Traditional MEMS inertial sensing devices include acceleration sensors, gyroscopes, magnetometers, and barometric pressure sensors. These devices are extremely low cost, miniaturized, lightweight, and provide stable and interference-free output with strong adaptability to external environmental conditions. They are now widely available for purchase. The American PNI nine-axis motion sensor fusion chip SENtral combines these traditional inertial measurement units. Such compositional units have been widely used in the military and aviation fields, such as the well-known term: inertial navigation systems. Building upon this concept and adding GPS module correction, it almost enters the scope of missile principles and TMD and NMD defense systems. Of course, laser gyroscopes with high precision are typically used in missile inertial navigation systems, which are expensive and bulky. However, these are not our main concerns. What we care about are the X, Y, and Z sensor data values from the acceleration sensor, gyroscope, and magnetic field, which is commonly referred to as the concept of a nine-axis sensor. Of course, just discussing these nine numerical values and directly applying them to specific devices such as unmanned aerial vehicles and VR equipment has no practical value. Because they must undergo a series of algorithms for fusion, filling in blank data and measurement data errors, and obtaining a smooth and continuous three-axis attitude angle output data. In this process, if there is no support for magnetic field data, the angle value obtained has no reference position, which is the angle information relative to the start-up time of the system. If there is magnetic field data as a reference, the absolute world coordinate angle can be obtained. However, this data often suffers from interference from other artificial strong magnetic fields, including some metal products and large-scale stage trusses. So can displacement information of key points in space be obtained based on this data? The answer is yes. In fact, mathematically speaking, the result of integrating acceleration values is velocity, and integrating again yields displacement. Additionally, the data from the other two sensors can also participate in the fusion algorithm and supplement measurement blanks. --------------------- Author: Sensor Information Source: Sensor Expert Network Original: //www.sensorexpert.com.cn/article/798.html Copyright Notice: This article is organized and published by Sensor Expert Network. Reproduction please indicate the source and link!