Algorithm design and experimental verification of a heading measurement system based on polarized light/inertial combination

In recent years, polarized light navigation has been widely used for the application of the autonomous heading measurement of small unmanned combat platforms to satellite navigation rejection. However, current techniques of polarized light navigation yield low accuracy when measuring the heading angle in dynamic environments, and the use of a single source of navigation has some shortcomings as well. In the environment of satellite navigation rejection, a method to measure the heading angle using angle compensation based on three-dimensional image geometric correction is proposed in this paper. A model of polarized light/inertial combination based on the Cubature Kalman Filter (CKF) is established using this, and was verified by outdoor experiments that employed the polarized light/inertial combination heading measurement system. The results showed that the overall stability of the heading angle as calculated by the data fusion algorithm of polarized light and the inertial system based on the CKF followed the trend of the polarized light, which adequately suppressed the angle drift caused by data of the inertial system. Following the application of the CKF filtering algorithm, the root mean square error of the heading angle was 1.0719 degrees, which improved the accuracy of calculating the heading angle of the polarized light/inertial integrated system in non-horizontal road environments.