用IMU的数据进行机器人位置和姿态的估计，比如acc或者gyro积分每个sample怎么进行坐标变换，怎么由rawdata得到位置和姿态信息的计算细节等。 In recent years, microelectromechanical system (MEMS) inertial sensors (3D accelerometers and 3D gyroscopes) have become widely available due to their small size and low cost. Inertial sensor measurements are obtained at high sampling rates and can be integrated to obtain position and orientation information. These estimates are accurate on a short time scale, but suer from integration drift over longer time scales. To overcome this issue, inertial sensors are typically combined with additional sensors and models. In this tutorial we focus on the signal processing aspects of position and orientation estimation using inertial sensors. We discuss dierent modeling choices and a selected number of important algorithms. The algorithms include optimization-based smoothing and ltering as well as computationally cheaper extended Kalman lter and complementary lter implementations. The quality of their estimates is illustrated using both experimental and simulated data.

惯性导航解算算法实现，根据加速度计，陀螺仪的数据来实时计算速度位置姿态

高精度惯性导航系统温度参数标定补偿，matlab程序设计

matlab编写的GPS和惯导的组合导航，内含仿真程序和真实的数据，大家可以下载下来仿真并得到结果。很好用的

本程序是关于四元数法捷联惯导解算算法的matlab程序组合包，其中包括滤波初始对准仿真，罗经法初始对准仿真，捷联惯导解算仿真，组合卡尔曼滤波等演示程序及其必需的参数矩阵转换程序，程序算法皆是本人通过大量阅读捷联惯导经典论文书籍编写的，经过调试已经通过，所得圆锥误差，划桨误差与秦永元所编惯性导航一书相符，可靠性较高。

EKF仿真程序，对了解惯导很有帮助.好不容易找到的，学习惯导的同志们有福了