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Promise of Spectral and Signatures Understanding. Todd Hawley Sean Acklam (SpecTIR) Technical Director Signatures Technology Fellow National Signatures Program National Signatures Program. Real Life Applications. Promise of Spectral. New sensor systems Novel spectral analysis

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promise of spectral and signatures understanding

Promise of Spectral and Signatures Understanding

Todd Hawley Sean Acklam (SpecTIR)

Technical Director Signatures Technology Fellow

National Signatures Program National Signatures Program

promise of spectral
Real Life Applications Promise of Spectral
  • New sensor systems
  • Novel spectral analysis
  • Geo-database population
  • Imagery fusion
  • Information visualization

Todd Hawley

bio mass material discrimination study
Hyperspectral data enables automated identification of roof types including discrimination of red asphalt shingles from terra cotta roofs.

Combined

Density Map

Natural RGB

Wildland Vegetation Density Analysis

(determine fuel availability for wildfire and vegetation types)

Bio-Mass / Material Discrimination Study

Todd Hawley

wetlands
Principal Component - Unsupervised Classification

Forested Wetlands – MD Eastern Shore – February 2006

Wetlands

Todd Hawley

geologic energy
Geologic/Energy
  • Mineralogy
  • Geothermal
  • Oil/gas exploration
  • Mining remediation

Todd Hawley

superfund site
Superfund Site

Todd Hawley

land use
Land Use
  • Forest fire projections
    • Fuel abundance mapping
  • Invasive species
  • Land cover/land use
    • Nutrient value
    • Agriculture/stock
    • Urban mapping
    • Impervious surfaces

Todd Hawley

ag site in mid west
AG Site in Mid-West

0.5 meter spatial

5 nm spectral

Mosaic of two lines

Todd Hawley

road analysis results
Correct: half of road is degraded

Correct: Recently paved

Correct:

Moderate road with slight cracks

Correct:

Severely degraded road

Road Analysis Results

Todd Hawley

SpecTIR Proprietary

hsi lidar integration
Adding unique elements of hyperspectral imaging and material classification…

…to LIDAR-derived topographic, very high resolution topographic information, yields unprecedented level of terrain information

HSI & LIDAR Integration

Todd Hawley

hsi lidar integration1
Paved Asphalt / Gravel (Lots)

Paved Asphalt (Streets)

Tar Roof

Vegetation

Sandy Soils

Metallic Roofs

HSI & LIDAR Integration

Todd Hawley

natural disaster
Natural Disaster

Preliminary analysis of spectral anomalies associated with hurricane damage.

Todd Hawley

paper industry
Near InfraRed (NIR) spectral camera together with multiple fiber optics is used to acquire snaphot moisture profiles across paper web in paper machine.Paper Industry

Todd Hawley

textile dyeing
A four-point fiber optic spectrometer measures dyed color at a resolution of <0.2 DE.

Pictures: Coltex system by Iris DP

Textile Dyeing

Todd Hawley

pharmaceutical industry
Pharmaceutical Industry
  • NIR spectral imaging expands the capabilities of single point near infrared spectrometry to fully cover the material and product streams under inspection
    • Inspection of chemical composition and its homogenity
    • Detection of foreign pills

Todd Hawley

gdb product examples
GDB Product Examples

Airfield Products

3\4 Dimensional Products

Hydrological Products

  • Airfield threat assessments
  • Airfield line diagrams
  • Airfield graphics
  • Airfield image maps
  • Landing zones
  • Helicopter landing zones
  • 3D visualization
  • 3D flythroughs
  • Elevation tints
  • Line of sight/intervisibility
  • Anaglyphs
  • Viewsheds
  • Interferomograms
  • Foliage penetration
  • Time sequencing
  • Video feeds
  • Littoral studies
  • Threat predictions
  • Predictive modeling
  • Damage assessments
  • Turbidity
  • Ports of entry
  • Beach landing zones

Todd Hawley

gdb product examples1
GDB Product Examples

Engineering Products

Domestic Security

Earth Sciences

  • Power distribution
  • Water distribution
  • Sewage distribution
  • Petroleum distribution
  • Utility isolation
  • Damage assessments
  • Threat prediction
  • Lines of communication
  • Communication studies
  • City construction/public works
  • R&S reporting graphics
  • Key infrastructure
  • Trends & tactics
  • Predictive modeling
  • Threat predictions
  • Damage assessments
  • Crowd control
  • Event security
  • Dignitary security detail
  • Raid graphics
  • Geological studies
  • Vegetation studies
  • Environmental hazards/impacts
  • Terrain categorization
  • Littoral studies
  • Geophysical studies

Todd Hawley

gdb product examples2
GDB Product Examples

Orientation Products

Mobility Products

  • Route analysis
  • Road isolation
  • Choke points
  • Bridges/ ford/ tunnel studies
  • Trafficability
  • Traffic Rate
  • MCOO/ COO
  • Route studies
  • Urban – orientation
  • City graphic
  • City image map
  • Targeting map
  • Gridded matrix
  • Geo – orientation
  • Change detection

Todd Hawley

network analysis
Network Analysis

Todd Hawley

data fusion
Wavelet Transform

Input Data

Fusion Rule

Inverse Wavelet Transform

Wavelet Fusion Tool: The wavelet fusion tool developed for the STF transforms any geographically linked data into wavelet space (sparse transformation) thereby decorrelating their coefficients, applies a fusion rule to the transformed data sets (dependent on internal geometry), and performs an inverse wavelet transformation on the newly fused datasets. The outcome is a fused dataset independent of wavelength and platform.

Data Fusion

Todd Hawley

data fusion1
Independent Component Analysis Tool: The ICA tool uses fused data and transforms into a space where components within the datasets can be isolated for statistical independence from the rest of the dataset. Non independent data like Gaussian noise is “ignored” through the use of negentropy approximations as opposed to kurtosis during the transformation process. These independent components (or vectors) act as unique and accurate signatures for any future classification and feature extraction. Data Fusion

Todd Hawley

data fusion2
Generalized Relevance Learning Vector Quantization Tool: The GRLVQ tool is a hybrid classification driven feature extraction that uses the input independent components to classify, discriminate and\or identify features of interest and extract the features into a geo-database as a geographic information system. The final geo-database format, containing all inclusive signatures of the urban area of interest, can be used for a wide variety of analyses and products.Data Fusion

Todd Hawley

information visualization
Three Modules for Information Visualization: Three modules define the signatures visualization tool. The first module is data input from the absolute geometric database. Data is represented in the form of clouds and is categorized via six different relationship types. These data clouds are projected using the second module made up of four axes depicted below. Finally, collection gaps and complete signature coverage are visualized by depicting collection asset coverage over the data clouds projected using the four axes.

Temporal

Wavelength

Energy

Axis:

Spatial

Unit:

Meters

Nanometers

Time

J\GHz

Information Visualization

Todd Hawley

signature visualization tool exemplar
Data relating to any sensor\observable\event can be loaded into the SVT through XML. Signature Visualization Tool (Exemplar)

Axis

Temporal

Spatial

Wavelength

Energy

1.

2.

3.

4.

Data

Signatures

Spectral Signatures

Behavior Signatures

RADAR Signatures

TTP signatures

IR Signatures

Todd Hawley

national signatures program
Broad-based program

to improve signature management & application

Web-Based

Operation

Multiple

Providers

Users

Spectral Infrared

Diverse

Signatures

Secure Networks

Infrared

Radar Data

Acoustic Data

National Signatures Program

What is

NSP?

Platform for analysis & decisions

Multi-community participation

Unified access to diverse, distributed signatures

Operation on classified networks

What Does

NSP Provide?

Defense Intelligence Agency

National Ground Intelligence Center

Data providers

Senior steering group

Who are Key

Players?

Todd Hawley

signatures
Spectral Infrared

Infrared Image

Radar Data

Acoustic Data

Signatures
  • Features characterize targets, threats, …
    • Unique, consistently reoccurring
  • Multiple signature domains
    • Traditional (radar, radio frequency, electro-optical, geophysical, nuclear, materials)
    • New domains (e.g., chemicals)
  • Multiple data types
    • Measurements, computational predictions
    • Spectral, time series, images, etc.

Todd Hawley

objective
Improve signature management and application by balancing data users’ and providers’ needs.Objective
  • User perspective
    • Simple to use one stop shopping
    • Common view of the nation’s signature pool data
    • Clear, definitive search results
    • Downloadable real data
  • Provider perspective
    • Provide data quickly & efficiently to many users
    • Maintain visibility as the source for hosted data
    • Control data content and quality
    • Define and control data access

Todd Hawley

national signature pool
Data Need

Test & Evaluation

Operations

Intelligence

Modeling & Simulation

Other US Government

NSP

NSP

Domain

Radar

IR

Acoustic

Chem

etc.

Bio

Aircraft

Vehicles

Target

Ships

Facilities

Provider

Provider

Provider

etc.

Acoustic

Radar

Chemical

Biological

IR

Seismic

MS/HSI

Vehicles

Ships

Aircraft

Facilities

Mat’ls

etc.

Chem’s

National Signature Pool

User

Communities

Multiple Providers

Common View

National

Signature Pool

Todd Hawley

operational overview
Data Summary

Target

Data

Location

Date

XYZ

IR

A

6/1/01

John Doe

123-123-1234

POC

File

Download

Community Wide

Metadata

Data

Set

Spect.

etc.

Target

X

1

12

R

A

xxx

8-12

xyz

Y

2

5

S

yyy

3-5

3

Z

zyx

X

T

B

4

X

U

3

X

yxz

zzz

C

xxx

3-5

xyz

C

NSP

Common

Data

Tgt

DC

Spct

etc.

Descriptions

Thumbnail Images

File Downloads

(Metadata)

(when available)

(Signature data)

Operational Overview

NSP

Web-Based

Application

NSP

Find

Signature Providers

Results

Users

Local

Database

Dynamically Generated

XML Data Summaries

Local

Metadata

Retrieve

Metadata

Files

Signature

Files

Data Location/Retrieval

Data Loading

Todd Hawley

key components
Dynamic signature operations: immediate on-demand access to all sources of quality assured standardized signatures and related data maintained with DOD, IC, and OGA to support sensor reprogramming in a highly fluid environment

Signature support plan (SSP): Potential observable signature types associated with each critical element of an activity, event, or equipment withing a specific mission area

Operational signature package (OSP): End user defined selection of operational signatures, their specific ordered integration, and the desired time sequencing required to support a specific mission area

Signature Based

Direct Reporting

Machine-to-Machine

Signature Exchanges

Signature Based

Tip-off/Cross Cueing

Key Components

Todd Hawley

ssp osp development
SSP/OSP Development
  • Gather information
    • Identify friendly aircraft signature requirements
      • Sensor and technique used
      • Required signature fidelity and format
    • Check existing signature holdings
  • Draft
    • Sensor specific, enemy aircraft OSP
      • Add required signatures to NSP holdings, or
      • Generate requirement for needed signatures
    • Incorporate into air engagement SSP
  • Finalize
    • User validation/review
    • Assess signature support

Todd Hawley

estimation environment
Modeling & simulation (M&S) tools to estimate signatures for environments and collectors not specifically available in NSP measured signature holdingsEstimation Environment

NSP Customer Communities

NSP Distributed Signature Modeling Centers

NSP Distributed Signature Data Centers

Modeled Signature Holdings

Measured

Signature Data Holdings

Todd Hawley

visualization tool
Gaps

Platform

Sensor

Location

Coverage

Phenomenology

Visualization Tool

Signatures data relating to any collections asset can be

loaded into the signatures visualization tool

Todd Hawley

gap identification
Optimized Signatures

Gaps

Energy

Current Collection Architecture

Spectral

Temporal

Spatial

Lower weighted

Relevant

Background

Gap Identification

Todd Hawley

summary
Summary
  • Target and background signature understanding is vital to achieve the promise of spectral technologies
  • NSP is a one-stop federated signatures and signature data source
  • To be versatile, signature data must be
    • Measured
    • Integrated
    • Accessible by analysts and developers
  • NSP is ready to accept, integrate, and provide relevant signature data

Todd Hawley

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