Antho，
如果您仍在查看有关LSM303使用情况的其他信息，我建议您查看F401演示文件夹中的selftest.c文件。您可以使用I2C连接读取传感器数据（例如LSM303DHLC_CompassReadAcc）。获得加速度计和罗盘数据后，应将其与陀螺仪数据（来自L3GD20）相结合。
加速度计有很多短期噪音，但长期稳定性好。陀螺仪噪音很小，但漂移很差。您可以使用卡尔曼滤波器来组合数据流，简单的低通和高通滤波器，或者附加方法（例如基于模型的偏差调整）。
以上来自于谷歌翻译
以下为原文
Antho,
Just in case that you are still looking some additional information about the LSM303 usage, I would recommend that you look the selftest.c file in the F401 demonstration folder. There you have the code to read the sensor data (such as LSM303DHLC_CompassReadAcc) using the I2C connection. Once you have the accelerometer and compass data, you should combine that with the gyro data (from L3GD20).
The accelerometer has a lot of short term noise, but good long term stability. The gyro has little noise, but it has a bad drift. You can use a Kalman filter to combine the data streams, simple low pass and high pass filters, or add-hoc methods (such as model based bias adjustment).
Antho，
如果您仍在查看有关LSM303使用情况的其他信息，我建议您查看F401演示文件夹中的selftest.c文件。您可以使用I2C连接读取传感器数据（例如LSM303DHLC_CompassReadAcc）。获得加速度计和罗盘数据后，应将其与陀螺仪数据（来自L3GD20）相结合。
加速度计有很多短期噪音，但长期稳定性好。陀螺仪噪音很小，但漂移很差。您可以使用卡尔曼滤波器来组合数据流，简单的低通和高通滤波器，或者附加方法（例如基于模型的偏差调整）。
以上来自于谷歌翻译
以下为原文
Antho,
Just in case that you are still looking some additional information about the LSM303 usage, I would recommend that you look the selftest.c file in the F401 demonstration folder. There you have the code to read the sensor data (such as LSM303DHLC_CompassReadAcc) using the I2C connection. Once you have the accelerometer and compass data, you should combine that with the gyro data (from L3GD20).
The accelerometer has a lot of short term noise, but good long term stability. The gyro has little noise, but it has a bad drift. You can use a Kalman filter to combine the data streams, simple low pass and high pass filters, or add-hoc methods (such as model based bias adjustment).
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