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用于性能评估的盖革模式成像激光雷达系统的仿真。

Simulation of a Geiger-mode imaging LADAR system for performance assessment.

机构信息

Department of Geoinformatics, University of Seoul, 90 Jeonnong-dong, Dongdaemun-gu, Seoul 130-743, Korea.

出版信息

Sensors (Basel). 2013 Jul 3;13(7):8461-89. doi: 10.3390/s130708461.

DOI:10.3390/s130708461
PMID:23823970
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3758605/
Abstract

As LADAR systems applications gradually become more diverse, new types of systems are being developed. When developing new systems, simulation studies are an essential prerequisite. A simulator enables performance predictions and optimal system parameters at the design level, as well as providing sample data for developing and validating application algorithms. The purpose of the study is to propose a method for simulating a Geiger-mode imaging LADAR system. We develop simulation software to assess system performance and generate sample data for the applications. The simulation is based on three aspects of modeling-the geometry, radiometry and detection. The geometric model computes the ranges to the reflection points of the laser pulses. The radiometric model generates the return signals, including the noises. The detection model determines the flight times of the laser pulses based on the nature of the Geiger-mode detector. We generated sample data using the simulator with the system parameters and analyzed the detection performance by comparing the simulated points to the reference points. The proportion of the outliers in the simulated points reached 25.53%, indicating the need for efficient outlier elimination algorithms. In addition, the false alarm rate and dropout rate of the designed system were computed as 1.76% and 1.06%, respectively.

摘要

随着激光雷达系统应用的逐渐多样化,新型系统正在被开发出来。在开发新系统时,模拟研究是必不可少的前提。模拟器可以在设计阶段预测性能和优化系统参数,并为开发和验证应用算法提供样本数据。本研究旨在提出一种模拟盖革模式成像激光雷达系统的方法。我们开发了模拟软件来评估系统性能并生成应用程序的样本数据。该模拟基于几何、辐射度和检测三个方面的建模。几何模型计算激光脉冲反射点的距离。辐射度模型生成包括噪声在内的回波信号。检测模型根据盖革模式探测器的特性确定激光脉冲的飞行时间。我们使用带有系统参数的模拟器生成样本数据,并通过将模拟点与参考点进行比较来分析检测性能。模拟点中的异常值比例达到 25.53%,表明需要有效的异常值消除算法。此外,设计系统的虚警率和漏报率分别为 1.76%和 1.06%。

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