使用扩展卡尔曼滤波器对imu和gps进行传感器融合 [英] Sensor fusion of imu and gps using extended kalman filter

问题描述

我正在研究imu和gps的传感器融合，以便在世界坐标上有准确的位置。

我已经在C ++中进行了2D实现，但是现在我很难将它扩展到3D作为参数真的很复杂添加，因为我很困惑如何使我的状态空间和其他矩阵进行预测和更新，加上融合数据也是一个问题如何在3D过滤器中引入数据，我需要IMU的保险丝（XYZ）位置也偏航，滚动（GPS的经度和纬度[XY]）位置。

如果你们中的任何人已经实现了它或导致我可以看到或采取的地方任何指导都会有很大的帮助。

谢谢！



我尝试过的事情：



i用于线性系统的1d和2d kalman实现。

Hi, i am working on sensor fusion fo imu and gps to have accurate position on world coordinates.
I have worked on 2D implementation in C++ but now i am facing it difficult to extend it to 3D as the parameters are really complex to add as i am getting confused how to make my state space and other matrix for predict and update, Plus fusing the data is also an issue how to introduce the data in the filter for 3D, I need to fuse (X Y Z) position of IMU also yaw, roll with (Longitude and Latitude [X Y]) position of GPS.
If anyone of you have implemented it or have leads to that where i can look or take any guide that would be a big help.
Thanks!

What I have tried:

i have worked with 1d and 2d kalman implementation for linear systems.

推荐答案

在此站点搜索GPS 。关于这个主题有很多文章。搜索框位于此站点第一页的右上角。

Do a search for GPS at this site. There are a good number articles on the topic. The search box is in the upper right corner on the first page of this site.

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