It appears that no particular approximate [nonlinear] filter is consistently better than any other, though . . . any nonlinear filter is better than a strictly linear one. 1 The Kalman filter is a ...

In configuring my Inertial Measurement Unit (IMU) for post-filtering of the data after the sensor, I see options for both a decimation FIR filter and also a Kalman filter. Which one is best for my ...

Kalman filtering has long served as a foundational tool for state estimation in dynamic systems, offering a robust and efficient means of filtering noise from measured signals. In the realm of ...

Fractional-order Kalman filtering extends traditional state estimation by incorporating fractional calculus, which enables the modelling of memory and hereditary properties in complex systems. This ...

If we are hiring someone such as a carpenter or an auto mechanic, we always look for two things: what kind of tools they have and what they do when things go wrong. For many types of embedded systems, ...

[Jcparkyn] clearly had an interesting topic for their thesis project, and was conscientious enough to write up a chunk of it and release it to the wild. The project in question is a digital pen that ...

Electric vehicles (EVs) have emerged as a promising trend for future development. Serving as the core energy source for EVs, lithium-ion batteries offer advantages. Accurate SoC estimation is vital ...

WASHINGTON -- The engineering profession's highest honors awarded in 2008, presented by the National Academy of Engineering (NAE), recognize a revolutionary contribution to the field of decision and ...

Distributed electric drive technology has become an important trend because of its ability to enhance the dynamic performance of multi-axle heavy vehicle. This article presents a joint estimation of ...

Originally developed for use in spacecraft navigation, the Kalman filter turns out to be useful for many applications. It is mainly used to estimate system states ...