High-Precision Inertial Navigation Algorithm

In this article, we discuss the significance of high-precision inertial navigation algorithms and their capabilities in experimental trajectory generation and inertial navigation computation. Firstly, high-precision inertial navigation algorithms serve as crucial tools for accurately determining position and orientation, which is vital for aerospace applications, marine exploration, and land surveying. The implementation typically involves sensor fusion techniques combining gyroscope and accelerometer data through Kalman filtering algorithms to minimize drift errors. Secondly, experimental trajectory generation represents a key functionality of high-precision inertial navigation systems, enabling researchers to better understand object motion patterns and trend variations during experiments. This feature often utilizes numerical integration methods like Runge-Kutta algorithms to simulate realistic motion paths based on inertial measurement unit (IMU) data. Finally, inertial navigation computation constitutes another essential capability that facilitates precise control over moving objects' direction and velocity, thereby achieving more accurate motion control and positioning. This process commonly employs quaternion-based attitude representation and mechanization equations to compute position, velocity, and attitude (PVA) solutions from raw sensor measurements.