The importance of sensor fusion is growing as more applications require the combination of data from different sensor inputs. Self-driving cars, radar tracking ...

Sensor fusion, which enables data analysis through the combination of several sensors, is being rapidly adopted in mobile designs such as smartphones, wearables, and internet of things (IoT) devices.

MathWorks’ Sensor Fusion and Tracking Toolbox helps engineers design, simulate, and analyze systems fusing data from multiple sensors. MathWorks’ Sensor Fusion and Tracking Toolbox helps engineers ...

First responder location determination therefore remains one of the most complex location applications in existence today. No one silver-bullet sensor can achieve the desired goals—instead, multiple ...

The US military has a combination of long-wave infrared search and track combined with high-speed multi-ship data networking and advanced sensor fusion algorithms for weapons quality tracking an enemy ...

As today’s internal-combustion engines are replaced by electric/electronic vehicles, mechanical-system sensors will be supplanted by numerous electronic sensors both for efficient operation and for ...

Environmental risk factors: ADAS sensors degrade under adverse weather and lighting conditions, reducing system reliability. Rain, fog, snow and glare can obstruct the camera and lidar’s fields of ...

Forbes contributors publish independent expert analyses and insights. I'm a South London-based technology journalist, consultant and author Two U.S. companies have partnered to demonstrate a new type ...

This video looks at track-level fusion, an architecture that provides advantages where access to data is an issue, where bandwidth is problem. where computing capabilities are limited, and where ...