Research On Motion Detection Technology Of Argo Buoy Based On Fuzzy Kalman

Ocean changes are closely related to abnormal climate conditions.With the development of science and technology,people have realized that monitoring real-time ocean changes is of great significance to climate prediction.Among them,Argo buoy plays an indispensable role in the current Marine environmental monitoring system,and is of great significance in Marine climate prediction,Marine temperature diagnosis and Marine resource development.The motion information of the Argo buoy is not only an important parameter to study the ocean circulation flow pattern,but also an important factor to ensure the effectiveness of the operation.As Argo buoy often works in a complex and changeable Marine environment,it’s motion state in the underwater drifting process is greatly affected by water depth,waves,flow field and other factors,so this paper aims to develop an Argo buoy motion detection system with high accuracy and strong adaptability.The motion detection of Argo buoy focuses on attitude Angle measurement.With the development of micro-electromechanical technology,the application of MEMS inertial sensor in attitude measurement is more and more extensive.But the MEMS gyroscope random drift problems cause cumulative error,and using accelerometer can correct the posture error of horizontal direction,but the attitude algorithm accuracy is affected by acceleration,magnetometer can be used to correct heading Angle error,but affected by the magnetic disturbance is serious,can obtain accurate and stable measurement values.Aiming at the working environment of the Argo buoy and the above problems existing in the inertial measurement devices of MEMS,research on the motion detection technology of the Argo buoy based on MEMS gyroscope,accelerometer and magnetometer is carried out Firstly,the paper analyzes the motion characteristics of the buoy.With the help of the three-dimensional linear potential flow theory,the paper qualitatively analyzes the different motion states of the Argo buoy under different depths of ocean current layers and sea conditions,selects the quaternion method to realize the attitude solution,and studies the motion error model of the buoy.After just a single sensor can only satisfy the precision of attitude algorithm under the condition of a certain limitations,the thought of attitude based on multi-sensor fusion,research with attitude quaternion and gyro random error related to state the amount of Kalman filtering algorithm,and use the fuzzy inference system through the judgment of buoy motion state,realize the noise covariance matrix online adjustment,in order to improve the detection precision and adaptability of the system.After that,the design of motion detection system was discussed.The hardware platform with STM32F303 as the micro-control unit and MEMS sensor as the core was determined.Aiming at the embedded platform,fiizzy Kalman algorithm was simplified to improve the real.time performance of attitude fusion.Finally,the algorithm tests are carried out from gyroscope error correction and fuzzy Kalman accuracy.The results show that the motion detection algorithm based on fuzzy Kalman can well compensate gyroscope error and correct attitude drift,and expand the adaptability of the system.The outdoor test was completed to verify the reliability of the motion detection system.