盖革模式APD阵列激光雷达图像的三维目标检测

Tianming Zhao, J. Tian, Hang Liu, Peng Jiang
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引用次数: 2

摘要

盖革模式雪崩光电二极管(APD)阵列激光雷达是一种体积小、成像速度快、灵敏度高的非扫描激光雷达。本文研究了盖革模式APD阵列激光雷达图像的三维目标检测问题。盖革模式APD阵列激光雷达由于其成像特性,在成像过程中存在较大的噪声。本文分析了其噪声特性,并将其分解为环境噪声、损耗噪声、内部噪声和串扰噪声四部分。根据噪声特性,模拟了盖革模式APD阵列激光雷达成像。在此基础上,研究了目标检测算法。本文提出了一种基于KNN分类的滤波方法,并结合改进的循环滤波算法对图像进行预处理。然后提出了一种自适应叠加算法,对预处理后的多帧图像进行融合。在盖革模式APD阵列激光雷达采集的5幅图像数据上对目标检测算法进行了测试,在20帧内即可检测到中、小规模目标。50帧可检测到大规模目标,100帧可检测到远距离目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
3D target detection of Geiger mode APD array lidar image
The Geiger mode Avalanche Photo Diode (APD) array lidar is a non-scanning lidar, which has a small volume, fast imaging speed and high sensitivity. In the paper, the 3D target detection of Geiger mode APD array lidar image is studied. Geiger mode APD array lidar has great noise in the process of imaging due to its imaging characteristics. The paper analyzes its noise characteristics and decomposes the noise into four parts: environment noise, loss noise, internal noise and crosstalk noise. According to the noise characteristics, the paper simulated the Geiger-mode APD array lidar imaging. And based on this, the target detection algorithm was studied. The paper proposes a filtering method based on the KNN classification and combine an improved loop filtering algorithm to preprocess the image. And then an adaptive superposition algorithm is proposed to fuse the preprocessed multi-frame image. Testing the target detection algorithm on five image data captured by the Geiger mode APD array lidar, the medium-scale and small-scale targets can be detected in 20 frames. The largescale targets can be detected in 50 frames, and long-distance targets can be detected in 100 frames.
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