Design and calibration model of a bioinspired attitude and heading reference system based on compound eye polarization compass

Abstract

Insects such as honeybees are capable of fusing the information sensed by multiple sensory organs for attitude and heading determination. In this paper, inspired by the sensory fusion mechanism of insects’ polarization compass and haltere, a bioinspired polarization-based attitude and heading reference system (PAHRS) is presented. The PAHRS consists of compound eye polarization compass and inertial measurement unit (IMU). By simulating multi-view structure of the dorsal rim area in insects’ compound eyes, a non-coplanar ‘polarization-opponent (POL)-type’ architecture is adopted for the compound eye polarization compass. The polarization compass has multi-directional observation channels, which is capable of adaptively selecting the angle of polarization and obtaining the polarization vectors. Therefore, the environmental adaptability of the polarization compass can be enhanced. In addition, the integration strategy between the compound eye polarization compass and IMU is proposed. Moreover, the sources of system errors are analyzed to improve the heading angle accuracy, based on which a new calibration model is established to compensate the installation errors of the PAHRS. Finally, experiments are carried out under both clear sky and cloudy conditions. The test results show that the error root mean square of heading angle is 0.14° in clear sky, and 0.42° in partly cloudy conditions.

Robust Heading Measurement Based on Improved Berry Model for Bionic Polarization Navigation

“…Han [24] established the error model about CMOS light intensity response error and polarizer installation angle error, and used the least square method to iteratively solve the error parameters. Yang [25], [26] introduced the coupling coefficient into the error model of the point-source polarization sensor to solve the problem of optical path coupling. Ren [27] introduced extinction ratio coefficient into the image-based polarization sensor model to unify the incident light intensity of two orthogonal channels, which improved the accuracy of the error parameters.…”

A 3D Attitude Estimation Method Based on Attitude Angular Partial Feedback for Polarization-Based Integrated Navigation System

“…IMU is mounted inside PAHRS. The features of PAHRS are given in Table 3 (for more about PAHRS see Ref [ 26 ]).…”

“…Then, the E-vector in b-frame is given by , where denotes the installation matrix of the monocular polarization unit, the calibration of which is detailed in Ref [ 26 ]. According to the single-scattering Rayleigh based theory, all E-vectors are orthogonal to the solar vector in CPP.…”

Bionic Integrated Positioning Mechanism Based on Bioinspired Polarization Compass and Inertial Navigation System

“…Based on Equations (9), (11), and (12), we can get the following expression by performing the first-order Taylor expansion on the point L real and λ real : sin(H c sun ) = sin(H n sun + δH) = sin H n sun + cos H n sun δH…”

“…Inspired by the polarization navigation mechanism of animals, the attitude determination methods based on the polarized light compass have been proposed [11][12][13][14][15]. To address the challenge of vehicle positioning based on the polarization pattern, Mei et al proposed a bioinspired positioning method based on the polarized skylight [16].…”