For conventional laser range-gated underwater imaging （RG[） systems, the target image is obtained based oil the reflective character of the target. One of the main performance limiting factors of conventional RGI is...For conventional laser range-gated underwater imaging （RG[） systems, the target image is obtained based oil the reflective character of the target. One of the main performance limiting factors of conventional RGI is that, when the underwater target has the same reflectivity as the background, it is difficult to distinguish the target from the background. An improvement is to use the polarization components of the reflected light. On the basis of conventional RGI, we propose a polarimetric RGI system that employs a polarization generator and a polarization analyzer to detect and recognize underwater objects. Experimental results demonstrate that, by combining polarization with intensity information, we are better able to enhance identification of the underwater target from other objects of the same reflectivity.展开更多
According to the study of super-resolution range-gated system, we proposed an improved system with linear plus detects. And a range function is derived by considering the shot effect noise and dark current noise. The ...According to the study of super-resolution range-gated system, we proposed an improved system with linear plus detects. And a range function is derived by considering the shot effect noise and dark current noise. The simulation shows that the improved system has a good range accuracy capability.展开更多
We present a range-gating delayed detection super-resolution imaging Iidar with high accuracy based on the signal intensities of three consecutive delay samples. The system combines the range and signal intensity info...We present a range-gating delayed detection super-resolution imaging Iidar with high accuracy based on the signal intensities of three consecutive delay samples. The system combines the range and signal intensity information from multi-pulse detections to calculate the pulse peak position under the assumption of a Gaussian pulse shape. Experimental results indicate that the proposed algorithm effectively calculates pulse peak position and exhibits excellent accuracy with super-resolution. Accuracy analysis shows that accuracy is best improved by enhancing signal-to-noise ratio, strategically selecting samples, reducing pulse width, and appropriately choosing the delayed periods between samples.展开更多
基金Supported by the National Natural Science Foundation of China under Grant No 61205187the China Postdoctoral Science Foundation under Grant No 2012M510217
文摘For conventional laser range-gated underwater imaging （RG[） systems, the target image is obtained based oil the reflective character of the target. One of the main performance limiting factors of conventional RGI is that, when the underwater target has the same reflectivity as the background, it is difficult to distinguish the target from the background. An improvement is to use the polarization components of the reflected light. On the basis of conventional RGI, we propose a polarimetric RGI system that employs a polarization generator and a polarization analyzer to detect and recognize underwater objects. Experimental results demonstrate that, by combining polarization with intensity information, we are better able to enhance identification of the underwater target from other objects of the same reflectivity.
文摘According to the study of super-resolution range-gated system, we proposed an improved system with linear plus detects. And a range function is derived by considering the shot effect noise and dark current noise. The simulation shows that the improved system has a good range accuracy capability.
文摘We present a range-gating delayed detection super-resolution imaging Iidar with high accuracy based on the signal intensities of three consecutive delay samples. The system combines the range and signal intensity information from multi-pulse detections to calculate the pulse peak position under the assumption of a Gaussian pulse shape. Experimental results indicate that the proposed algorithm effectively calculates pulse peak position and exhibits excellent accuracy with super-resolution. Accuracy analysis shows that accuracy is best improved by enhancing signal-to-noise ratio, strategically selecting samples, reducing pulse width, and appropriately choosing the delayed periods between samples.
