Northrop Grumman Fall Student Challenge 2021 – Multiple Maritime Target Optical Tracking

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Information Session

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Agenda• Introduction to Northrop Grumman• Challenge Description• Schedule• Administrative• Resources• Meet and Greet

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Northrop Grumman Today

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Leading global security company

$36.8 billion sales in 2020– 86% U.S. / 14% International

$81 billion total backlog(as of Dec. 31, 2020)

~97,000 employees

Leading capabilities in:– Space– Missiles– Advanced Weapons

Focus on Growth and Performance

– Aeronautics– Mission Systems

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Four Operating Sectors at a GlanceMission Systems

Airborne Sensors and Networks

Artificial Intelligence/Machine Learning

Cyber and IntelligenceMission Solutions

Navigation, Targeting and Survivability

Maritime/Land Systems and Sensors

Engineering & Sciences

Emerging Concepts Development

Multi-domain C2

Agile/DevSecOps Systems

Autonomous Systems

Aerospace Structures

Advanced Technologies and Concepts

Aircraft Design, Integration and Manufacturing

Long-range Strike

Multi-Domain Integration and Operations

Intelligence, Surveillanceand Reconnaissance

Battle Management

Aeronautics Systems Defense Systems

Integrated Air & Missile Defense

Defensive Cyber and Information Operations

Platform Modernization and Fleet Operations Support

Advanced Weapons

Precision Munitions

Software Systems Modernization and Sustainment

Training and Simulation

Propulsion Systems

Space Systems

Launch Vehicles

Propulsion Systems

Commercial Satellites

Military and Civil Space Systems

Science and National Security Satellites

Human Space and Advanced Systems

Space Components

Missile Defense

Space Exploration

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Northrop Grumman Today

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Challenge Background• Sensors of all types depend on target tracking to keep a history of and predict

future movement of a target- Radar Trackers for Aircraft and Ship movement- Acoustic trackers for undersea wildlife and submarines- Optical trackers for camera systems

• Target trackers come in many types- Kalman Filter Target Trackers- Machine Learning Tracker models- Alpha Beta (known also as f-g) Radar Detection/Object tracker

• Multiple Optical Target Tracking is a non-trivial task- Image occlusions and reflections- Multiple angles of a detected target

• Challenge – create a target tracker to keep track of multiple ships in a video

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Challenge Description

• The task will be performed using MATLAB (and available toolboxes) or Python (and publicly available toolboxes)

• The teams will be given a catalogue of training data that simulates real world data- Video files, defined resolution and frame rates – Up to 20 ships per video

• An in depth explanation and materials regarding Image processing concepts will be given in order to help teams – no target tracking experience is required

• Teams of two to four undergraduates may apply to compete

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Competition Overview• Create an application that can identify, keep track of, and classify vessels in a

scene- Keep an accurate frame by frame catalogue of maritime vessels- Classify into Civilian Vessel, Warship, Aircraft Carrier, Submarine

• Project Deliverables:- Application to test in real life test- Processing block diagram and report- Final Presentation (10 mins. w/ Q&A)

• Resources- MATLAB/Python Image processing and target tracking toolboxes- UMD Mentor- Northrop Grumman Mentor- Short Course and Resources related to Image Signal Processing and Target Tracking

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Preliminary Schedule

All Events will be Virtual (Zoom)

September 21, 23, & 28 Info Sessions

October 04 – Applications Due (11:59 PM)

October 07 – Kickoff

October 22 – Mentor Midpoint meeting

November 5 (11:59PM) – Applications and Presentations Due

November 11 – Exposition

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Judging and ScoringTwo aspects of the competition:• (70%) Real life test: Teams will test their app in a real world test

- We will test each team’s applications versus videos of real life maritime traffic- Points will be given for correctly identifying and keeping track of each vessel for

>90% of the frames that they are in- Additional Points will be given for correctly identifying type of vessel (only must be

done once during time vessel is in the footage)

• (30%) Innovation and Presentation- Teams will give a presentation to the Judges outlining their signal processing

architecture and techniques- Points will be awarded for innovation, ingenuity, and overall technical achievement- UMD Judge Tom Goldstein Associate Professor of Computer Science - Northrop Grumman Judge Paul Ledbetter, Director for Mission Engineering and

System Architecture

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Mentoring

• Each team will be assigned a Northrop Grumman mentor- Suggest a teleconference every 2 weeks, email/informal call in between

• Ways your mentors can help:- Provide insight into Northrop Grumman business/application areas (Northrop

Grumman mentor)- Provide feedback on designs or technical questions- Discuss common design considerations

• Feeling stumped? Ask your mentor!

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