陆地移动卫星链路的统计模型

4星 · 超过85%的资源 需积分: 9 7 下载量 134 浏览量 更新于2024-09-27 1 收藏 455KB PDF 举报
"A Statistical Model for a Land Mobile Satellite Link - 描述了陆地移动卫星链路的统计模型,该模型假设直视路径分量在树叶衰减(阴影)下的幅度服从对数正态分布,接收的多径干扰具有瑞利分布。提供了等级穿越率和平均衰落持续时间的表达式,并通过模型计算与测量结果的比较显示了合理的良好一致性。该模型对于设计通信系统和模拟实验室中的传播效应非常有用。" 这篇论文主要探讨的是一个用于陆地移动卫星通信链路的统计模型,该模型对于预测不同调制方案下的通信系统性能至关重要。具体来说,模型假定在树叶遮挡(阴影衰落)影响下的直视路径信号幅度遵循对数正态分布,而接收到的多径干扰则符合瑞利分布。这两个假设是基于对实际无线通信环境的理解,其中直视路径信号可能受到建筑物、树木等障碍物的影响,而多径效应则是由于信号反射、折射造成的。 文章中提到了等级穿越率(Level Crossing Rate, LCR)和平均衰落持续时间(Average Faded Duration, AFD),这些都是衡量信号质量的重要参数。等级穿越率描述了信号强度在特定阈值以上或以下穿越的频率,而平均衰落持续时间则反映了信号在低于某一强度水平的时间长度。这些指标对于理解通信系统的稳定性,尤其是对于突发性的信号衰落有重要意义。 模型的建立与验证是通过将计算结果与实际测量数据进行比较来实现的,结果显示两者之间有良好的一致性,这表明该模型可以有效地模拟真实的陆地移动卫星通信环境。这样的模型对于通信系统的设计者来说极其有价值,他们可以利用这个模型来预估不同条件下的系统性能,并进行优化。 此外,该模型也适用于构建传播仿真器,使得研究人员能够在实验室环境中模拟实际的传播效应,这对于实验验证理论预测、优化通信协议和设备设计具有重要作用。论文引用了多篇关于城市环境中的移动无线电信道建模的相关文献,表明了作者对该领域的广泛研究和深入理解。 "A Statistical Model for a Land Mobile Satellite Link" 是一篇关于陆地移动卫星通信的重要研究,它提出的模型对于理解和预测卫星通信信道的衰落特性,以及设计和优化通信系统具有深远的科学价值和工程应用前景。

With the rapid development of China's economy, the per capita share of cars has rapidly increased, bringing great convenience to people's lives. However, with it came a huge number of traffic accidents. A statistical data from Europe shows that if a warning can be issued to drivers 0.5 seconds before an accident occurs, 70% of traffic accidents can be avoided. Therefore, it is particularly important to promptly remind drivers of potential dangers to prevent traffic accidents from occurring. The purpose of this question is to construct a machine vision based driving assistance system based on machine vision, providing driving assistance for drivers during daytime driving. The main function of the system is to achieve visual recognition of pedestrians and traffic signs, estimate the distance from the vehicle in front, and issue a warning to the driver when needed. This driving assistance system can effectively reduce the probability of traffic accidents and ensure the safety of drivers' lives and property. The main research content of this article includes the following aspects: 1. Implement object detection based on the YOLOv5 model. Conduct research on convolutional neural networks and YOLOv5 algorithm, and develop an object detection algorithm based on YOLO5. Detect the algorithm through road images, and analyze the target detection algorithm based on the data returned after training. 2. Estimate the distance from the front vehicle based on a monocular camera. Study the principle of estimating distance with a monocular camera, combined with parameters fed back by object detection algorithms, to achieve distance estimation for vehicles ahead. Finally, the distance estimation function was tested and the error in the system's distance estimation was analyzed. 3. Design and implementation of a driving assistance system. Based on the results of two parts: target detection and distance estimation, an intelligent driving assistance system is constructed. The system is tested through actual road images, and the operational effectiveness of the intelligent driving assistance system is analyzed. Finally, the driving assistance system is analyzed and summarized.

138 浏览量