基于生物复眼的视觉结构特性及视神经处理机制, 搭建了环形31通道的仿复眼视觉快速测距传感器, 建立了基于侧抑制神经网络的仿生多通道视觉快速测距模型, 并提出了基于高斯分布离散信息的多通道传感器多视轴快速标定法, 实现环形传感器视轴标定.实验结果表明：传感器视轴标定后, 传感器阵列中间视角区左眼相对准确度提高20.46%, 右眼相对准确度提高9.00%; 采用夹角6°的传感器阵列, 在左右眼中间评测区内80%以上区域内测得目标所在角度误差小于±0.60°; 实现了仿复眼视觉测距传感器对运动目标(速度50 mm/s)定位误差在-3～10 mm间的实时测距.

Based on the processing mechanism of optic nerve and the characteristics of visual structure of biological compound eye, a ring-shaped vision sensor based on bionic compound eye with fast distance measurement function and 31 channels is built, and a bionic multi-channel fast vision distance measurement model based on lateral inhibition neural network is established. To calibrate optic axis of ring sensors, a rapid way for optic axis calibration of muti-channel sensors based on discrete information with Gaussian distribution is proposed. The experimental results show that the relative accuracy of the left eye is increased by 20.46% and that of the right eye is increased by 9.00% in intermediate angle of view of sensor array after the calibration of optic axis of sensors. The angle measurement accuracy of more than 80% of the points in the middle evaluation area of the left and right eye is within ±0.60° with the sensor array that use 6° angle spacing. The location error of binocular real time ranging results is kept within the range of -3 mm to 10 mm under 50 mm/s velocity.