2个传感器读数融合(偏航，俯仰) [英] 2 sensor readings fusion (Yaw, pitch)

问题描述

目前，我正在实施一种头部跟踪解决方案，该解决方案可以从2个不同的来源获取偏航和俯仰.陀螺仪和磁场传感器.

Currently I am implementing a head tracking solution that takes yaw and pitch from 2 difference sources; a gyro and a magnetic field sensor.

我已经将两个值都传递到了程序中，现在我试图确定保持陀螺仪精度与固定发射器mf传感器的无损特性的最佳方法.目前，我正在使用newYaw = currentGyroYaw + 0.05 *(两者之间的差异)缓慢拖动陀螺仪以将其锚定到mf，但是它具有相当恒定的运动.

I have both the values passed into my program and now I am attempting to determine the best way to keep the precision of the gyro with the lossless nature of a fixed emitter mf sensor. Currently I am using newYaw = currentGyroYaw + 0.05*(difference between) to slowly drag the gyro to anchor to the mf, but it has some fairly constant movement.

有人建议我尝试使用卡尔曼滤波器，但是我整天都在寻找有关它的资源，但似乎无法弄清楚如何将其应用于我的场景.以及在我的情况下所有的值是什么.

It has been suggested that I try and use a Kalman filter but I've been looking up resources all day about it but can't seem to figure out how to apply it to my scenario; and what all the values would be in my case.

如果任何人都可以帮助伪造步骤和计算，我将需要获取2个偏航/俯仰值并产生一个新的更准确的设置，将不胜感激.谢谢.

If anyone could help psuedo the steps and calculations I would need to take 2 yaw/pitch values and produce a new more accurate set it would be greatly appreciated. Thanks.

推荐答案

基本上，此技术称为传感器融合.是的，您可以使用基于卡尔曼滤波器的传感器融合.请阅读此 https://home.wlu.edu/~levys/kalman_tutorial/kalman_14 .html ，其中不带任何有关运动模型的信息的解释，并举例说明了如何执行传感器融合.

Basically, this technique is called sensor fusion. Yes, you can use Kalman filter based sensor fusion. Please read this https://home.wlu.edu/~levys/kalman_tutorial/kalman_14.html where it explains without knowing any information about motion model how to perform sensor fusion with an example.

如果我进一步说明您的问题，则有两个传感器可提供偏航角和俯仰角.如果我遵循上面提到的相同符号，则C矩阵应为.我假设来自两个传感器的那两个读数具有相同的影响.您必须更改其他矩阵的维数.在这里( https://github.com/GPrathap/RobotTrajectoryEstimation )，您可以找到一些我拥有的示例完毕.希望这可以帮助您解决问题.

If I explain a little bit more about your problem, you have two sensors which give yaw and pitch. If I follow the same notation which I referred above, C matrix should like, . where I assume that those two reading which comes from two sensors has the same influence. You have to change the dimensionality other matrics. Here (https://github.com/GPrathap/RobotTrajectoryEstimation) you can find some example which I have done. Hope this will help you to resolve your problem.

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