基于雷达和传感器融合建模的车辆安全系统
发布时间：2021-08-15 23:26
由于交通事件和道路威胁的增加,交通事故造成了越来越多人员的物质和生命损失。也门是发生公路事故数量最多的国家之一,根据统计数十万人在这些事故中受伤甚至丧生。在最近一年的时间里,有10万到15万的人死于车祸造成的交通事故。为解决这一问题,本文致力于通过数据融合和传感器技术为智能车辆提供一个安全系统,即应用雷达传感器和传感器集成在车辆安全系统中,特别是应用在车辆安全系统的理论中,这将提高跟踪车辆速度和周围环境的雷达系统的可靠性和准确性。本文的主要研究工作总结如下:1)研究了现代车辆安全系统的准确性、可靠性和效率问题。讨论了一些解决方案并演示了如何获得有效的的改进方法。2)研究并提出了一种基于融合水平和具体分类方法的传感器数据融合算法,该算法有助于解决正在研究的传感器数据融合问题。该系统在雷达和视觉系统中都采用了一种特殊的传感器集成机制。3)对所提出的系统进行了设计和评价。本文注意到,作为一个效率案例,本文所提方法实现了更高的准确性和整体性能。与以往的研究相比,本文提出的一组系统性能参数可以获得最优测量值。第一种功能是模拟与另一功能相关的接口系统,使仿真过程更简单、准确。该方法通过多普勒理论来...
【文章来源】：兰州理工大学甘肃省
【文章页数】：85 页
【学位级别】：硕士
【文章目录】：
Abstract
摘要
LIST OF ACRONYMS
Chapter1 Introduction
1.1 Background
1.2 Vehicle safety systems background
1.2.1 Safety systems prevention
1.2.2 Preventive safety systems
1.3 Safety benefit and motivation
1.4 Context of the study
1.5 Problem statement
1.6 Objectives
1.7 Thesis contributions
1.8 Thesis organisation and outlines
Chapter2 Radar& Sensor Fusion(RSF)
2.1 Sensor Fusion
2.1.1 Accuracy
2.1.2 Reliability
2.1.3 Range and field view detection
2.1.4 Resolution and identification of target
2.1.5 System delay
2.2 Radar system
2.3 Radar equation
2.4 Doppler effect
2.5 Doppler radar
2.6 The CW doppler radar
2.7 Moving targets
2.8 Radar resolution
2.8.1 System delay
2.8.2 Bearing resolution
2.9 Radar accuracy
2.10 Radar applications
2.11 LIDAR sensor fusion
2.12 Lidar equation
2.13 Applications of LIDAR
2.14 Vision-based approach
Chapter3 Methodology and Models Analysis
3.1 Background
3.2 Vehicles safety approach
3.3 Data fusion
3.4 Energy minimization model
3.5 Purposed approach
3.6 Obstacle detection using cooperative fusion of laser and camera
3.7 Multi-target tracking(MTT)
3.7.1 Data association
3.7.2 State estimation
3.7.3 Track management
3.8 Comparison
Chapter4 Design of Data Fusion Model
4.1 Introduction
4.2 Simulation model
4.3 RSF interfacing design
4.4 Cooperative fusion results
4.4.1 Modelling sensor detections
4.4.2 Simulating radar detections
4.5 Summary
Chapter5 Summary&Concluding
5.1 Concluding
5.2 Future work
References
Acknowledgement
本文编号：3345129
【文章来源】：兰州理工大学甘肃省
【文章页数】：85 页
【学位级别】：硕士
【文章目录】：
Abstract
摘要
LIST OF ACRONYMS
Chapter1 Introduction
1.1 Background
1.2 Vehicle safety systems background
1.2.1 Safety systems prevention
1.2.2 Preventive safety systems
1.3 Safety benefit and motivation
1.4 Context of the study
1.5 Problem statement
1.6 Objectives
1.7 Thesis contributions
1.8 Thesis organisation and outlines
Chapter2 Radar& Sensor Fusion(RSF)
2.1 Sensor Fusion
2.1.1 Accuracy
2.1.2 Reliability
2.1.3 Range and field view detection
2.1.4 Resolution and identification of target
2.1.5 System delay
2.2 Radar system
2.3 Radar equation
2.4 Doppler effect
2.5 Doppler radar
2.6 The CW doppler radar
2.7 Moving targets
2.8 Radar resolution
2.8.1 System delay
2.8.2 Bearing resolution
2.9 Radar accuracy
2.10 Radar applications
2.11 LIDAR sensor fusion
2.12 Lidar equation
2.13 Applications of LIDAR
2.14 Vision-based approach
Chapter3 Methodology and Models Analysis
3.1 Background
3.2 Vehicles safety approach
3.3 Data fusion
3.4 Energy minimization model
3.5 Purposed approach
3.6 Obstacle detection using cooperative fusion of laser and camera
3.7 Multi-target tracking(MTT)
3.7.1 Data association
3.7.2 State estimation
3.7.3 Track management
3.8 Comparison
Chapter4 Design of Data Fusion Model
4.1 Introduction
4.2 Simulation model
4.3 RSF interfacing design
4.4 Cooperative fusion results
4.4.1 Modelling sensor detections
4.4.2 Simulating radar detections
4.5 Summary
Chapter5 Summary&Concluding
5.1 Concluding
5.2 Future work
References
Acknowledgement
本文编号：3345129
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