Target-positioning method for a four-aperture infrared bionic compound eye based on the reprojection Kalman filter estimation

To accurately determine the relationships among sub-aperture cameras in four-aperture infrared bionic compound eye systems and enhance the target-positioning accuracy, addressing the issues that traditional single-aperture infrared cameras suffer from a limited imaging field-of-view, and multi-aperture camera systems fail to utilize all camera combination and exhibit slow target-positioning convergence speed due to neglecting pose differences of sub-eye cameras, static and dynamic target images were captured using the system. Target-positioning methods were then designed and investigated. Spatial and pose weights were assigned based on the spatial positions and rotation angles of the cameras. A reprojection method was employed to establish the relationships between various camera combinations using the conversion relationship between the image and world coordinate systems. A Kalman filter prediction and update method incorporating a spatially weighted projection was proposed for all camera combinations. Single-aperture and dual-target calibrations were performed using a four-aperture infrared bionic compound eye system to determine the actual field-of-view overlap rate, spatial angle, and pose angle. Static target-positioning experiments were performed using the four-aperture infrared bionic compound eye system. The results indicated that the static target-positioning algorithm achieved a horizontal error of 1.76% at a distance of 2660 mm, a vertical error of 2.44%, and a spatial depth-estimation error of 0.40%. Ablation experiments were conducted to demonstrate the necessity of incorporating spatial weighting. Further verification through dynamic ball target-positioning experiments indicated that the positioning error in the four-aperture overlapping field-of-view at 2840 mm could be controlled within 2.5%.