Summary
The Computational Imaging Detection and Ranging (CIDAR) challenge aims to explore the potential of computational imaging tools and techniques to drastically enhance the accuracy of passive ranging for tactical and civil applications.
Unlike active systems that emit detectable laser radiation, passive approaches are undetectable, resistant to jamming, and safer for use in intelligence, surveillance, and reconnaissance and sense-and-avoid operations.
Challenge participants will leverage computational imaging, machine learning, and AI to develop algorithms capable of extending passive range measurements to 10 km or more with accuracy and low latency, rivaling active systems like light detection and ranging (LADAR) and laser rangefinder (LRF).
Current passive methods use only ~1% of the potential distance information in images, but advancements could improve accuracy by up to 10–100x through the integration of multi-filter optical data. This in turn could redefine range measurement by providing more accurate, undetectable, and efficient alternatives to active systems, enhancing both tactical and civil capabilities.
The CIDAR challenge will take place in three stages starting in early 2025: the white paper, the semifinal, and the final competition. Prizes will be given out along the way, with the top prize of $1 million awarded at the conclusion of the competition.