在车载自组织网VANETs(vehicular ad hoc networks)中,高动态的拓扑结构和频繁断裂的链路给车间通信提出挑战。为此,针对VANETs城市场景,提出基于方向矢量角簇群和桥节点的车间通信VAC-BNR(Vector-angle-cluster and bridge nodes-based...在车载自组织网VANETs(vehicular ad hoc networks)中,高动态的拓扑结构和频繁断裂的链路给车间通信提出挑战。为此,针对VANETs城市场景,提出基于方向矢量角簇群和桥节点的车间通信VAC-BNR(Vector-angle-cluster and bridge nodes-based routing)协议。VAC-BNR协议将城市道路划分为十字路口区域和十字路口间的直线路段区域。在十字路口区域内,选择合适的车辆作为桥节点,并由桥节点连通断裂的链路。而在直线路段区域,利用矢量角将车辆划分不同的簇群,然后计算每个簇群内节点的效用值,并选择效用值最高的车辆传输数据。仿真结果表明,提出的VAC-BNR协议能够有效地降低端到端传输时延、提高数据包传递率。与AMD相比,VAC-BNR协议的平均端到端传输时延下降了约30%,当车流密度大于80辆/km^2时,数据包传递率提高了约50%。展开更多
在车载自组织网(vehicular ad hoc networks,VANET)中,高动态的拓扑结构和频繁断裂的链路给车间通信提出挑战。为此,针对VANET城市场景,提出基于方向矢量角簇群和桥节点的路由(vector-angle-cluster and bridge nodes-based routing,VAC...在车载自组织网(vehicular ad hoc networks,VANET)中,高动态的拓扑结构和频繁断裂的链路给车间通信提出挑战。为此,针对VANET城市场景,提出基于方向矢量角簇群和桥节点的路由(vector-angle-cluster and bridge nodes-based routing,VAC-BNR)协议。VAC-BNR协议将城市道路划分为十字路口区域和十字路口间的直线路段区域。在十字路口区域内,选择合适的车辆作为桥节点;并由桥节点连通断裂的链路。而在直线路段区域,利用矢量角将车辆划分不同的簇群,然后计算每个簇群内节点的效用值;并选择效用值最高的车辆传输数据。仿真结果表明,提出的VAC-BNR协议能够有效地降低端到端传输时延、提高数据包传递率。与AMD相比,VAC-BNR协议的平均端到端传输时延下降了约30%,当车流密度大于80辆/km^2时,数据包传递率提高了约50%。展开更多
We propose a method based on the Poynting vector that combines angle-domain imaging and image amplitude correction to overcome the shortcomings of reverse-time migration that cannot handle different angles during wave...We propose a method based on the Poynting vector that combines angle-domain imaging and image amplitude correction to overcome the shortcomings of reverse-time migration that cannot handle different angles during wave propagation. First, the local image matrix （LIM） and local illumination matrix are constructed, and the wavefield propagation directions are decomposed. The angle-domain imaging conditions are established in the local imaging matrix to remove low-wavenumber artifacts. Next, the angle-domain common image gathers are extracted and the dip angle is calculated, and the amplitude-corrected factors in the dip angle domain are calculated. The partial images are corrected by factors corresponding to the different angles and then are superimposed to perform the amplitude correction of the final image. Angle-domain imaging based on the Poynting vector improves the computation efficiency compared with local plane-wave decomposition. Finally, numerical simulations based on the SEG/EAGE velocity model are used to validate the proposed method.展开更多
为解决当前OFDM网络信号误差限制算法难以消除窄带莱斯噪声干扰,且单纯采用一次发射机制存在精度较低等问题,提出了一种基于环正交腔体噪声消除机制的OFDM网络信号误差限制算法.首先,对OFDM信号进行离散化,并依据信号投影矢量及窄带莱...为解决当前OFDM网络信号误差限制算法难以消除窄带莱斯噪声干扰,且单纯采用一次发射机制存在精度较低等问题,提出了一种基于环正交腔体噪声消除机制的OFDM网络信号误差限制算法.首先,对OFDM信号进行离散化,并依据信号投影矢量及窄带莱斯噪声投影矢量在全频谱上的投影,按极坐标旋转方式构建了环正交腔体噪声消除结构,实现了信号投影矢量与窄带莱斯噪声投影矢量的正交分离,提高了信号投影矢量的投影效率,减少信号投影矢量与噪声投影矢量的重叠现象,降低了信号发射过程中出现的信号衰落水平;随后,依据信源信号投影矢量与信道状态投影矢量的夹角误差,采取极大似然估计,构建矢量角度误差控制机制,并通过拉普拉斯窗函数估计方法,进一步改善了信道传输过程中的角度衰落,降低了传输误码率.仿真实验表明:与当前常用的矢量线性积分误差消除机制(Vector Integral Error Elimination Mechanism,VIEE机制)及预发射累计误差控制机制(Prelaunch Accumulative Error Control Mechanism,PAEC机制)相比,本文算法具有更低的传输误码率与更强的抗衰落性能.展开更多
Accuracy of angle-domain common-image gathers(ADCIGs)is the key to multiwave AVA inversion and migration velocity analysis,and of which Poynting vectors of pure P-and S-wave are the decisive factors in obtaining multi...Accuracy of angle-domain common-image gathers(ADCIGs)is the key to multiwave AVA inversion and migration velocity analysis,and of which Poynting vectors of pure P-and S-wave are the decisive factors in obtaining multi-component seismic data ADCIGs.A Poynting vector can be obtained from conventional velocity-stress elastic wave equations,but it focused on the propagation direction of mixed P-and S-wave fields,and neither on the propagation direction of the P-wave nor the direction of the S-wave.The Poynting vectors of pure P-or pure S-wave can be calculated from first-order velocity-dilatation-rotation equations.This study presents a method of extracting ADCIGs based on first order velocitydilatation-rotation elastic wave equations reverse-time migration algorithm.The method is as follows:calculating the pure P-wave Poynting vector of source and receiver wavefields by multiplication of P-wave particle-velocity vector and dilatation scalar,calculating the pure S-wave Poynting vector by vector multiplying S-wave particle-velocity vector and rotation vector,selecting the Poynting vector at the time of maximum P-wave energy of source wavefield as the propagation direction of incident P-wave,and obtaining the reflected P-wave(or converted S-wave)propagation direction of the receiver wavefield by the Poynting vector at the time of maximum P-(S-)wave energy in each grid point.Then,the P-wave incident angle is computed by the two propagation directions.Thus,the P-and S-wave ADGICs can obtained Numerical tests show that the proposed method can accurately compute the propagation direction and incident angle of the source and receiver wavefields,thereby achieving high-precision extraction of P-and S-wave ADGICs.展开更多
文摘在车载自组织网VANETs(vehicular ad hoc networks)中,高动态的拓扑结构和频繁断裂的链路给车间通信提出挑战。为此,针对VANETs城市场景,提出基于方向矢量角簇群和桥节点的车间通信VAC-BNR(Vector-angle-cluster and bridge nodes-based routing)协议。VAC-BNR协议将城市道路划分为十字路口区域和十字路口间的直线路段区域。在十字路口区域内,选择合适的车辆作为桥节点,并由桥节点连通断裂的链路。而在直线路段区域,利用矢量角将车辆划分不同的簇群,然后计算每个簇群内节点的效用值,并选择效用值最高的车辆传输数据。仿真结果表明,提出的VAC-BNR协议能够有效地降低端到端传输时延、提高数据包传递率。与AMD相比,VAC-BNR协议的平均端到端传输时延下降了约30%,当车流密度大于80辆/km^2时,数据包传递率提高了约50%。
文摘在车载自组织网(vehicular ad hoc networks,VANET)中,高动态的拓扑结构和频繁断裂的链路给车间通信提出挑战。为此,针对VANET城市场景,提出基于方向矢量角簇群和桥节点的路由(vector-angle-cluster and bridge nodes-based routing,VAC-BNR)协议。VAC-BNR协议将城市道路划分为十字路口区域和十字路口间的直线路段区域。在十字路口区域内,选择合适的车辆作为桥节点;并由桥节点连通断裂的链路。而在直线路段区域,利用矢量角将车辆划分不同的簇群,然后计算每个簇群内节点的效用值;并选择效用值最高的车辆传输数据。仿真结果表明,提出的VAC-BNR协议能够有效地降低端到端传输时延、提高数据包传递率。与AMD相比,VAC-BNR协议的平均端到端传输时延下降了约30%,当车流密度大于80辆/km^2时,数据包传递率提高了约50%。
基金sponsored by the Natural Science Fund of Heilongjiang Province(No.F201404)
文摘We propose a method based on the Poynting vector that combines angle-domain imaging and image amplitude correction to overcome the shortcomings of reverse-time migration that cannot handle different angles during wave propagation. First, the local image matrix （LIM） and local illumination matrix are constructed, and the wavefield propagation directions are decomposed. The angle-domain imaging conditions are established in the local imaging matrix to remove low-wavenumber artifacts. Next, the angle-domain common image gathers are extracted and the dip angle is calculated, and the amplitude-corrected factors in the dip angle domain are calculated. The partial images are corrected by factors corresponding to the different angles and then are superimposed to perform the amplitude correction of the final image. Angle-domain imaging based on the Poynting vector improves the computation efficiency compared with local plane-wave decomposition. Finally, numerical simulations based on the SEG/EAGE velocity model are used to validate the proposed method.
文摘为解决当前OFDM网络信号误差限制算法难以消除窄带莱斯噪声干扰,且单纯采用一次发射机制存在精度较低等问题,提出了一种基于环正交腔体噪声消除机制的OFDM网络信号误差限制算法.首先,对OFDM信号进行离散化,并依据信号投影矢量及窄带莱斯噪声投影矢量在全频谱上的投影,按极坐标旋转方式构建了环正交腔体噪声消除结构,实现了信号投影矢量与窄带莱斯噪声投影矢量的正交分离,提高了信号投影矢量的投影效率,减少信号投影矢量与噪声投影矢量的重叠现象,降低了信号发射过程中出现的信号衰落水平;随后,依据信源信号投影矢量与信道状态投影矢量的夹角误差,采取极大似然估计,构建矢量角度误差控制机制,并通过拉普拉斯窗函数估计方法,进一步改善了信道传输过程中的角度衰落,降低了传输误码率.仿真实验表明:与当前常用的矢量线性积分误差消除机制(Vector Integral Error Elimination Mechanism,VIEE机制)及预发射累计误差控制机制(Prelaunch Accumulative Error Control Mechanism,PAEC机制)相比,本文算法具有更低的传输误码率与更强的抗衰落性能.
基金financially supported by the Fundamental Research Funds for the Central Universities(No.201822011)the National Key R&D Program of China(No.2018YFC1405900)+1 种基金the National Natural Science Foundation of China(Nos.41674118 and 41574105)the National Science and Technology Major Project(No.2016ZX05027002)。
文摘Accuracy of angle-domain common-image gathers(ADCIGs)is the key to multiwave AVA inversion and migration velocity analysis,and of which Poynting vectors of pure P-and S-wave are the decisive factors in obtaining multi-component seismic data ADCIGs.A Poynting vector can be obtained from conventional velocity-stress elastic wave equations,but it focused on the propagation direction of mixed P-and S-wave fields,and neither on the propagation direction of the P-wave nor the direction of the S-wave.The Poynting vectors of pure P-or pure S-wave can be calculated from first-order velocity-dilatation-rotation equations.This study presents a method of extracting ADCIGs based on first order velocitydilatation-rotation elastic wave equations reverse-time migration algorithm.The method is as follows:calculating the pure P-wave Poynting vector of source and receiver wavefields by multiplication of P-wave particle-velocity vector and dilatation scalar,calculating the pure S-wave Poynting vector by vector multiplying S-wave particle-velocity vector and rotation vector,selecting the Poynting vector at the time of maximum P-wave energy of source wavefield as the propagation direction of incident P-wave,and obtaining the reflected P-wave(or converted S-wave)propagation direction of the receiver wavefield by the Poynting vector at the time of maximum P-(S-)wave energy in each grid point.Then,the P-wave incident angle is computed by the two propagation directions.Thus,the P-and S-wave ADGICs can obtained Numerical tests show that the proposed method can accurately compute the propagation direction and incident angle of the source and receiver wavefields,thereby achieving high-precision extraction of P-and S-wave ADGICs.
