Research and Implementation of Inertial Navigation Algorithm for FPGA

Aiming at the problem that the sensor in the current flight control system is to many and the computational complexity is large, the traditional microprocessor has been difficult to meet its growing performance requirements. This paper presents a parallel adaptive inertial navigation algorithm for FPGA. In this algorithm, the extended Kalman filter is used to estimate the result. The fourth-order Runge-Kutta algorithm is used to estimate the integral. At the same time, the inertial navigation algorithm is modularized and the parallel processing is used to improve the solution speed. The FPGA development board is used to drive the sensor, and the data is solved on the FPGA. The result of the solution is transmitted from the interface to the microprocessor to reduce the interface and performance requirements of the microprocessor. Finally, the simulation results show that the proposed algorithm has good performance in terms of speed and accuracy, and verifies the feasibility of the algorithm on FPGA.