Testing Kalman Filter for accelerometer data
- Guava
acc_log.dat file
with format:
timestamp [millis] | accelerometer (one of axis)
65464208 0.25911117
65464260 0.20279828149999996
65464281 0.2315574732583333
65464293 0.1434090791808333
65464309 0.14202263688562494
.
.
.
Adjust:
constants.Constants.FILTER_GAIN
to value in range [0.0 - 1.0]. Smaller the value is -> Kalman filter algorithm has less impact to the final data.
new_acc_log.dat
Usage with gnuplot:
plot "acc_log.dat" using 1:2 w l, "new_acc_log.dat" using 1:2 w l
ALL (raw data + two Kalman charts):
RAW DATA:
KALMAN FILTER WITH FILTER_GAIN == 0.9:
KALMAN FILTER WITH FILTER_GAIN == 0.95: