© 2001 Mercury Computer Systems, Inc.

Underwater Tactical Operations Center

(UTOC)

Underwater Tactical Operations Center

(UTOC)

David A. Toms

Mercury Computer Systems

Dtoms@mc.com

2© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

OutlineOutline Trends in tactical C4ISR:

1991: TOCs can’t get enough intel support 2002: TOCs are inundated with intel products Targeting timelines are increasing! New tools are required to process the data

USAF/USA TOCs are migrating toward mobile, lightweight, open architectures

Technology demonstrations at Mercury Intelligent Bandwidth Data Compression Aided Target Recognition Multi-Hypothesis Target Tracking Geo-registration

Open Wings A new architecture for tactical op centers

3© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

High-Value Targets

Military ConvoysMassed Forces

Function of Underwater Tactical Operations Center Provide Surveillance Operator with Unified Tactical Picture via GIG Tools to Review Sensor Information, Provide Contextual Information Remove Sensor Clutter, Fuse Target Information

UTOCProcessing

ProcessingExploitation

(Sensor)Tasking

Dissemination

Processing

Processing

Collection Platforms

‘Common Operational Picture’

UTOC ISR SystemUTOC ISR System

4© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

UTOC ProcessingUTOC Processing

‘TPED Crisis’ Trained Image Analyst can

Process 10-30 Full-Scene 1Mega-pixel SAR Images/Hr (Global Hawk Will Generate ~6,000 Images/Hour)

Trained Surveillance Operator can Track 3-6 Targets (Joint STARS will Generate 10,000 Target Reports per second)

Trend Semi and Fully Automated

Tracking, Registration, ATR, Data Fusion

Semi-Automated Situation Assessment, Sensor Tasking TPED: Tasking, Processing, Exploitation, and Dissemination

PD: Probability of Detection, FAR: False Alarm Rate

Assisted Exploit.

ATR only

IA only

PD

FAR

How Well do IAs Classify Targets?

Dr. John M. Irvine, SAICPresentation at ATR Transition Conference, MIT Lincoln Lab, June 7, 2000

5© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

Processing Algorithms Processing Algorithms

Tracking

ATR

Fusion

PatternAnalysis

Filtering

Detection

SituationAssessment

Algorithm

Phy

sics

Geo

met

ryS

tatis

tical

Rul

e-B

ased

Model

Information Processing

KnowledgeProcessing

Intelligence

Type

Signal Processing

Data Processing

Processing

10 - 100GFLOPS

100s of GFLOPS

Throughput

Amount of Sensor Data (100s of MB/s)

Dec

reas

ing

Am

ount

of

Dat

a

Incr

easi

ng D

esire

d In

form

atio

n

Impact

MercuryDomain

6© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

Signal and Data Processing Architecture

Signal and Data Processing Architecture

MTI SignalProcessing (e.g., STAP)

SAR ImageFormation

SARRegistration

MTI TargetDetection

MTIRegistration

SAR TargetDetection

Video/IRRegistration

TargetDetection

SAR FeatureExtraction

FeatureExtraction

HRR FeatureExtraction

ATR

2D ATR

1D ATR

TrackingSensor

Tasking

Multi-Sensor/Multi-LookATR Fusion

Chip-Level ProcessingImage Processing

Report ProcessingSignal Processing

Video/IR Signal

RadarSignal

Sensor Mode/Look Region

Image-Level Processing

‘Data’ Processing

Image ChangeDetection

Fire ControlSystems

Signal Analysis Registration

ESM

7© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

UTOC Data FusionUTOC Data Fusion

Types of Sensor Data to be fused: Synthetic Aperture Radar imagery Ground Moving Target Indicator reports Electro-optic/Infrared imagery Hyperspectral imagery SIGINT/ELINT reports COMINT data BDA Chem/Bio/WMD reports Minefield delimitations Unattended sensors

8© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

Stand-Alone DemonstrationsStand-Alone Demonstrations

Tools are required to analyze all the data

Completed demonstrations: Intelligent Bandwidth Compression (Sandia

Labs/Black River Systems/Mercury) Model-based ATR Algorithm (DARPA) Geo-Registration (DARPA)

Under Development Multiple Hypothesis Tracking (DARPA)

9© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

Intelligent Bandwidth CompressionIntelligent Bandwidth Compression

Full-Scene Image Compressed After Target Chips Have Been Detected High Ratio for Background Low Ratio for Target Chips Overall Ratio ~128:1

10© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

GMTI Tracking FunctionGMTI Tracking Function

Generate Target Tracks Based on MTI Radar Reports

Tracker has to Account for Non-constant Target Velocities Measurement Errors Missed Detections False Reports

MTI REPORTS

TRACKS

11© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

GMTI Tracking ApproachGMTI Tracking Approach

PREDICTTRACKS

PREPROCESSREPORTS

GATE REPORTSWITH TRACKS

UPDATETRACKS

TRACKHYPOTHESIS

MANAGEMENT

MTIReports

DTEDData

RoadData

DTEDData

RoadData

TargetTracksConstrained

MTI Reports

Report/TrackPairs

Updated TrackHypotheses

Predicted TrackHypotheses

Retained TrackHypothesesTime

Multitarget Tracking Associate Reports for Tracks Filter out Measurement Noise by Averaging

Multiple Hypothesis Approach (MHT) Form Multiple Hypotheses for Report

Associations and Target Kinematics Select Most Likely Hypothesis After Processing

Multiple Frames of MTI Reports

CREATENEW TRACKS

SearchProblem

12© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

Image Registration FunctionImage Registration Function Provides Spatial Correspondence Between Two Images Image Registration Prerequisite for Performing Change

Detection

Registration Results: Alan Chao, Alphatech

13© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

Image Geo-Registration ApproachImage Geo-Registration Approach

Two-step Procedure

Image Geocoding (Image Ortho-rectification): Image Projected to a Common Reference Frame

Image Registration: Uses Image Data (Pixel Intensities or Image Feature) to Find Spatial Correspondence Between Images

ImageGeocoding

ImageRegistration

Images

SystemError Statistics

GeocodedImages

GeocodingError Statistics

RegisteredImages

RegistrationError Statistics

RelativeGeometry

SearchProblem

14© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

Image Registration RequirementsImage Registration Requirements

Function of Feature or Pixel Intensity Approaches Features Used (e.g., Topological, Region, Object) Matching Algorithm (e.g., Hausdorff Distance,

Bayesian Metric) Desired Accuracy

Preliminary Estimates (Feature-Based Algorithm for SAR Image Registration) ~450x350 Pixel SAR Image 10 -100 Giga operations

Processing Requirements are Function of Input Rate, Data Characteristics, Desired Performance

15© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

ATR FunctionATR Function

Classify Target Based on Image Chip 2-D ATR: Uses High-Res SAR Image Data 1-D ATR: Uses High-Res Range Profile from

Radar MTI Data (Research Area)

T72Confidence:0.95

2-D ATR 1-D ATR

SCUD TELConfidence:0.7

Range-DopplerTarget Chip

SARTarget Chip

Range-Profile

16© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

2-D ATR Approach2-D ATR Approach

Traditional Approach: Template-Based Store Target SAR Templates for Various

Poses, Articulation Find Best Match and Declare Target Type

Model-Based Approach (Research) Store Wire-Frame Model for Various Target

Types Predict, Evaluate, Match, Search for Best

Match of Pose and Articulation

17© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

2-D ATR Requirements2-D ATR Requirements

Preliminary Estimates From Demo System Chip-Level Parallel Processing

Approx. 40 Mega operations per Chip

Ground Truth

System call & score, if correct

System call & score, if incorrect

T72 T72 BTR70 SA8 ZSU T72 BTR70ZSU SCUD T72

T72 BTR70

ZSU T72SCUD SA8ZSUBTR70 ZSUBTR70SA8ZSU

T72 T72 BTR70 SA8 ZSU T72 BTR70ZSU

T72 T72 T72BTR70 SA8 ZSU T72 BTR70 SCUD.95.90 .85 .80 .95 .95 .65 .80 .90

Click on image chip to inspect

ATR details

Click on image chip to inspect

ATR details

18© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

Model-Based ATR AlgorithmModel-Based ATR Algorithm

Type (x,y) ScoreM2 35,87 10 0.91M548 38,88 14 0.83BMP2 32,89 192 0.05...

Focus ofAttention

Index

Search

Predict

Match

Extract

SAR Image

Detect

Scene Hypothesis

ROIs

ROI

PredictedFeatures

ExtractedFeatures

Evaluations

Scene Model

CoarseHypotheses

Cue

Explain

Verify

19© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

Mercury Role in UTOCMercury Role in UTOC

Established Leader in Signal Processing Expertise in Sensor Algorithm Technology Middleware to Support Application Development Low space, weight and power requirements

Mercury HPC Architecture Well-Suited for Data Processing Can be Scaled to Support Improvements in Sensor

Resolution Supports Algorithms Requiring Tight Coupling

Between Signal & Data Processing Functions Testing underway at WPAFB Sensor laboratory

20© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

Participation in Ground Station Activities: Openwings

Participation in Ground Station Activities: Openwings

OpenwingsArchitecture

HPCUTOC

Dom

ain

Exa

mpl

eProcessingRequirements

Container

Specifications

Openwings: Architecture for Plug-and-Play, Network Centric, Service Oriented System

Mobile Ground Stations is a Domain Example

Mercury is on Expert Team Analyzing Ground Station

Processing Requirements Developing HPC Container

Specifications• Life Cycle Support for an

Application• Clustering of Processors• Process Load Balancing www.openwings.org

21© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

Program OverviewProgram Overview

Openwings initiative established June ‘99 as a Joint IR&D effort between Motorola & Sun

Motorola and Sun Microsystems to lead a community in the development of a distributed, self-forming architecture

Mercury will provide High Performance Computing engines

Architecture development will be done using an open development approach

Initial framework is available to the Openwings community

22© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5

SummarySummary

If submarines are to become full players in network centric warfare, then accessing and exploiting all available data sources will become essential

We are performing groundwork to show Mercury’s computers can meet these requirements Conducting data processing requirements analysis

and preparing demonstrations

These tools could be used for sonar data exploitation as well.