陀螺仪在手机上的漂移 [英] Gyroscope drift on mobile phones

问题描述

很多帖子都谈到了陀螺仪漂移问题.有些人说陀螺仪的读数有漂移，但是其他人说积分有漂移.

Lots of posts talk about the gyro drift problem. Some guys say that the gyro reading has drift, however others say the integration has drift.

1. 原始陀螺仪读数有漂移 [链接] .
2. 集成出现了漂移 [链接] (答案1).

1. The raw gyro reading has drift[link].
2. The integration has drift[link](Answer1).

因此，我进行了一个实验.接下来的两个数字就是我得到的.下图显示陀螺仪读数根本不漂移，但具有偏移量.由于存在偏移，因此集成是可怕的.因此，似乎积分就是漂移，不是吗?

So, I conduct one experiment. The next two figures are what I got. The following figure shows that gyro reading doesn't drift at all, but has the offset. Because of the offset, the integration is horrible. So it seems that the integration is the drift, is it?

下图显示，减少偏移量后，积分根本不会漂移.

The next figure shows that when the offset is reduced the integration doesn't drift at all.

此外，我进行了另一个实验.首先，我将手机固定在桌子上约10秒钟.然后将其向左旋转，然后还原回去.然后向右和向后.下图很好地说明了角度.我使用的只是减少偏移量，然后进行积分.

In addition, I conducted another experiment. First, I put the mobile phone stationary on the desk for about 10s. Then rotated it to the left then restore to back. Then right and back. The following figure tells the angle quite well. What I used is only reducing the offset then take the integration.

所以，我的最大问题是，偏移量可能是陀螺漂移(积分漂移)的本质吗?在这种情况下可以使用免费的滤波器或卡尔曼滤波器来消除陀螺仪漂移吗?

So, my big problem here is that maybe the offset is the essence of the gyro drift(integration drift)? Can complimentary filter or kalman filter be applied to remove the gyro drift in this condition?

感谢您的帮助.

推荐答案

如果陀螺仪读数出现漂移"，则称其为 bias 而不是漂移.

If the gyro reading has "drift", it is called bias and not drift.

漂移是由于积分引起的，即使偏差恰好为零，也会发生漂移.漂移是因为您正在通过积分积累读数的白噪声.

The drift is due to the integration and it occurs even if the bias is exactly zero. The drift is because you are accumulating the white noise of the reading by integration.

对于取消漂移，我强烈推荐方向余弦矩阵IMU :理论手稿，我已经为 Shimmer 2 实现了传感器融合a>基于它的设备.

For drift cancellation, I highly recommend the Direction Cosine Matrix IMU: Theory manuscript, I have implemented sensor fusion for Shimmer 2 devices based on it.

(该文档来自 MatrixPilot 项目，此项目已移至Github，并且可以在Wiki的下载"部分找到.)

( The document is from the MatrixPilot project, which has since moved to Github, and can be found in the Downloads section of the wiki there.)

如果您坚持使用卡尔曼滤波器，请参阅 https://stackoverflow.com/q/5478881/341970 .

If you insist on the Kalman filter then see https://stackoverflow.com/q/5478881/341970.

为什么要实现自己的传感器融合算法?

两个Android(Sensor.TYPE_ROTATION_VECTOR下的 SensorManager )和iPhone(

Both Android (SensorManager under Sensor.TYPE_ROTATION_VECTOR) and iPhone (Core Motion) offers its own.

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