MZA Associates Corporation

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• MZA Associates Corporation
• Overview Capabilities
• Bob Praus
• Steve Coy
• October 12, 2005

MZA Associates Corporation 2021 Girard SE, Suite
150 Albuquerque, NM 87106 Voice (505)
245-9970 Fax [phone] praus_at_mza.com coy_at_mza
.com
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Organizational Overview

• A progressive research services company with an
  emphasis in software and adaptive optics systems.
• 30 employees (11 Ph.D., 6 M.S.)
• Established in 1991
• Incorporated in Albuquerque, New Mexico
• Dayton office Established in October 2005
• Bob Praus, President and Senior Software Engineer
• 24 years experience in scientific computing.
• Contribution to wave optics codes since 1983
  (WCSS, TASAT, WaveTrain).
• Formerly the software manager of the National
  Test Facility for Martin Marietta.
• Primary inventor of Adaptive Dynamic Range
  Wavefront Sensor (ADRWFS, Pat. 6,707,020).
• Principal investigator on AFRL support and ABL
  modeling contracts.
• Expert in supercomputing, data management
  analysis.
• Steve Coy, Principal Scientist
• 19 years experience in analysis, simulation, and
  the design of software tools.
• Primary author of WaveTrain and tempus.
• Record of innovation in adaptive optics Variable
  and Multi Conjugate Adaptive Optics, Novel
  control concepts.
• Inventor of image enhancement techniques which
  are in widespread use in astronomical and space
  surveillance telescope systems.

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MZA Senior Staff

• Dr. Russ Butts, Senior Scientist
• Former 30-year AFRL scientist, world-renowned in
  the area of directed energy weapons systems.
• Department of Defense Distinguished Civilian
  Service Award.
• Fellow of the Directed Energy Professional
  Society.
• Author of over 65 technical publications.
• Dr. Matthew Whiteley, Vice President
• Former ATK Senior Research Scientist and Group
  Leader who built a staff of adaptive optics and
  atmospheric propagation expert.
• Primary author of SCALE and SHaRE HEL system
  performance models.
• Former USAF Captain who served as the PI for the
  NOP DyCE AO experiment at NOP.
• Dr. Justin Mansell, Senior Scientist
• Inventor of numerous AO components and systems
  including MEMS membrane DMs.
• Co-founder of Intellite (now Agiloptics), one of
  the leading DM suppliers.
• Principal investigator of a innovative laboratory
  experiment of relay concepts.
• Dr. Boris Venet, Senior Scientist
• 18 years experience in optical physics research
  emphasizing atmospheric propagation.
• PI of MZA's AFRL support and Maritime modeling
  contracts.
• Dr. Eric Magee, Senior Scientist
• Lead author of ATMTools a Matlab-based
  atmospheric propagation scaling code.
• Developer of phase screen generation technique
  which extrudes correct long phase screens.

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ABL-Related Accomplishments of MZA

• Airborne Laser Experiment (ABLEX)
• Reduced and analyzed the data from this
  aircraft-to-aircraft experiment designed to
  characterize atmospheric scintillation.
• Airborne Laser Atmospheric Characterization
  Experiment (ABLE ACE)
• Designed and implemented sophisticated software
  system for the management and reduction of the
  data.
• Reduced and analyzed the data from this
  aircraft-to-aircraft multi-sensor experiment
  looking at atmospheric scintillation and phase
  effects.
• Identified two separate problems which threatened
  the success of the 20M experiment, and devised a
  crucial fix for one of them.
• Airborne Laser Advanced Concepts Testbed
  (ABL-ACT)
• Primary designer and implementor of the NOP
  optics system.
• Designed the networking and implemented the
  computing concept throughout the facility.
• Designed and implemented numerous control and
  data acquisition systems including
  scintillometers, weather stations, high-speed
  science cameras, laser personnel safety systems,
  differential image motion meters, and atmospheric
  profiler systems.
• Designed and implemented the data management and
  analysis system.
• Using WaveTrain, MZA is the primary system
  modeler for the NOP system and related
  experiments.
• Airborne Laser Modeling and Simulation
• Designer and implementor of the ABL SPO beam
  control system performance model, ABLWOPM.
• Assisted in anchoring ABL's top-level system
  performance models to ABLWOPM. In the process of
  anchoring ABLWOPM to ABL ground test and flight
  data.
• Performed and assisted others in performing
  numerous parametric studies using ABLWOPM.
• Architect and integrator of ABL Performance
  Analysis Toolkit (ABL PAT) a top-level time-line
  simulation of ABL which uses SCALE as the primary
  system lethality model.

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Other Accomplishments of MZA

• Adaptive Dynamic Range Wavefront Sensor
• Bob Praus and Dr. Dan Eastman invented the
  Adaptive Dynamic Range Wavefront Sensor (ADRWFS),
  patent pending. We built a system, developed its
  software, and delivered it to AFRL for less than
  100K.
• Variable Conjugate AO for Imaging Beam
  Projection Systems
• MZA originally proposed and developed the
  Variable Conjugate Adaptive Optics (VCAO) concept
  which can result in improved imaging and beam
  projection performance.
• Image Enhancement Techniques
• Steve Coy developed an image enhancement
  algorithm now in regular use at the MSSS and SOR.
• Waffle Constrained Reconstructor
• Bob Praus invented the Waffle Constrained
  Reconstructor (WCR) a waffle suppressing
  reconstructor which uses a novel constraint
  during the pseudo-inverse process.
• ABL Range Simulator Optical Design
• MZA designed the ABL range simulator telescope
  optical system.
• Other WaveTrain Models
• Airborne Laser (ABL) augmented by an optical
  relay system
• Airborne tactical HEL system with and without
  relays
• Navy ship self-defense laser with and without
  relays
• Starfire Optics Range (SOR) adaptive optics
  performance model
• SOR active tracking system modeling
• Ground-based space debris tracking system
• Maritime atmospheric characterization experiment
• Detailed Anchoring of WaveTrain

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MZA Contributions
About MZA, AFRL customers wrote Their untiring
efforts were key in the ultimate success of the
ABLE ACE project, a project which was recently
awarded the AFMC Scientific Achievement Award for
1995. Through careful examination of the data,
MZA discovered problems with the Differential
Phase Experiment, the highest priority experiment
on ABLE ACE, and devised strategies for solving
those problems. Without their crucial
contributions, ABLE ACE would have failed.
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MZA Flagship Software
tempusTMmodernizing interdisciplinary simulation
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(No Transcript)
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WaveTrain ABL Model
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North Oscura Peak DyCE Simulation(provided by
AFRL)
atmosphere
NOP ground systems
DyCE aircraft
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WaveTrain is Anchored to NOP Field
DataPeak-to-Peak Closed-Loop Performance

• Experimental results adjusted for uncorrected
  system losses (as measured)
• Green curve represents DyCE simulation with
  CLEAR-1 profile
• Red curve represents DyCE simulation with
  CLEAR-1/NF5 profile

System performance bounded by simulation with
atmospheric models which bound observed
atmospheres in (r0 , R) parameter space
Provided by Capt. Matt Whiteley
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tempusTMmodernizing interdisciplinary simulation
The Challenge of Interdisciplinary
Simulation Computer simulation has become an
important tool in many fields of endeavor, from
science and engineering to computer based
training and computer animation. Over the years
considerable progress has been made in tools and
methodologies for simulation, but much of this
progress has come in the form of improvements to
a variety of relatively specialized tools, for
modeling control systems, flexible structures,
fluid dynamics, communication networks, and so
forth. By comparison, relatively little progress
had been made in tools designed to support
interdisciplinary simulation, involving
interactions among subsystems with qualitatively
dissimilar behaviors and requiring differing
modeling approaches. This is easy to understand,
because it is a hard problem, and ill-defined.
But for some classes of applications, it is
crucial. The Solution is tempus tempus uses a
powerful and flexible block diagram-based
architecture designed to meet the demands of
multidisciplinary simulation. Combining ideas
from object-oriented programming and hybrid
simulation, tempus can be used to model just
about anything. It also has an open
architecture, which makes it easy to integrate
other software into tempus, and vice versa.
the new tempus GUI
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tempus scaling code model (tier II) of a generic
solid state laser weapons system (for HEL JTO)
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tempus engagement model of the ABL
tempus ABLPAT
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ADRWFSTMAdaptive Dynamic Range Wavefront Sensor

• A Solution to the Challenge of Wavefront
  Measurement in Highly Aberrated Systems
• The adaptive dynamic range wavefront sensor
  images the pupil of a test optic or wavefront
  onto both a spatial light modulator (SLM) and the
  lenslet array. The pupil imaging is arranged so
  that each lenslet is imaged on to a sub-array of
  the SLM that operates as a simple shutter for
  each lenslet. The system is programmed to choose
  the subset of lenslets illuminated in a single
  frame. This process optimizes data acquisition
  for the various types and magnitudes of wavefront
  aberrations. With only some lenslets illuminated
  in each frame, the foci unambiguously occupy a
  larger segment of the detector array. The dynamic
  range is increased and at the same time the
  precision of the local slope error is maintained.
  From a number of frames, the slope measurements
  are combined to provide a complete wavefront
  measurement of the test object.

US Patent 6,707,020
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• What follows is illustrative information about
  MZA optical design, data acquisition, and data
  management and analysis support.
• More information about WaveTrain modeling and
  simulation can be found in the WaveTrain Gallery.
• More information about tempus can be found in the
  tempus DE overview.

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Optical System Design and Implementation

• MZA was a leader in the design and implementation
  of experimental adaptive optics and tracking
  systems for AFRL
• Airborne Laser Advanced Concepts Testbed
  (ABL-ACT), North Oscura Peak and Salinas Peak
  Optical Systems. Primary optical system designer
  for this experiment which includes
  non-cooperative adaptive optics and tracking
  systems, a variety of diagnostic and atmospheric
  measurements, and a multibeam illumination
  system.
• ARGUS Stellar Scintillometers Designed and lead
  the implementation of two airborne
  scintillometers which measure scintillation over
  long horizontal paths.
• Airborne Laser Atmospheric Characterization
  Experiment (ABLE ACE) Dr. Eastman designed the
  optical system for the integration of a variety
  of atmospheric optical measurements including a
  differential phase interferometer, a Hartmann
  wavefront sensor, and pupil and far-field imaging
  cameras.
• High Altitude Balloon Experiment (HABE) Initial
  designer of opto-mechanical concepts.
• AEOS telescope Supported parametric designs and
  procurement issues.
• MZA designed the Range Simulator telescope
  optical system for ABL.
• To test variable conjugate and multiple conjugate
  adaptive optics concepts, MZA designed
  modifications to the MIT Lincoln Lab advanced
  concepts laboratory.
• Dr. Seward implemented the multi-beam illuminator
  system at NOP.

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North Oscura Peak LayoutPupil Relays from
Telescope to WFS and Tracking Cameras
Multi-Beam Beacon Lasers
WFS Camera
Tracking Cameras
In Situ Interferometer
Fast Steering Mirror
To Coude Path and Telescope
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Data Acquisition Systems

• In support of ABL-ACT, MZA developed a number of
  data acquisition systems based on a client/server
  model.
• Our approach has evolved as we have gone along,
  but we think that what we do has broad
  applicability.
• We devised a high-speed Windows-NT-based camera
  acquisition system.
• Uses Imaging Technologies PCI-based frame
  grabbers.
• Drives Dalsa area scan cameras, but any RS-422
  will do.
• Achieved 2,900 frames per second of data
  acquisition and computation. Theoretically more
  than 10,000 64x64 frames per second is possible,
  but we dont have any cameras that fast.
• Based on novel client/server software utilizing
  Windows-NT shared memory files.
• Has many applications in laboratory
  instrumentation.
• Could be used as the basis for a low-cost tracker
  system.
• Matlab interfaces are available (hardware in the
  loop simulations).
• Less than 12,000 in hardware costs for a very
  capable system.
• Our approach to client/server acquisition allows
  remote control and remote monitoring of devices.
• We use the network as the interface between
  software components.
• We use multicasting of data to reduce network
  traffic and make data available to multiple
  viewers.
• We developed a wavefront sensor implemented in
  Matlab and interfaced to a Dalsa camera and LCD
  spatial light modulator.

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Image Capture System (ICS)
Network
Dual Processor Windows NT System
Shared Memory
Record Server
ITI PCIFrameGrabber
DAQ Process
Multicast Client
Compute Engine
Multicast Server
Multicast
Multicast Client
Network Card
ImageDisplay GUI
Multicast Client
Control Server MFC-based GUI
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ICS Control GUI
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ICS Image Display GUIs
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Data Acquisition Objectives

• Implement a uniform approach to Data Acquisition
  throughout the facility.
• Reduce costs through code-reuse.
• Standardize interfaces between control, snoop,
  and data acquisition components.
• Allow for centralized and distributed control and
  monitoring of experimental components.
• Allow for experiment director to control and
  monitor multiple components from a single
  console.
• Allow for individual experiment operators to
  control and monitor components from convenient
  locations throughout the facility.
• Allow for control and monitoring functions to be
  performed from geographically separated
  locations.
• Provide a flexible software model for building
  data acquisition devices.
• Building a new data acquisition device involves
  following a well-defined prescription.
• Data acquisition run on both Linux and Windows-NT
  machines.
• Approach allows for rapid-prototyping. The
  fundamental system is designed, so each new
  system does not require and extensive design
  process.
• Provide a flexible interface for monitoring
  acquired data.
• Data monitoring functions utilize the multicast
  internet standard, so any device capable of
  receiving multicast packets can monitor acquired
  data.
• Use of multicast minimizes network traffic. Only
  one copy of the data is put on network lines
  while many listeners can obtain the data.

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DACS Framework

• DACS prescribes three processes which run on the
  data acquisition device
• DAQ (Data Acquisition Process)
• The DAQ process is implemented as a finite state
  machine which interfaces with the data
  acquisition electronics.
• Observe instructions from the control server
  process (CS).
• Acquire data from data acquisition electronics.
• Record data as instructed (usually to disk).
• Make data available to the multicast server (MS)
  process as instructed.
• CS (Control Server Process)
• The CS communicates with the user with simple
  ASCII commands. After verifying that the commands
  are valid, it relays the information to the DAQ
  and MS processes.
• Allow telnet connections from control clients.
• Parse text commands from clients. Relay valid
  information to DAQ and MS.
• Respond with error messages when appropriate.
• MS (Multicast Server Process)
• The MS is a simple process which multicasts data
  throughout the network when so instructed.
• Monitors commands from CS.
• Multicasts data appearing in snoop buffer
  provided by DAQ.

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The DACS Model
Network
Control Client
Data Acquisition Machine (Pentium running Linux
or Windows-NT)
DAQ Process
Shared Memory
Multicast Server
Multicast Client
Multicast
Network Card
Control Server
Multicast Client
Telnet
Disk
Multicast Client
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DACS Software Details

• All three processes are implemented as C
  classes with consistent interfaces.
• The three processes communicate via shared
  memory.
• The CS and MS are generally simple applications
  needing little modification from component to
  component.
• The DAQ process is more complicated in that it
  must interface with the data acquisition hardware
  and often meet stressing speed requirements.
• The ACE library (http//siesta.cs.wustl.edu/schmi
  dt/ACE.html) is used to provide a portable
  mechanism to obtain object-oriented access to
  operating system and networking facilities.
• Multicasting is an internet standard which allows
  one-to-many network communications.
• DACS does not dictate the form of the user
  interface for controlling data acquisition
  devices or monitoring acquired data. However, it
  does facilitate the implementation of simple GUIs
  to perform such functions.

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ABL-ACT Control Clients

• The control client allows experimentalists to
  control ABL-ACT components from anywhere on the
  internet.

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ABL-ACT Snoop Clients

• The snoop client allows experimentalists to
  monitor acquired data from any subnet to which
  data is tunneled.

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Scintillometer GUIs
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Laser Controller GUIs
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Weather Station GUIs
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Safety Systems GUIs
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Matlab ODBC Interface

• We have written a package which allows database
  data to be queried, retrieved, and stored from
  within Matlab.
• This is based on the Open Database Connectivity
  (ODBC) standard which all major database systems
  support.
• Database table structures are mapped directly to
  Matlab structures.
• Example Matlab commands
• dbid,rc mdbopen('mmactdual','sverzi',xxxx
  xxx')
• tabs,rc sqltables(dbid)
• cols,rc sqlcolumns(dbid,'ACTScintStatsL3')
  
• ts,rc mdbfetch(dbid,'ACTScintStatsL3','tim
  e,cn21,cn22',
• 'time BETWEEN 19981217000000000000 AND
  19981218000000000000','time')
• rc,sql mdbcreate(dbid,'MyScintStats30',myt
  s,types)
• rc,sql mdbinsert(dbid,'MyScintStats30',myt
  s)
• rc mdbclose(dbid)
• The software is used to manage and process the
  ABL-ACT data.

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RDBMS Tables are Mapped to Matlab Structures
The structure in Matlab whos t Name
Size Bytes Class t 1x10
12384 struct array Grand total is 240
elements using 12384 bytes t t 1x10
struct array with fields RecordID
SampleBT SampleST BkgMean BkgVar
SigMean SigVar SigNormVar Cn2
StatLength SampleRate AtoDConv
The Table in Access