D3 and RIT Awarded $60,000 Grant to Develop Concealed Object Detection Solutions

Editor Contact: Ellen Raffaelle, Marketing Manager (585) 429-1550 press@d3engineering.com

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Rochester, NY – November 2, 2021 – D3 Engineering is pleased to collaborate with Rochester Institute of Technology’s Machine Learning Optimization & Signal Processing Laboratory which has been awarded a grant from the NYSTAR Center of Excellence (CoE) in Data Science at the University of Rochester. This $60,000 grant will support the development of novel solutions for efficient radar imaging and machine learning for concealed object detection. This project will support D3 Engineering’s mission to develop transformative solutions for critical real-world object detection applications. It is yet another example of the long-term collaboration between D3 Engineering and RIT and promises to generate economic benefit for New York State.

“D3 Engineering is pleased to be working with Dr. Markopoulos and his team funded by this grant award. This technology advancement in portable Synthetic Aperture Radar for seeing inside packages and luggage will increase public safety, and has countless other applications for much higher resolution imaging than MIMO radar alone” said Tom Mayo, Product Manager for Spatial Sensors at D3 Engineering. “D3 Engineering is already a leader in providing many types of solutions with millimeter-wave radar, and this additional technology will allow D3 to assist product innovators in an even wider range of applications.” 

This project aims to develop efficient and portable solutions for concealed object detection based on Multiple-Input Multiple-Output (MIMO) radar technology, intelligent millimeter-wave Synthetic Aperture Radar (SAR) sensing/imaging, and machine learning. Concealed objects such as stolen goods, weapons, and explosives, hidden by an optically opaque cover or container, can be revealed with low power portable radar sensors. Detection of concealed objects has many critical civil and military applications, such as threat detection at airport security checkpoints. For such applications, metal detectors and x-ray imaging systems are extensively used today, but have limited practicality and can raise safety concerns. The use of synthetic-aperture radar methods employing MIMO millimeter-wave radar will resolve these limitations and significantly improve the detection of concealed objects, making the world a safer place. 

“We are thankful to the NYSTAR/UR CoE in Data Science for the award and to the D3 Engineering team for their eagerness to collaborate with us in this truly exciting project” said Dr. Panos Markopoulos, Director of Machine Learning Optimization & Signal Processing Laboratory at RIT. “In addition to advancing the state-of-the-art in radar-based imaging and object detection, this project will benefit NYS economy and give an outstanding opportunity to RIT students to learn through research, while solving important real-world problems.” 

About D3 Engineering  

D3 Engineering provides embedded electronic design services and original design manufacturing (ODM) products for original equipment manufacturers (OEM) in the industrial, transportation, infrastructure and commercial sectors. Using its proven DesignCore® Platforms and stage-gate development process, D3 Engineering helps its partners minimize the cost, schedule, and technical risks of new product development for performance-critical applications. D3 Engineering has expertise in autonomous machines, sensors, imaging, optics, edge computing, algorithms, robotics, and electrification. The company provides hardware design, firmware design, validation testing, transition to production, and ODM products. Learn more at www.D3Engineering.com.

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