Research And Circuit Design Of Inertial Navigation Algorithm For Uav Based On FPGA

With the rapid development of embedded microprocessors,sensors and other components since the 21 st century,unmanned aerial vehicles have also derived complex functions such as cruise,disaster warning,transportation,telemetry,face recognition and even long-distance communication.As the demand for UAV(unmanned aerial vehicles)increases,so does the number of sensors UAV must carry,which greatly increases the computation of the microprocessor.This poses a challenge to the performance of the microprocessor in UAV.Therefore,the adoption of new design is imperative to reduce the calculation of processor.Since the UAV is over reliance on the microprocessor's performance now,in order to solve this problem,this paper describes the development of quadrotor UAV and the navigation algorithm,and then analyzes the principle of inertial navigation algorithm and its improvement method in detail.Then achieve and optimize the algorithm designed in the paper with MATLAB,and use the final module as a reference of FPGA hardware circuit.According to the structure and function of the inertial navigation module,a sensor drive module,a data calculation module and a data transmission module are designed.Fourth-order Runge-Kutta is used to estimate the integral.According to the relevance of the algorithm data,the pipeline technology is adopted to make the algorithm parallelized and improve the efficiency.In the circuit design of FPGA,a sensor driving module based on IIC protocol,an attitude fusion module based on extended Kalman filter and a data transmission module based on UART are designed.For the pose fusion algorithm,it is divided into linear matrix module,process matrix prediction module,Runge-Kutta module,state measurement module and state update module,and parallelized in the design process.When compare the simulation results with MATLAB's,it proves the correctness of the entire circuit.This paper studies and realizes the inertial navigation module in FPGA.And it uses extended Kalman filter to reduce the noise interference and improve the performance of a flight control system,at the same time uses the fourth-order Runge-Kutta for integral estimation,the final design's accuracy is high,not only reduce the pressure on the flight control master chip,but also improve the performance of the UAV.This project lays a foundation for the UAV in the ASIC design.