Calibration of a Polarization Navigation Sensor Using the NSGA-II Algorithm


A bio-inspired polarization navigation sensor is designed based on the polarization sensitivity mechanisms of insects. A new calibration model by formulating the calibration problem as a multi-objective optimization problem is presented. Unlike existing calibration models, the proposed model makes the calibration problem well-posed. The calibration parameters are optimized through Non-dominated Sorting Genetic Algorithm-II (NSGA-II) approach to minimize both angle of polarization (AOP) residuals and degree of linear polarization (DOLP) dispersions. The results of simulation and experiments show that the proposed algorithm is more stable than the compared methods for the calibration applications of polarization navigation sensors.