Recent content by wolfpackdiver

Good point. Estimation filters also will help your results. Look up Kalman filters in particular. (EKF, UKF, etc.) Thanks for the reminder.

...and one more thing. If anyone is wondering where the -omega^2 is coming from, try taking the analytical second derivative of a simple sine wave, say "sin(wt+phi)" and see what you get...interesting, huh? f(t) = A.sin(wt+phi) f'(t) = -Aw.cos(wt+phi) f''(t) = -Aw^2.sin(wt+phi)

Look up discrete FFT (Fast Fourier Transform). There are algorithms out there in most languages and even books called Numerical Recipes that will give you FFT algorithms. As for the increasing function...it's called "drift". Try looking for "accelerometer drift" in google.

Double integration of raw acceleration data is a pretty poor estimate for displacement. The reason is that at each integration, you are compounding the noise in the data. If you are dead set on working in the time-domain, the best results come from the following steps. 1. Remove the mean...