January 29 - 31, 2020 | Hilton Alexandria Mark Center, Alexandria , VA

Main Day Conference 1

January 30, 2020

8:00 am - 8:50 am Registration and Morning Networking

8:50 am - 9:00 am Chairman Opening Remarks

This lecture will provide an overview of fully adaptive radar processing from the standpoint of bringing to bear optimally and adaptively, all available degrees of freedom on transmit and receive to address the problem of detection, tracking, and classification from a single as well as a multi-sensor perspective. The idea of closed loop radar processing will be introduced. Pertinent research challenges will be identified and ameliorating solutions will be discussed. Important issues of training data heterogeneity, computational cost, waveform optimization and design as well as joint transmit-receive adaptive processing will be addressed. 

-Swap-C considerations
-Technology needs to bolster closed loop rdar processing
-Sensor development needs 


Muralidhar Rangaswamy, PhD, Fellow IEEE

Technical Lead for Radar Sensing
Air Force Research Laboratory Sensors Directorate, AFRL/RYMD

9:45 am - 10:30 am The US Combat Capabilities Development Command ARL's Radar Advancement in Support of the Army Modernization Priorities

Brian Phelan, PhD - Senior Electronics Engineer, Army Research Laboratory
The Combat Capabilities Development Command Army Research Laboratory is testing the “art-of-the-possible” with a scaled-down version of today’s massive antenna element radar arrays. They’re focused on developing a low-SWAP and low-cost radar testbed to couple with new signal processing techniques in an effort to combat degraded visual environments (DVE) for helicopter navigation and landing. The envisioned radar concept relies heavily on the platform motion and signal processing power to deliver a 3-D imaging capability at a fraction of the SWAP of multi-element radar arrays. In order to meet resolution requirements, the radar must operate in the millimeter-wave regime, the initial testbed is planned to operate at Ka-band which necessitates that special care be taken to account for inertial measurement errors. If successful, ARL will transition the technical details of these radar modes in hopes that they can be further developed and eventually used on future vertical lift (FVL) platforms.

Brian Phelan, PhD

Senior Electronics Engineer
Army Research Laboratory

10:30 am - 11:15 am Networking Break and Demo-Drive

11:15 am - 12:00 pm DoD Actions to Facilitate Spectrum Sharing

Frederick Moorefield - Acting Principal Director to the Deputy CIO for C4IIC, DoD CIO
In order to align the Government's R&D and T&E efforts in the spectrum arena, the White House, DoD CIO and Commerce Department have worked hand in hand to develop the first National Spectrum Strategy. This spectrum-sharing strategy requires collaboration at the highest level between Federal agencies and industry, highlighting a need to define clear spectrum utilization strategies for today and the future.

- Framing the Warfighter IT environment: managing multiple systems, devices and networks
- Spectrum sharing and repurposing activities
- DoD 5G contributions and its impact on Military operations


Frederick Moorefield

Acting Principal Director to the Deputy CIO for C4IIC

11:45 am - 12:30 pm Echodyne Sponsored Speaking Session

Tom Driscoll - Co-Founder & CTO, Echodyne

Tom Driscoll

Co-Founder & CTO

12:30 pm - 1:30 pm Networking Lunch

1:30 pm - 2:15 pm Shadow Exploitation in Synthetic Aperture Radar

Ann Marie Raynal, PhD - ISR Analysis & Applications, Sandia National Laboratories
Radar shadows can be more intuitive for target detection, location, tracking and shape observation than other target traits due to human visual perception preferences, but these characteristics depend on many factors. This session will provide an overview of shadow enhancement and exploitation methods.

- Shadow advantages versus traditional radar observables
- Synthetic aperture radar product shadow detection challenges
- Shadows for radar performance testing

Ann Marie Raynal, PhD

ISR Analysis & Applications
Sandia National Laboratories

2:15 pm - 3:00 pm Developing, Acquiring, Fielding and Supplying Life-Cycle Support for Aerial ISR Sensors

Christian Keller - Project Manager, Sensors Aerial Intelligence, PEO IEW&S
The Product Director for Sensors Aerial intelligence aims to deliver the Army’s premier AISR sensors, enabling timely dissemination of intelligence products to meet current and future Warfighter needs. The massive utilization of sensors across the Force point to an upending effort to provide improved battlespace awareness. 

-Technological needs to bolster aerial intelligence, surveillance, and reconnaissance
-Enabling critical processing, exploitation and dissemination of sensor operations
-Programs and initiatives of interest


Christian Keller

Project Manager, Sensors Aerial Intelligence

3:15 pm - 3:45 pm Afternoon Networking Break

3:30 pm - 4:15 pm Beyond the Radar Archipelago: A New Roadmap for Missile Defense Sensors

Thomas Karako - International Security Program and Director, Missile Defense Project, Center for Strategic and International Studies
The expansion of long-range missile defense sensors over the past 16 years has, with some exceptions, been nearly synonymous with a gradual increase of large, surface-based radars. Adapting today’s sensor architecture will be one of the most critical steps to reorient U.S. missile defenses to the complex realities of air and missile battle.

- Prioritizing a space-based sensor layer for persistent, birth-to-death tracking and discrimination
- Enhancing survivability of sensor architectures
- Challenges of over reliance on RF for communication, command, and control

Thomas Karako

International Security Program and Director, Missile Defense Project
Center for Strategic and International Studies

4:15 pm - 5:00 pm Compressive Object Tracking and Classification Using Deep Learning

Trac Tran, PhD - Professor, Dept. of Electrical and Computer Engineering, The Johns Hopkins University
This session presents a deep learning approach that directly performs target tracking and classification in the compressive measurement domain without any frame reconstruction. The approach has two parts: tracking and classification. Efforts to combine deep learning across military applications has a high utilization capacity, one that could drastically alter conventional radar operations.

-       Deep learning initiatives to improve tracking and classification of objects
-       Efforts to improve collaborative multi-sensor classification
-       Efforts to bolster compressed sensing, sparse recovery, and sparsity-based signal processing 

Trac Tran, PhD

Professor, Dept. of Electrical and Computer Engineering
The Johns Hopkins University

5:00 pm - 5:15 pm Chairman Closing Remarks

5:15 pm - 5:15 pm Post-Conference Networking