no_std implementation of Heikki Hyyti and Arto Visala DCM-IMU algorithm. """The DCM-IMU algorithm is designed for fusing low-cost triaxial MEMS gyroscope and accelerometer measurements. An extended Kalman filter is used to estimate attitude in direction cosine matrix (DCM) formation and gyroscope biases online. A variable measurement covariance method is implemented for acceleration measurements to ensure robustness against transient non-gravitational accelerations which usually induce errors to attitude estimate in ordinary IMU-algorithms."""
Usage
# Create DCMIMU:
let mut dcmimu = DCMIMU::new();
let mut prev_t_ms = now();
loop {
# get gyroscope and accelerometer measurement from your sensors:
let gyro = sensor.read_gyro();
let accel = sensor.read_accel();
# Convert measurements to SI if needed.
# Get time difference since last update:
let t_ms = now();
let dt_ms = t_ms - prev_t_ms
prev_t_ms = t_ms
# Update dcmimu states (don't forget to use SI):
let dcm = dcmimu.update((gyro.x, gyro.y, gyro.z),
(accel.x, accel.y, accel.z),
dt_ms.seconds());
println!("Roll: {}; yaw: {}; pitch: {}", dcm.roll, dcm.yaw, dcm.pitch);
# Measurements can also be queried without updating:
println!("{:?} == {}, {}, {}", dcmimu.all(), dcmimu.roll(), dcmimu.yaw(), dcmimu.pitch());
}