This report provides an introduction to inertial navigation, focusing on strapdown systems based on MEMS devices. It explores the error characteristics of such systems using a combination of measurement and simulation. The report highlights that current introductions to inertial navigation often fail to adequately describe the error characteristics of these systems. The report begins by introducing inertial navigation and its applications, distinguishing between stable platform and strapdown systems. It then delves into the details of gyroscopes and accelerometers, including their types, error sources, and performance specifications. The Allan Variance technique is introduced as a method to analyze noise processes in these sensors. The report analyzes a simple inertial navigation system (INS) based on the Xsens Mtx inertial measurement unit (IMU). It demonstrates that the average error in position grows to over 150 meters after 60 seconds of operation, primarily due to orientation errors caused by noise in the gyroscope signals. The report identifies white noise as the most significant contributor to this drift. To mitigate drift, the report discusses sensor fusion and domain-specific constraints, showing that using magnetometers can reduce the average error in position from over 150 meters to around 5 meters after 60 seconds. However, it concludes that while MEMS IMU technology is rapidly improving, it is not yet possible to build a MEMS-based INS with sub-meter position accuracy for more than one minute of operation. The report provides a comprehensive analysis of the error characteristics of MEMS gyroscopes and accelerometers, and demonstrates the propagation of errors in an INS using the Xsens Mtx device. It emphasizes the importance of correcting orientation errors to achieve accurate position tracking.This report provides an introduction to inertial navigation, focusing on strapdown systems based on MEMS devices. It explores the error characteristics of such systems using a combination of measurement and simulation. The report highlights that current introductions to inertial navigation often fail to adequately describe the error characteristics of these systems. The report begins by introducing inertial navigation and its applications, distinguishing between stable platform and strapdown systems. It then delves into the details of gyroscopes and accelerometers, including their types, error sources, and performance specifications. The Allan Variance technique is introduced as a method to analyze noise processes in these sensors. The report analyzes a simple inertial navigation system (INS) based on the Xsens Mtx inertial measurement unit (IMU). It demonstrates that the average error in position grows to over 150 meters after 60 seconds of operation, primarily due to orientation errors caused by noise in the gyroscope signals. The report identifies white noise as the most significant contributor to this drift. To mitigate drift, the report discusses sensor fusion and domain-specific constraints, showing that using magnetometers can reduce the average error in position from over 150 meters to around 5 meters after 60 seconds. However, it concludes that while MEMS IMU technology is rapidly improving, it is not yet possible to build a MEMS-based INS with sub-meter position accuracy for more than one minute of operation. The report provides a comprehensive analysis of the error characteristics of MEMS gyroscopes and accelerometers, and demonstrates the propagation of errors in an INS using the Xsens Mtx device. It emphasizes the importance of correcting orientation errors to achieve accurate position tracking.