计算机应用研究2024，Vol.41Issue(6)：1722-1727,6.DOI:10.19734/j.issn.1001-3695.2023.10.0525
基于测距与GNSS信息融合的车联网协同定位技术
Cooperative positioning in vehicular networks based on fusion of ranging and GNSS information
摘要
Abstract
In order to enhance the accuracy of vehicle positioning in the Internet of Vehicles,this paper proposed a collabora-tive positioning method for the Internet of Vehicles based on fusing vehicle-mounted radar ranging information with GNSS infor-mation.This method established a mathematical model using the maximum likelihood estimation strategy,which essentially solved a nonlinear optimization problem.It simplified the problem as a quadratic programming problem with multiple quadratic constraints,presented a semi-definite relaxation method to efficiently approximate the original problem,and used the eigenva-lue decomposition method to further improve the approximate solution.Simulation results demonstrate that the accuracy of the collaborative positioning achieved by this information fusion method significantly improves compared to the linearized weighted least squares method.It can also achieve the positioning accuracy of BP(back propagation)neural network localization method based on a large dataset,without the need for pre-training the model,enabling high-precision real-time positioning.关键词
车联网/协同定位/车载雷达测距/半正定松弛Key words
Internet of Vehicles/cooperative positioning/vehicle radar ranging/semi-definite relaxation分类
信息技术与安全科学引用本文复制引用
屈小媚,王世法,谭屈山,黄海峰,焦育威,魏川棣..基于测距与GNSS信息融合的车联网协同定位技术[J].计算机应用研究,2024,41(6):1722-1727,6.基金项目
国家自然科学基金面上项目(61873217) （61873217）
新一代人工智能国家科技重大专项(2022ZD0115600) （2022ZD0115600）
