IOT开发套件对话框半导体DA14583：测量雷竞技电竞平台角度数据而不是角度

嗨divya panchai，

1. Since that data is raw, you are getting the data as extracted from the gyro sesnor, so they are rates and not angles so they are deg/sec.
2. I ve allready mentioned that you can integrate the raw values and estimate the actual angle using only the gyro data, but in any case this question is out of scope of this forum.
3. The log file logs raw data so again is deg/sec
4. The same way mentioned in answer 2, between the different projects the raw data are the same, but the feeding the sensor fusion engine provides an estimation of the angle using a fusion of all the sensors.
5. I suppose that you can customize the android application in order to output only that data that you would like, but we dont support modifications on the android applications, the source code is available in order for you to check it. Or you can modify the SFL project in order to send only SFL data instead of raw with SFL but this would require significant modifications on the project and its not just a simple #define or a simple mod.
6. Regarding the sensor fusion data, the sensor fusion packet is described on Table 12 : Report Structure for sensor fusion, the values return by the sensor fusion algorithm, the algorithm outputs the orientation in quartenions, if you would like to isolate only the SFL reports from the log file you could process the log using somekind of sw, excell or something similar, please check the Appendixes A and B for the sensor fusion data.

Thanks MT_dialog

Hi Divya Panchal,

As mentioned, the raw data that you can use and get actual angles are the data from the gyro, integrating the data will give an estimation of the rotation of the object over the three gyro axis but there are downsides when using only the gyro to estimate position. The IoT in order to aquire the orientation uses data from all three sensors, accelerometer, gyroscope and magnetometer (depending on the configuration) in order position the object's orientation more accurate. Dialog's SFL library and the sensor fusion algorithm is not provided. There are methods and approprite explanations over the internet that describe how to estimate the position of an object in space that are available.

Yes, the Appendixes A and B describe the output of the sensor fusion data of the SFL library and how should be interpreted, there is also a reference to the appropriate wikipedia explanation.

The log in the SFL will provide you both with raw data and SFL data on demand (sensor fusion raw enable option), regarding the rate of the sensor fusion this is configurable and depends on the rate of the accelerometer and the gyroscope, please check the UM-B-063 DA14583 IoT Sensor Development Kit.pdf on paragraph 7.3 in order to understand how the sensor fusion rate is calculated and what data are send over the air.

Thanks MT_dialog

Hi Divya Panchal,

1) Regarding refreshing the data on the sensors, on the SFL the data should be updated automatically you dont have to do anything explictly, if you are getting the same data on your log, are you moving the sensor so that you can obtain new data ?

6) The IoT application uses the SFL data and translates them in roll, pitch and yaw in order to move the 3D image if that is what you mean as "angular form" then you can check the android source code which is available on line and check how the application is using the received data in the updateScene method and converts the SFL data. Those data are also logged after the application gets a SFL data packet.

Thanks MT_dialog