Research On Modeling And Calibration Method Of A Bionic Polarization Sensor

Navigation has been widely used in transportation,robot positioning,geographic information mapping,aerospace and other fields.However,in the complex environment,the existing navigation technology inevitably has the defects of low autonomy,poor precision and vulnerability to interference.It is urgent to have a new navigation method with strong autonomy,small accumulation error,high precision and strong anti-interference ability.In recent years,researchers have found that creatures such as sand ants can use the sky polarized light information to achieve long-distance high-precision autonomous navigation and positioning.The bionic polarization navigation method satisfies the navigation requirements under complex environments.The polarization sensor is a core device for implementing polarization navigation.It is very important for polarization navigation to improve sensor accuracy.In this paper,according to the animal's use of sky polarized light information to realize the navigation mode,the bionic polarization sensor is designed to obtain the carrier heading angle information.In terms of analyzing the multi-source disturbance and error sources that constrain the accuracy of the sensor,the disturbance model is established,and the least squares,Extended Kalman Filter(EKF)and Unscented Kalman Filter(UKF)algorithm are designed to estimate and compensate the multi-source disturbance of the sensor.The main research contents are:1.For the problem that the accuracy of polarization sensor is affected by multi-source error disturbance,the type and source of sensor error are analyzed based on the mechanism of polarization information acquisition,including polarizer installation error,sensor scale factor,polarization coefficient and measurement noise,and four kinds of error sources.In the mathematical characteristics,the installation error is constant.The scale factor and the degree of polarization coefficient are related to the difference in the response of the photodiode to the optical signal,and the measurement noise distribution exhibits a Gaussian distribution.Based on the characteristic analysis of the disturbance signal,the measurement model of the bionic polarization sensor with multi-source disturbance is established.2.For the problem that the parameters of polarization sensor need to be calibrated,a state equation containing unknown parameters is established on the basis of the sensor measurement model with multi-source disturbance.In order to solve the problem of light intensity phase inconsistency measured by sensors,a rough calibration algorithm is proposed to achieve input light intensity normalization.Based on the rough calibration,the least squares algorithm,EKF algorithm and UKF algorithm are designed to estimate the unknown parameters.3.In order to verify the validity of the proposed algorithm and evaluate the accuracy of the polarization sensor after calibration,the simulation and indoor measured data experiments were carried out.The least squares,EKF,and UKF simulations and indoor experiments under the coarse calibration are performed respectively.The three kinds of calibration algorithms can improve the measurement accuracy of the sensor in the indoor environment,and the error of polarization azimuth angle of two calibration algorithms of EKF and UKF is smaller.The algorithm designed can meet the accuracy and stability requirements of polarization sensors in this paper.