
40
50
60
70
Blur [pixels subtended]
80
90
100
0
10
20
30
40
50
60
70
Blur [pixels subtended]
80
90
100
10/12/2011
83
Algorithms – Centroid Accuracy 7th Mag @ Day
Centroid Errors for Various Methods vs. Blur (67 ms Exposure)
Computer Operations for Various Methods vs. Blur (67 ms Exposure)
4
350
CoG
IWC
Gaussian Fit
Parabolic Fit
roboCoG
roboIWC
3
300
Computer Operation [counts]
Centroid RMS Error [arcseconds]
3.5
2.5
2
1.5
1
250
200
150
100
50
0.5
0
CoG
IWC
Gaussian Fit
Parabolic Fit
roboCoG
roboIWC
0
10
20
30
40
50
60
70
Blur [pixels subtended]
80
90
100
0
0
10
20
30
40
50
60
70
Blur [pixels subtended]
80
90
100
10/12/2011
84
Imaging Model Assumptions
2.5
-3
2
Blackbody curves for normalized total irradiance (1 W /cm)
B = 10,000 K
A = 7500 K
F = 6000 K
G = 5200 K
K = 3700 K
M = 2000 K
2
1.5
1
0.5
0
0
500
1000
1500
 (nm)
2000
2500
3000
Bolometric Correction vs. Star Temperature
0
-1
-2
Change in Magnitude
2
Irradiance (W/cm /nm)
• 𝜆 = 441-1080 [nm] (MODTRAN data limits)
• Optical Transmission Efficiency = 0.95
• MODTRAN at 35 [km] = 115,000 [ft],
LAZ = 90o
• sCMOS values
– QE, 𝜆 range, read noise 10 [e-], dark
current 65 [e-/pixel/s],
well depth = 30,000 [e-]
• Black body stars
– Bolometric correction
• Gaussian distributions (blur)
x 10
-3
-4
-5
-6
-7
M = 2000 K
K = 3700 K
G = 5200 K
F = 6000 K
-8
-9
2000
3000
4000
5000
6000
7000
Temperature (K)
8000
9000
10000
10/12/2011
85
Imaging Model: 2D plots
Magnitude/Flux variation for m=8 star
SNR vs. Star Temp (8th mag)
120
120
100
Flux (photons/cm /s/nm)
100
mbol=4.8248
mbol=6.3545
mbol=7.2543
mbol=7.6514
mbol=7.8601
80
2
80
60
40
60
40
20
20
0
2500
3000
3500
4000 4500 5000 5500
Star Temperature [K]
6000
6500
0
7000
0
500
1000
SNR vs. Megapixels
1500
2000
2500
Wavelength (nm)
3000
3500
4000
SNR vs. Exposure Time
25
22
20
20
Signal to Noise
18
Signal to Noise
Signal to Noise
T=3000,
T=3700,
T=4500,
T=5200,
T=6000,
15
10
16
14
12
10
5
8
0
0
1
2
3
4
5
Megapixels]
6
7
8
9
6
0
0.02
0.04
0.06
Exposure Time [s]
0.08
0.1
10/12/2011
86
Imaging Model: SNR
• Megapixels vs. blurring
– Daytime
– 4th-8th mag
– Tstar = 7962K (weighted avg.)
– Blurring (16-36 for algorithms)
– Exposure time
• Result: 5.53 Mp SN>10
10/12/2011
87
Imaging Model: Enough SNR
•
•
•
•
•
•
Exposure time vs. blurring
4th-6th magnitude
Tstar = 7962K (weighted avg.)
5.53 Mp sCMOS
Blurring 16-36 (optimal)
Exposure time 1/10th – 1/100th s
• Result: texp = 0.3ms S/N > 10
10/12/2011
88
Imaging Model: Saturation
•
•
•
•
•
•
Exposure time vs. blurring
4th magnitude
Tstar = 7962K (weighted avg.)
5.53 Mp sCMOS
Blurring 16-36 (optimal)
Exposure time 1/10th – 1/100th s
• Result: No saturation
10/12/2011
89
Imaging Model Data
10/12/2011
90
Imaging Model Equations
𝑆
=
𝑁
𝑆𝑠𝑡𝑎𝑟
𝑆𝑠𝑡𝑎𝑟 ∗ 𝑡 + 𝑆𝑏𝑔 ∗ 𝑡 ∗ 𝑏𝑙𝑢𝑟 + 𝐷𝐶 ∗ 𝑡 ∗ 𝑏𝑙𝑢𝑟 + 𝑅𝑁 2 ∗ 𝑏𝑙𝑢𝑟
10/12/2011
91
sCMOS Data
[21]
10/12/2011
92
Prototyping Clocks
• Common Input-Basic Rolling Shutter Readout
Scheme1.0
10/12/2011
93
Supporting sCMOS
• Power requirements-0-3.3V DC
• 5 or 6 separate levels
• Digital protocol: 1.8V LVCMOS and 1.8V
HSTL
• 168 Pin LCC surface mount package
• 54 supply pins
• 28 ground
• 22 input
• 64 output
• 12 pins for data output
• Many others for diagnostics
10/12/2011
94
CMOS Comparison: Cameras
10/10/2011
95
CMOS Comparison: Chips
10/10/2011
96
Power Budget
• 150 W total power
– Processor: 40 W
– Motherboard: 30 W
– sCMOS: 2 W
– Microcontroller: 2 W
– FPGA: 2 W
– Regulator efficiency: 0.90
• Total consumption: 84.4 W
• Margin: 43.7% (65.6 W)
10/12/2011
97
Reflector Trade Study
• Pros:
–
–
–
–
Easy to baffle
Fewer aberrations
Short design
High contrast images
[22]
• Cons:
– Secondary mirror block some light
– Affected by temperature changes
– Cannot produce field view greater than 1 degree.
10/12/2011
98
Refractor Trade Study
• Pros:
–
–
–
–
High contrast images
Closed tube design
Low maintenance
Easy to baffle
[23]
• Cons:
– Lenses can be expensive
– Chromatic aberrations
– Longer and heavier than other types
10/12/2011
99
Catadioptric Trade Study
• Pros:
– Good for deep sky objects
– Short, closed tube design
– Low maintenance
• Cons:
–
–
–
–
–
[24]
Increased errors with low f-ratios
Impossible to baffle internally
Difficult to modify COTS telescope
Expensive
Added complexity
10/12/2011
100
Optics – FOV Feasibility
• Current objective lens: Istar Optical 152 mm f/4.7
Aperture
= 152 mm
α
α
Focal Length = 714.4 mm
• Find alpha
α = atan(152/714.4)
= 12.01°
• Alpha is half of FOV
• FOV of lens = 24.02°
• Field stop reduces
FOV to 8.6° diagonal
10/12/2011
101
Detailed analysis of First Design
Size of Field Stop
4.3°
8.6°
5°
FL = 714.4 mm
x
107.8 mm
62.66 mm
87.72 mm
7°
x= tan(4.3)*714.4 = 53.9 mm
Full diagonal = 107.8 mm
10/12/2011
102
Detailed analysis of First Design
diag1
diag2
f1
f2
Demagnification
y = 43.73 mm
Size of image at
imaging focal plane
43.73 mm
35.28 mm
25.42 mm
10/12/2011
103
Aberration Analysis
Aberration
Effect
Mitigation
Spherical
Defocusing of point source
Anastigmatic lenses
eliminate effects
Coma
Off-axis point sources
become distorted
NONE - refractors have little
or no coma
Astigmatism
Two planes of the light do
not focus at the same point
NONE- most designs have no
noticeable effects
Field Curvature
Curved sky does not focus on
a flat sensor
Field flattener if needed
Distortion
Deviation from rectilinear
projection
Specific lens selection
Longitudinal Chromatic
Only one color is in focus at
a time
Achromatic lenses limit the
effects
Lateral Chromatic
Color fringing at edge of
field
NONE - most designs do not
have noticeable fringing
10/12/2011
104
External Light Baffle
10/12/2011
105
Preliminary Mass Budget
• 40 kg total mass
• Assume 40% margin (16 kg)
– Electronics, enclosures, and radiators – 8kg
– Optical telescope – 10 kg
– Light baffle – 6 kg
10/12/2011
106