Research And Implementation Of MAVs Sensor System Based On The Dual-core Of CORTEX-M4

Multi-rotor MAVs is the research object that has attracted much attention in recent years, because of its simple mechanical structure, high controllability. The sensor system researched in this paper is one of the most important parts of the UAV. It is mainly composed of the AHRS subsystem and the GPS\INS subsystem. The main work of this thesis is shown as the following:(1) Study the application of UAV navigation algorithm, which is mainly the ARHS design and the INS\GPS design, both of which are based on the Extended Kalman Filter. ARHS provides the attitude angle information. In order to improve the accuracy of the attitude angle estimation, this paper presents a joint estimation algorithm in which the dynamic acceleration is added to the observation equation as the noise and the offset error of the gyroscope is added to the state equation. The INS\GPS system is mainly used to calculate the velocity information and position information. Because the GPS sometimes loses the star and the output frequency is low, we used the integrated INS\GPS navigation algorithm to improve the output frequency to meet the requirements of the UAV control. By embedding the designed algorithm into the sensor system, the results of the algorithm were compared with that of the commercial MTI-G.(2) In order to meet the computational requirements of the algorithm, we improved the traditional single-chip inertial navigation hardware system by replacing it with a dual-chip system to let them cooperate with each other. Combined with the Extended Kalman Filter, the master controller is responsible for running the INS/GPS algorithm to calculate the more accurate position and speed information and the slave controller is responsible for running the algorithm for the attitude and heading system to calculate the attitude information. The master and slave controller transmit the data with each other simultaneously via the high speed SPI interface to guarantee the real-time performance of the controller.(3) Embed the algorithm into the system to verify the feasibility of the algorithm and the hardware circuit. Through the experiments, we verified that the design of the sensor system is effective and practical.