NUAIR Deploys CAL Analytics Detect and Avoid Service and CMP in NY’s 50-mile Drone Corridor
by DRONELIFE Staff Writer Ian M. Crosby
Autonomous systems leader CAL Analytics will be incorporating its proprietary detect and avoid (DAA) service and contingency management platform (CMP) into New York’s 50-mile Drone Corridor. The Drone Corridor, operating out of Griffiss International Airport in Rome, NY and managed by NUAIR, is one of seven uncrewed aircraft systems (UAS) test sites designated by the Federal Aviation Administration (FAA). The organizations are collaborating on a Technical Assistance program with the FAA in order to establish a DAA service for use in low-altitude beyond visual line of sight (BVLOS) UAS operations.
Under current regulations, drone operators are required to maintain visual contact with the aircraft they are flying at all times, presenting a major obstacle for long distance flight operations. DAA systems are a necessity in circumventing this issue, and require the ability to detect and avoid obstacles both in the air and on ground, all without visual sight of the drone. The availability of safe BVLOS solutions is essential to utilize the full potential of routine commercial drone operations in use cases such as medical and package deliveries.
“This upgrade to the 50-mile Drone Corridor between Rome and Syracuse will help integrate detect and avoid technology to further the safe advancement of unmanned aircraft systems into the national airspace and unlock the true potential of commercial drone operations,” said Oneida County Executive Anthony J. Picente Jr. “We look forward to the fruit of this partnership between CAL Analytics and the FAA will bear at Oneida County’s Test Site, which continues to flourish under NUAIR’s management.”
As CAL’s newest UAS traffic management (UTM) service, the DAA service builds off their existing contingency management platform (CMP), which offers a range of UTM services. CAL’s CMP will provide essential airspace services for the guarantee of safe UAS operation, such as situational awareness from Kongsberg, conflict detection from CAL, health monitoring by ResilienX, and an assortment of weather services from TruWeather Solutions.
“We’re excited to partner with NUAIR and working directly with the FAA to get our DAA service approved for small UAS,” said CAL Analytics managing director Dr. Sean Calhoun. “This will go a long way towards validating several of the DAA standards, including those from ASTM-F38 and RTCA SC-147, and opening the skies for safe BVLOS drone operations.”
CAL’s solutions will grant several major services for the allowance of safe BVLOS operations within New York’s 50-mile UAS Corridor, which will be conducted by NUAIR.
“One of the most important recommendations from the recent BVLOS Aviation Rulemaking Committee was for the FAA to develop a methodology for approving safety-critical UTM services for BVLOS,” said NUAIR CTO Andy Thurling. “NUAIR is working with our partners at CAL Analytics and the FAA to do just that.”
CAL Analytics, alongside NUAIR, ResilienX, TruWeather Solutions and other partners, will be demonstrating the latest in their technologies and advancements at the upcoming AUVSI XPONENTIAL conference in Orlando, Florida, April 25-28, at the GENIUS NY booth #1761.
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Ian attended Dominican University of California, where he received a BA in English in 2019. With a lifelong passion for writing and storytelling and a keen interest in technology, he is now contributing to DroneLife as a staff writer.
Miriam McNabb is the Editor-in-Chief of DRONELIFE and CEO of JobForDrones, a professional drone services marketplace, and a fascinated observer of the emerging drone industry and the regulatory environment for drones. Miriam has penned over 3,000 articles focused on the commercial drone space and is an international speaker and recognized figure in the industry. Miriam has a degree from the University of Chicago and over 20 years of experience in high tech sales and marketing for new technologies.
For drone industry consulting or writing, Email Miriam.
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