智能车联网下的车辆激光测距停车技术研究
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摘要
在车辆辅助停车中受到障碍物对回波的阻挡,导致对车辆方位的估计和测距性能不好,为了提高车辆辅助驾驶停车的智能性,提出一种基于回波探测和波束形成的智能车联网下的车辆激光测距停车技术。构建智能车联网下的车辆激光测距的信号回波探测模型,采用激光波束形成技术进行车辆的回波信号聚集处理。根据探测回波的谱峰进行车辆距离和方位参数的准确估计,根据车辆的激光定位结果进行速度和转向的自动调节和控制,结合空间MUSIC算法进行车辆距离的自适应估算,采用联合参数估计方法,在智能车联网环境下进行车辆激光测距的多维参量估计,提高辅助停车中的测距准确性。仿真结果表明,采用该方法进行智能车联网下的车辆激光测距准确性较高,参数估计精度得到提升,车辆激光测距停车的可靠性较好。
In order to improve the intelligence of vehicle assisted driving parking,the obstacle obstructs the echo wave in vehicle assisted parking,which leads to the poor performance of vehicle azimuth estimation and ranging. A vehicle laser ranging and parking technique based on echo detection and beam-forming is proposed in this paper. The signal echo detection model of vehicle laser ranging based on intelligent vehicle network is constructed,and the laser beam forming technique is used to process the echo signal of vehicle. The vehicle distance and azimuth parameters are estimated accurately according to the spectral peak of the detected echo,the speed and steering are automatically adjusted and controlled according to the laser location results of the vehicle,and the self-adaptive estimation of the vehicle distance is carried out in combination with the spatial MUSIC algorithm. Using the method of joint parameter estimation,the multi-dimensional parameter estimation of vehicle laser ranging is carried out under the environment of intelligent vehicle networking,which improves the accuracy of ranging in auxiliary parking. The simulation results show that the accuracy of vehicle laser ranging is higher,the precision of parameter estimation is improved,and the reliability of vehicle laser ranging and parking is better.
In order to improve the intelligence of vehicle assisted driving parking,the obstacle obstructs the echo wave in vehicle assisted parking,which leads to the poor performance of vehicle azimuth estimation and ranging. A vehicle laser ranging and parking technique based on echo detection and beam-forming is proposed in this paper. The signal echo detection model of vehicle laser ranging based on intelligent vehicle network is constructed,and the laser beam forming technique is used to process the echo signal of vehicle. The vehicle distance and azimuth parameters are estimated accurately according to the spectral peak of the detected echo,the speed and steering are automatically adjusted and controlled according to the laser location results of the vehicle,and the self-adaptive estimation of the vehicle distance is carried out in combination with the spatial MUSIC algorithm. Using the method of joint parameter estimation,the multi-dimensional parameter estimation of vehicle laser ranging is carried out under the environment of intelligent vehicle networking,which improves the accuracy of ranging in auxiliary parking. The simulation results show that the accuracy of vehicle laser ranging is higher,the precision of parameter estimation is improved,and the reliability of vehicle laser ranging and parking is better.
引文
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[3]徐丽媛,何杰,王然,等.不依赖于精确初始坐标的车联网相对定位坐标估计算法[J].计算机学报,2017,40(7):1583-1599.
[4] LIU Y.Joint resource allocation in SWIPT-based multi-antenna decode-and-forward relay networks[J]. IEEE Transactions on Vehicular Technology,2017,66(10):9192-9200.
[5] DU C,CHEN X,LEI L.Energy-efficient optimisation for secrecy wireless information and power transfer in massive MIMO relaying systems[J].IET Communications,2017,11(1):10-16.
[6] ZHU X,LU Y,HAN J,et al.Transmission reliability evaluation for Wireless Sensor Networks[J]. International Journal of Distributed Sensor Networks,2016,6(2):1-4.
[7] WANG W,CHEN Y,ZHANG Q,et al. Less Transmissions, More Throughput:Bringing Carpool to Public WLANs[J]. IEEE Transactions on Mobile Computing,2016,15(5):1168-1181.
[8]胡荣娜,郭爱煌.车联网中基于功率控制的传输可靠性算法[J].计算机应用,2015,35(6):1523-1526.
[9]梁生,刘腾飞,盛新志,等基于空间域差分的φ-OTDR光纤分布式扰动传感器定位方法研究[J].红外与激光工程,2016,45(6):622005-0622005(5).
[10] LI Z,CHEN Y,SHI H,et al.NDN-GSM-R:a novel high-speed railway communication system via Named Data Networking[J].Eurasip Journal on Wireless Communications&Networking,2016,16(1):48-52.
[11] XIE K,HU B,SINGH C.Reliability Evaluation of Double12-Pulse Ultra HVDC Transmission Systems[J]. IEEE Transactions on Power Delivery,2016,31(1):210-218.
[12]陆兴华,彭意达.基于回波探测的汽车防撞系统智能测距方法[J].电子测量技术,2016,39(6):126-129.
[13]徐正平,沈宏海,许永森.直接测距型激光主动成像系统发展现状[J].中国光学,2015,8(1):28-38.
[14]刘衍聪,刘本良,战祥华,等.激光熔覆层结合强度测试方法研究及装置设计[J].应用激光,2016,36(6):641-648.
[15]宋凯楠,王彪,唐超颖.基于激光测距扫描的室内定位方法研究[J].激光与红外,2016,46(8):938-942.
[16] EVANGELIO R H,PATZOLD M,and KELLER I. Adaptively splitted GMM with feedback improvement for the task of background subtraction[J]. IEEE Transactions on Information Forensics and Security,2014,9(5):863-874.
[17]谢斌,陈乙利,冯裕松,等.RFID识别技术的车联网智能信息终端研究[J].工程技术:引文版,2016(3):00287-00287.
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