Core Motion的传感器融合算法是否利用了卡尔曼滤波器？ [英] Do the sensor fusion algorithms of Core Motion take advantage of the Kalman filter?

问题描述

Core Motion的传感器融合算法是否利用卡尔曼滤波器？

Do the sensor fusion algorithms of Core Motion take advantage of the Kalman filter?

推荐答案

6月22日更新，2016

根据文档，

Core Motion的传感器提供的处理后的设备运动数据
融合算法给出设备的姿态，旋转速率，b $ b校准磁场，重力方向以及用户赋予设备的
加速度。

The processed device-motion data provided by Core Motion’s sensor fusion algorithms gives the device’s attitude, rotation rate, calibrated magnetic fields, the direction of gravity, and the acceleration the user is imparting to the device.

也就是说，现在已经提供了某种传感器融合算法。我无法从这条信息中分辨出传感器融合算法是卡尔曼滤波器还是同样好的东西。

That is, some sort of sensor fusion algorithm has been provided by now. I cannot tell from this piece of information whether that sensor fusion algorithm is the Kalman filter, or something equally good.

< sub>（从2011年回复。）

不，根据这篇文章。

8月20日更新， 2011

Apple的文档（注意：此链接页面已于2016年6月22日消失）实际上是提供。它似乎不是卡尔曼滤波器实现。

It is not clear from Apple's documentation (note: this linked pages has disappeared by June 22, 2016) what is actually provided. It does not seem to be a Kalman filter implementation.

根据Kay （谁给我发送了上述链接）他自己的卡尔曼滤波器提供了更好的结果。

According to Kay (who sent me the above link) his own Kalman filter provides better results.

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