Surveillance is Sensor Networking

1. Surveillance is Sensor Networking • Without Flexible on-demand use of Spectral Band, we operate ‘Blind’ • We support Intelligent Spectral Allocation • FY05 “Waveform Diversity” in the Pipeline

2. Waveform Diversity and the RF Spectrum Issue • Optimize Waveforms adaptively for Multi-Mission Operations • Fullest Exploitation of Network-centric operations demand increased spectrum, but • Over 10 X overuse predicted: 255 MHz of DOD spectrum was lost in the last 10 years

3. Foundations of ATR • Feature – Enhanced processing takes into account key discrimination characteristics of target • “integrated” treatment of SAR data with HRR, LADAR, IR sensor input • Image Formation accentuates the target features that you seek • Combine physical models (scattering) with statistical models of reception • ‘structure of radar clutter as it affects detection has defied solution’

4. Mathematical Understanding disambiguates object identifications! • Fundamentals of hybrid optical sensing/sampling and communication • Exploit ultra-fast devices such as Terahertz Optical Demultiplexer (TOAD) • Functional decomposition of images adapted to geometry • Edgelets, ridgelets (local analysis) • Curvature-based methods (smooth geometry) • texture analysis (fractal geometry) • Under constrained spectral regimen in a multiple UAV environment, geometric diversity (tomography) enhances autonomous operation and battlefield awareness

5. Mathematical Understanding disambiguates object identifications! • “Geometric, Algebraic and Topological Structure for Signal and Image Processing” • New “derivation logic” : reasoning abut Target Articulation state • Pixel-Pair – enhance performance tied to geometrical invariance • MIMO, STAP and UWB techniques both in sensing and network information accessing • New Mathematical paradigm using L1 Norm: build in the proper importance to edges and image transitions • Trade off frame rate versus resolution, Low res video version high-res still shot • Achieve “super-resolution under limited bandwidth and storage capacity • Perform compression/reconstruction intelligently

6. Service EmphasisSurveillance and Communications • ARMY • Ad-hoc “Networks-on-the-Move” (Mobile comms) • Compact optical communicator (SpecOps) ‘Army of One’ concept • A comprehensive suite of night vision capabilities, helicopters, vehicles sensing • ‘Signature’ studies to find vulnerabilities, sensing needs for Urban Warfare • FCS Conception for Humvee: less Armor, greater mobility as comms node • AF • AFRL/SNR is getting involved in XG Spectrum management • 3-D sensing, processing at the ‘front-end’ • Integrated signature design and modeling, enhanced XPATCH • High confidence ID on articulated objects • Extend WSOA Flying Network-Centric Platform; CORBA Layer over legacy “Link-16” • Adaptive “Middleware” allows commercially developed communication protocols to be used for military applications. • NAVY • “Time Reversal” techniques in communications, originated from Sonar applications • Highly ‘network-centric’ orientation • Littoral sonar detection, coastlines and harbored in chaotic milieu, different from deep ocean • Defeat Camouflage, Concealment & Deception (C,C&D) events: shape-based reasoning on various parts of the object

7. SN – linked Activities other than ATR • MOU with DRDC (Ottawa) on EW - radar ID) tied to ACC EW Center (Eglin), JSF SPO • Fuselage antennas for GPS anti-jamming, transition to Predator SPO. • Control the radiation pattern of printed re-configurable GPS antennas • Lt.Col. Steiner (AFOSR/NE) launched a new Task at SNRR, transitioning the innovations of Rojas, likely move to AFOSR/NM (Sjogren)

8. QC with open network architecture Logical qubit LC resonant bus qubit M=0  no direct flux coupling between buses Qubit coupling to bus TYPE – IQuantum ComputerGlobally Coherent Quantum Control Big Questions (DiVincenzo): How to Read-Out a Qubit ? How to Initialize a Qubit ? Josephson Junction Network Tensor products of JJ circuits are the qubit elements connected by an LC resonant bus (quantum coherent bus) S. Yukon AFRL/SNHE

9. Vision-based Precision Navigation and Control • Track Optical Flow to find Ego-Motion • Location, Orientation and Velocity • Build up a 3-D “terrain” map , target environment: indoors, underground • Vision-based control reduces reliance on both IMU and GPS Sample Aerial Imagery with optic flow vectors

10. Analytical and Hardware Advances in GPS Protection • Sensing and communication platforms require multiple antennas to perform various functions • Reducing the number of antennas is important • Limited real state • Interference • Goal: Single antenna/array that can be reconfigured quickly • Switches: MEMS, Photonic, electronic E-plane pattern control, 1.227 GHz Antenna element with parasitic strips Adaptive Scheme 3

11. Fiscal Record • FY 2003 • Signals Communication/Surveillance $3.4 M 31 Projects • Quantum Computing (Mathematicakl Sciences) $.8 M 9 Projects • FY 2004 • Signals Communication/Surveillance $2.62 M 31 Projects • Quantum Computing (Mathematical Sciences) $.8 M 10 Projects

12. Extra Slides

13. Summary • AFOSR/NM“Signals Comms and Surveillance” plus “Data Fusion” concentration manages a focused program benefiting TD’s, SPO’s and national agencies to achieve ATR in our lifetime • Sparkplugsinter-Agency Initiatives, monitors and disseminates their progress • Researches Foundation Technologies for Critical Air Force Systems including Real-Time ATR • Fosters Transitions of Innovative Technologies • Earns its Reputation as “World-Class” through Early and Accurate Selection of Premiere Research Scientists

14. Sensing and Mathematical Methods • Colorado State Univ. (Kirby): Self-correlation of images, eigen-object analysis, manifold structures and dimensional reduction of data. • Rice University (Baraniuk): Multi-dimensional hypercomplex wavelet transform; rapid reconstruction of singularities. Opportunistic Sensing. • Rensselaer Polytechnic Inst. (Yazici): Methods of Representation of continuous groups including classical groups in design of digital filters. • Arizona State Univ. (Morrell/Cochran): Selection of sensing modality in the context of optimal decision-making for effective exploitation. • Colorado State Univ. (Scharf/Chong): Waveform coding, information-theoretic processing and target/environment modeling. [DARPA] • SUNY Buffalo (Soumekh): SAR return processing, full Sommerfeld interference model, exploitation of massive computation. [DURIP] • Geophex Inc. (STTR, $500K): Time Exposure Acoustics (Passive)

15. Quantum Computing • MIT (Cory): More numerous Qubits toward Type II QC • MIT (Orlando/Berggren): Optimization of SC Josephson Junctions for QC applications, problems of device matching, identical Q states. • Lincoln Laboratories (Oliver): Demonstrate Quantum entanglement with Superconducting JJ’s.

16. GPS and Navigation • Miami Univ. (Morton): Signal processing algorithms to enhance GPS. • Ohio State Univ. (Grejner): Geodetic GPS receivers, accurate INS, MEMs inertial measurement (IMU) and pseudolites [DURIP] • Ohio State Univ. (Rojas): Beam control for circularly polarized GPS receiving antenna. Control time-variability, frequency, polarization, with softward that adapts to enviroment.