Unscented Kalman Filtering-based multisource error calibration method for bionic polarization sensor

Abstract

The invention discloses an unscented Kalman Filtering-based multisource error calibration method for a bionic polarization sensor. The method does not depend on high-precision instrument equipment; and by building a bionic polarization system model, multisource error calibration and compensation are realized by virtue of an unscented Kalman Filtering method. The method comprises the following steps of (1) performing multisource error analysis on the polarization light sensor, wherein multisource errors mainly include a sensor mounting error, a measurement noise and a scale factor; (2) selecting the multisource errors and a polarization azimuth angle as system states for building a system state model; (3) selecting a light intensity measurement value comprising the multisource errors as a system output for building a system measurement model; (4) establishing an experimental environment, and collecting experimental data; (5) designing an unscented Kalman Filter, and estimating the mounting error, the scale factor and the polarization azimuth angle; and (6) according to estimated values, compensating an actual measurement value of the polarization sensor. The method has the characteristics of low calibration cost, high efficiency and the like, and is suitable for quick calibration and compensation of the bionic polarization sensor.

Description

technical field [0001] The invention relates to the technical field of calibration and compensation of a bionic polarization navigation system, in particular to a multi-source error calibration method for a bionic polarization sensor based on an unscented Kalman filter. Background technique [0002] In the 1870s, the famous British physicist Rayleigh discovered the Rayleigh scattering law based on Maxwell's electromagnetic wave theory, and learned about the scattering characteristics of sunlight in atmospheric molecules. After sunlight enters the earth's atmosphere, different polarization forms are produced due to the scattering of atmospheric molecules, and these polarization forms will produce stable atmospheric polarization distribution patterns. People can use these distribution patterns to obtain navigation information. [0003] With the deepening of research, Professor R. Wehner, a scientist at the University of Zurich in Switzerland, studied the trajectory of sand ant...

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Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide an unscented Kalman filter calibration method for the multi-source errors of the polarization sensor in view of the multi-source error interference of the polarization sensor in the polarization navigation system, which solves the problem that the polarization sensor does not rely on other precision The problem of error analysis and calibration under the conditions of instruments and equipment improves the efficiency and accuracy of polarization navigation

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