IMU 32 is a project to simplify working with MPU9250 imu sensors and STM32 ARM M3 microprocessors.
MPU9250.h provides interface which uses the HAL functionality of STM32 and helps in developing applications to interact with imu data.
Write size number of bytes to the register starting at reg.
Read size number of bytes from the register starting at reg.
Write a bit to the register reg.
Read a bit from the register reg.
Set Gyro Full Scale Range:
Available ranges (gyro_fs):
GYRO_FS_250dps: 250 deg/sec
GYRO_FS_500dps: 500 deg/sec
GYRO_FS_1000dps: 1000 deg/sec
GYRO_FS_2000dps: 2000 deg/sec
Set Accelerometer Full Scale Range:
Available ranges (acc_fs):
ACC_FS_2g: 2 g ~ 20 m/s2
ACC_FS_4g: 4 g ~ 40 m/s2
ACC_FS_8g: 8 g ~ 80 m/s2
ACC_FS_16g: 16 g ~ 160 m/s2
Set gyro offsets to gyroOffsets[3].
Set accelrometer offsets to accelOffsets[3].
Configure Gyro Digital Low Pass Filter (DLPF).
Available options (gyro_dlpf):
GYRO_DLPF_BW_8800Hz: 8800 Hz bandwidth with 32 kHz of sampling frequency
GYRO_DLPF_BW_3600Hz_Fs_32kHz: 3600 Hz bandwidth with 32 kHz of sampling frequency
GYRO_DLPF_BW_250Hz: 250 Hz bandwidth with 8 kHz of sampling frequency
GYRO_DLPF_BW_184Hz: 184 Hz bandwidth with 1 kHz of sampling frequency
GYRO_DLPF_BW_92Hz: 92 Hz bandwidth with 1 kHz of sampling frequency
GYRO_DLPF_BW_41Hz: 41 Hz bandwidth with 1 kHz of sampling frequency
GYRO_DLPF_BW_20Hz: 20 Hz bandwidth with 1 kHz of sampling frequency
GYRO_DLPF_BW_10Hz: 10 Hz bandwidth with 1 kHz of sampling frequency
GYRO_DLPF_BW_5Hz: 5 Hz bandwidth with 1 kHz of sampling frequency
GYRO_DLPF_BW_3600Hz_Fs_8kHz: 3600 Hz bandwidth with 8 kHz of sampling frequency
Configure Accelerometer Digital Low Pass Filter (DLPF).
Available options (accel_dlpf):
ACCEL_DLPF_BW_1046Hz: 1046 Hz bandwidth
ACCEL_DLPF_BW_420Hz: 420 Hz bandwidth
ACCEL_DLPF_BW_218Hz: 218 Hz bandwidth
ACCEL_DLPF_BW_99Hz: 99 Hz bandwidth
ACCEL_DLPF_BW_44Hz: 44 Hz bandwidth
ACCEL_DLPF_BW_21Hz: 21 Hz bandwidth
ACCEL_DLPF_BW_10Hz: 10 Hz bandwidth
ACCEL_DLPF_BW_5Hz: 5 Hz bandwidth
EKF.h provides the interface to implement the Extended Kalman filter algorithm which enables estimation of the orientation of the sensor with extreme accuracy.