Stanley Chan, the Elmore Professor of Electrical and Computer Engineering, is leading a team of PhD students in the CIDAR Challenge

A Purdue University team is changing how distance is measured with ordinary cameras.

Stanley Chan, the Elmore Professor of ECE, and a team of PhD students led by Bole Ma in the Elmore Family School of Electrical and Computer Engineering have advanced to the semifinal round of the DARPA Computational Imaging Detection and Ranging (CIDAR) Challenge.

The team earned $200,000 for their winning white paper submission and an additional $50,000 for advancing to the semifinal stage. Participating teams now have until April to analyze a new set of images.

The CIDAR Challenge tackles a major goal: accurately measuring distance using only passive imaging. Instead of using lasers or emitted signals like LiDAR, CIDAR extracts precise distance data from the light captured by cameras. CIDAR uses AI and computational imaging to extend passive range measurements up to 10 km, ensuring results stay quick and efficient. That combination matters. High accuracy paired with low latency, meaning results are produced quickly with minimal computing power, could enable new capabilities for both tactical and civil applications, from sensing and navigation to surveillance and environmental monitoring.

“This challenge is about pushing passive imaging beyond what’s possible today,” Chan said. “We are aiming to understand the fundamental limits, and from there we develop faster and more efficient sensing systems for both civil and defense applications.”

Up next is the final round of the challenge, where all remaining teams will tackle a fresh set of images. The first-place team will win $1 million, the second-place team will win $600,000, and the third-place team will win $400,000.

Through the CIDAR Challenge, DARPA is exploring how computational imaging, machine learning, and AI can reveal new ways to observe and measure the world without active sensors.