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 remains a cornerstone of state estimation in stochastic systems, enabling the real‐time integration of noisy measurements into dynamic system models. Originally developed for linear ...

Numerical basics -- Method of least squares -- Recursive least-quares filtering -- Polynomial Kalman filters -- Kalman filters in a nonpolynomial world -- Continuous polynomial Kalman filter -- ...

During the COVID pandemic, while most of us spent our time in lockdown baking bread and creating dance memes, Electrical Engineering Professor Sami Fadali was writing a textbook. “Introduction to ...

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, ...

(A) 3D model of the manipulator structure, consisting of 3 continuum segments. The manipulator operates in the plane. (B) Close-up view of the revolute joint between adjacent disks. (C) Diagram ...

Global navigation satellite systems (GNSS) are vital for positioning autonomous vehicles, buses, drones, and outdoor robots. Yet its accuracy often degrades in dense urban areas due to signal blockage ...

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 ...

We’ve probably all had a few conversations with people who hold eccentric scientific ideas, and most of the time they yield nothing more than frustration and perhaps a headache. In [Bertrand Selva]’s ...