Lawrence-based Ainstein zeroing in on success

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Ainstein’s ULGB-D1 is optimized for ground-to-air drone detection and monitoring.

Ainstein, a Midwest startup with global ambition, aims to make radar solutions smarter, more affordable, and easier to deploy.

Lawrence, Kansas-based Ainstein, a leader in intelligent radar systems, was honored in October at the Commercial UAV Expo in Las Vegas for drone technology innovation. Ainstein’s Long Range Drone Radar Altimeter (LR-D1) was recognized as one of the top ten most innovative products at the Expo, nominated by a select group of industry media representatives at the show.

The LR-D1 is a low-cost, high-performance millimeter wave (mmWave) radar altimeter designed to enable safe takeoff and landing for advanced UAVs, manned helicopters, and other aircrafts. Built to withstand rugged environments, the LR-D1 continuously monitors incoming data, assuring the measured altitude is accurate, even in low-visibility conditions up to 1,640 feet. The LR-D1 is part of a radar altimeter offering that also includes Ainstein’s US-D1 altimeter, the smallest and lightest radar altimeter on the market at under 60 grams.

Founded in 2015 by Zongbo Wang, Ainstein develops AI radar systems-based drone detection systems designed to protect valuable assets and enable safer driving, flying, working, and living. Dr. Wang also founded Aerotenna in 2015. Aerotenna has been well recognized as the leading innovators in developing the first commercially available collision-avoidance radar, radar altimeters and FPGA-based flight controllers for UAS.

Dr. Wang talked to SPN about his motivation for starting Ainstein. He served as a research professor at the Center for Remote Sensing of Ice Sheets (CReSIS) at the University of Kansas from 2013-2015. Dr. Wang is a researcher and professor who specializes in radar systems, remote sensing, and imaging system design. He has over fifteen years of experience in sensor and electronics development. He has led numerous large-scale UAV-borne and air-borne research projects at universities and research institutes in the United States, China, Singapore, the Netherlands, and Spain. He has more than 40 scientific publications and patents in the areas of radar system, signal processing, remote sensing, embedded system and flight control system design.

Dr. Wang realized the many potential commercial applications of radar systems technology, and said he’s pleased by the many gains the company has had since he started it three years ago.

For example, the company announced two new products in its Ultra Long Range UAV radar series; the Ultra Long Range Airborne (ULAB-DA) and Ultra Long Range Ground-Based (ULGB-D1) radars, capable of precise detection more than 1,000 meters away. These tools are designed to provide a highly precise and cost-effective solution to minimize disaster risks and keep assets and classified information safe. Applications include high-security facilities, such as government buildings and airports, or critical infrastructure, such as water treatment facilities and mass transit systems.

The company leverages radar technology in order to offer products and solutions that are more affordable, and easier to deploy. Ainstein offers complete customized solutions for autonomous drones, advanced driver-assistance systems (ADAS), autonomous vehicles, and industrial sensing – incorporating a combination of mmWave radar, sensor fusion and artificial intelligence (AI) technologies.

Dr. Wang is optimistic about what he sees as a very bright future for the industry. He said he predicts expanding development of drone technology will bring a great deal of value to a variety of industries in the coming years, and particularly in aviation as a whole.

Dr. Wang said that Ainstein will continue to work with partners to develop custom drone detection radar systems; Ainstein is also developing other radar solutions with applications in autonomous vehicle operation (collision avoidance), as well as indoor radar sensors that can sense people while being non-invasive (sensing, not identifying), with applications such as security and crowd monitoring and control.

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