The Design Of Attitude Detection System Based On Multi-Sensor And Research On Data Fusion Algorithm

The attitude detection system based on multi-sensor fuses the data from different sensors to calculate the optimal attitude information of carrier.And the attitude information is outputted in real time.Compared with the attitude detection system based on a single sensor,multiple sensors work together to further improve the accuracy and reliability of measurements in the system.With the emergence of new sensors such as MEMS inertial sensors,magnetoresistive sensors,visual sensors and so on,the application field of attitude detection systems has gradually expanded from the traditional fields of aerospace and industrial control to people's daily life.At the same time,higher requirements for attitude detection system have also been put forward on many aspects such as volume,power consumption and accuracy.Firstly,this paper analyzes the application value of attitude detection systems.Then some kinds of attitude detection methods and the advantages of attitude detection system based on multi-sensor are introduced.After investigating a large number of literatures related to attitude detection technology and the information of related product in the current market,the research status and development trend of attitude detection technology and data fusion algorithm in recent decades are summarized.Secondly,the relevant theoretical knowledge involved in attitude detection systems is elaborated.The definitions of reference coordinate system and carrier coordinate system are pointed out.And the mutual conversion between two coordinate system is also pointed out.Several mathematical representations of carrier attitude and their interrelations are also summarized.The principle of attitude measurement based on different sensors is introduced.Several data fusion algorithms are summarized by analyzing the output characteristics of different sensors.The design principle and applications of these algorithms are described in detail.The performance of different data fusion algorithms was compared.Thirdly,a low cost,miniaturized and high precision attitude detection system is designed based on the requirements of the civil use.The STM32F103T8U6 microprocessor is token as the control and calculation unit in the system.And multi-sensor combination scheme consists of an inertial measurement unit LSM6DS3 and a magnetoresistive sensor HMC5883 L to obtain the angular velocity,acceleration,magnetic field strength and other information.The former integrates a triaxial MEMS gyroscope and a triaxial MEMS accelerometer.The output of the three sensors are calibrated by establishing their error models.By analyzing the performance of the main control chip and the expectation of the system,an extended Kalman filter algorithm is designed to fuse the calibrated sensor measurements to obtain the unique attitude information.The computer soft is designed by Qt5.7 to communicate with the system and display the attitude angles.Finally,the stability,static accuracy,dynamic tracking and other performance of the system were tested and analyzed through experiments.The experimental results show that the proposed extended Kalman filter algorithm can effectively fuse the measurements of the three sensors.It also can significantly suppress the angular drift caused by the cumulative error of the gyroscope and the influence of other noises in the system.The calculated attitude information is stable and reliable.The whole system can not only output stable and accurate attitude angles in static state,but also realize the real-time tracking of attitude angles when it is in acceleration or uniform velocity state.So it has good dynamic response.In a word,the system meets the initial design expectation under both static and dynamic conditions.