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MIE Assistant Professor Martinez-Lorenzo Award NSF CAREER Award for Fast 4D Imaging System
MIE/ECE Assistant Professor Jose Martinez-Lorenzo awarded $500K NSF CAREER Award for “4D mm-Wave Compressive Sensing and Imaging at One Thousand Volumetric Frames per Second”.
Jose Martinez-Lorenzo, assistant professor of mechanical and industrial engineering, jointly appointed in the Department of Electrical and Computer Engineering, of Northeastern University's College of Engineering, was recently awarded a $500K National Science Foundation (NSF) CAREER Award for his work on developing a method for “4D mm-Wave Compressive Sensing and Imaging at One Thousand Volumetric Frames per Second.” Millimeter-wave sensing and imaging systems are generally used for a wide range of applications, such as security monitoring to detect potential threats at the airport and biological imaging for wound diagnosis and healing. Because this is the first four-dimensional millimeter-wave imaging system that can operate in quick-changing scenarios, it will benefit society greatly.
One of the main applications of this system is finding security threats hidden under clothing, inside backpacks, or in public spaces, such as sports arenas. The system can scan multiple people within 26 cubic meters and produce 1000 3D image frames per second. This far surpasses existing millimeter-wave sensing and imaging systems.
Despite the efficiency of this system, there are still some challenges to overcome. This project will look to address these challenges and ideally, the results of this research will establish the scientific basis for the proposed new sensing and imaging systems, by enhancing the imaging performance, reliability, and efficiency while reducing the hardware complexity, overall cost, and energy consumption of the system.
Additionally, Professor Martinez-Lorenzo will develop an educational program that combines classroom learning with research training methods to help students understand the principles and limitations of wave-based imaging. This educational program will also collaborate with the Northeastern University Cooperative Education and Career Development Program to transition students into industry and the Northeastern University Center for STEM Education to provide valuable research experiences for K-12, undergraduate, and underrepresented students, as well as education through online materials and public venues.
Below is the abstract from the NSF.
Millimeter-wave sensing and imaging systems are used ubiquitously for a wide range of applications, such as atmospheric sounding of the earth to forecast the weather, security monitoring to detect potential threats at airport checkpoints, and biological imaging of superficial tissues for wound diagnosis and healing. These systems typically operate well when the scene dynamics do not change rapidly. Unfortunately this is not the case in emerging societally-important applications like swarms of drones in rescue missions, smart self-driving cars on roadways, or cyber-physical systems searching for suicide bombers when they are on the move. This project will benefit our society with the development of the first four-dimensional (4D) millimeter-wave imaging system operating in fast changing scenarios, in which safety-critical decisions must be made quickly. One of the new applications of this system will be finding security threats, concealed under clothing or inside backpacks, in open areas like shopping malls, sport venues, and office buildings. Specifically, the system will have the capability to scan multiple people moving within a volumetric region of 26 cubic meters, producing 1000 image frames per second in three dimensions, thus outperforming existing millimeter-wave sensing and imaging systems that are currently used at airport checkpoints. In addition to the societal impact, the Principal Investigator (PI) will build a strong educational program through which diverse audiences can understand the principles and limitations of wave-based imaging systems. The integration of research and education will be accomplished through the development of new curricula and research training methods for students, as well as through the elaboration of a roadmap for transitioning students into industry, in collaboration with Northeastern University (NEU) Cooperative Education Program. The outreach plan includes enabling research experiences for K-12, undergraduate, and underrepresented students in collaboration with the Science, Technology, Engineering, and Mathematics (STEM) centers at NEU, as well as education through online materials and public venues.
The research goal of this CAREER program is to understand the theoretical principles and fundamental limitations of adaptable compressive sensing and imaging systems using 4D (temporal and spatial) coding and to develop and experimentally validate these principles through a novel 4D millimeter-wave adaptive compressive imaging radar system. This system will produce 4D volumetric frame rates beyond 1000 frames per second, each frame having over one million pixels. The primary challenges of implementing 4D adaptable imaging systems are the following: 1) the system must be capable of handling variable dynamics, i.e., objects moving with different velocities and located at different focal ranges; 2) the system must sample data with sufficient signal to noise ratio during the limited period of time; and 3) the system must sample data extremely fast to perform fast 4D video reconstruction with high volumetric frame rates. This project will address these challenges as follows: (i) it will develop a new theory that brings together functional analysis, information theory, compressive sensing, and adaptable metamaterials to enhance the information transfer efficiency of sensing systems; (ii) it will develop a new mathematical framework to optimize 4D codes based on the desired information rate and energy efficiency of the compressive imaging system; and (iii) the system will utilize spatial light modulators, vortex-meta-lenses, and compressive reflectors to perform the coding and to dynamically adapt to the state of the imaging region. The result of this research will establish the scientific basis for the proposed new sensing and imaging systems, by enhancing the imaging performance, reliability, and efficiency while reducing the hardware complexity, overall cost, and energy consumption of the system.