共查询到19条相似文献,搜索用时 125 毫秒
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针对混合视距/非视距环境中的移动节点定位,提出一种基于到达时间测量值和误差抑制的定位方案。首先,配备有超宽带无线电的节点随机移动,以收集到达时间测量数据,并执行最短路径距离选择算法得到包括一跳节点距离在内的非视距误差减小后的多跳节点距离;采用多维标度确定节点的初始位置;采用迭代三边测量法和误差积累管理相结合来获得定位节点位置。仿真实验结果表明,提出的定位方案的定位精确度优于其他几种常用方案。 相似文献
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针对室内定位,当信号受到非视距(non-line-of-sight, NLOS)和多径传播的影响时,本文提出一种接收信号强度(Received Signal Strength, RSS)协助的Ray-tracing室内定位算法,改进已经提出的基于虚拟基站方法的信号到达时间 (Time of Arrival, TOA)和信号到达角度(Direction of Arrival, DOA)室内无线信号Ray-tracing模型,利用信号RSS测量值优化算法,实现TOA、DOA和RSS协同定位,提高室内多径及非视距环境下,无线定位的精度,降低算法复杂度,提高算法处理信号多重散射的能力并降低了对基站的依赖性适用环境更为广泛。首先通过RSS得到信号源可能存在的位置,随后利用Ray-tracing原理并使用虚拟基站,将非视距路径定位问题转化为视距路径定位问题,利用TOA和DOA对直射、透射、反射和绕射情况进行分析建模,最后使用最小二乘法对可能的位置进行筛选,得到信号源的最终位置。仿真结果表明,本算法较改进前拥有更高的定位精度。 相似文献
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针对Bounding Box算法定位误差大、覆盖率低的缺点,提出了一种采用虚拟锚节点策略的改进定位算法。首先未知节点利用其通信范围内的锚节点进行定位;其次,已定位的节点根据升级策略有选择性的升级为虚拟锚节点;最后,无法定位的节点利用虚拟锚节点实现定位。另外,在离散网络模型的基础上,通过建立双半径网络节点模型从而进一步约束了未知节点的位置。理论分析及仿真结果均表明,该算法在显著提高定位覆盖率的同时,有效地提高了定位精度。 相似文献
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提出了一种基于锚节点功率调节的加权质心定位算法,通过锚节点的功率调节确定各个锚节点对于未知节点的影响力因子,并将其作为权重计算未知节点的位置,体现了不同锚节点为未知节点位置计算结果的影响.仿真表明,该算法减小了节点的平均定位误差,是一种适合于无线传感器网络的定位方法. 相似文献
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赵梦龙 《电子技术与软件工程》2021,(4):30-32
本文提出一种基于目标临时位置估计的无线网络残差幂次方加权定位算法。这种算法能够运用分组定位,获取不通目标位置节点的估计位置,并获得估计各位置之间的差值,临时定位残差与传统残差加权定位算法之间区别,在于本文提出残差幂次方作为加权函数,仿真获得最优化加权函数。结果发现在LOS-SN低于2时,本文提出无线定位方法的精度较传统非视距定位误差远远较小,提高了60%的定位精度,并且降低了对LOS-SN的个数要求。 相似文献
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为了提高非视距(NLOS)环境中的毫米波系统定位精度,基于分布式压缩感知理论,提出一种深度优先的多路径参数估计算法。通过估计出来的多径参数来识别NLOS路径,增强了定位性能。首先,使用深度优先算法来减少非必要的路径搜索,获得更加准确的多径参数。其次,采用反向定位距离残差的方法进行NLOS多径识别。然后,对NLOS路径中的散射体进行匹配,估计出散射体的位置并将其视为虚拟锚节点。结合基站与虚拟锚节点的信息实现定位增强。最后,对所提算法的定位性能进行了仿真,与距离加权最小二乘(LS)算法和最大鉴别变换(MDT)算法相比,所提算法的性能分别提升了17%和8%。 相似文献
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两种NLOS误差消除及TOA定位算法 总被引:2,自引:0,他引:2
在蜂窝网络定位中,由于NLOS环境造成的附加时延(NLOS误差)是导致定位精度下降的主要原因,本文将NLOS误差与系统测量误差合成的噪声分为均值部分和随机部分,利用卡尔曼滤波算法输出与噪声方差无关的特性,无需得到全部噪声方差的准确值,只利用系统测量噪声的方差,用卡尔曼滤波算法除随机部分,再根据噪声均值部分与移动台到基站距离的关系,提出了一种简单的最小二乘(LS)定位算法,或利用最优化方法进行定位;利用仿真实验得到滤波距离--误差先验信息,基于先验信息提出了第二种NLOS误差消除算法,再利用所提的最小二乘定位算法进行定位.仿真结果表明,本文提出的算法能够有效消除NLOS误差带来的影响,具有更高的定位精度与稳健性. 相似文献
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针对无线传感器网络在非视距(NLOS)环境下利用接收信号强度(RSS)定位存在精度不足的问题,提出了一种新的基于二阶锥规划(SOCP)的鲁棒性定位算法。在假定非视距偏差上界的基础上构建了对非视距偏差量具有鲁棒性的定位方程,从而抑制了非视距偏差的干扰;接着利用凸优化技术将鲁棒性的定位问题转化为二阶锥规划问题,达到精确估计的目的,进而提高定位精度;此外,将定位问题推广到未知发射功率的情况,提出了一个迭代SOCP的算法。仿真结果表明,所提出的算法有效地解决了非视距定位中存在的问题,且定位精度要优于以往的牛顿迭代法、UT法以及SOCP法。 相似文献
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Rajendran Mani Sasikala Jayaraman Mohan Ellappan 《International Journal of Communication Systems》2020,33(14)
The reliability of data dissemination in vehicular ad hoc network (VANET) necessitates maximized cooperation between the vehicular nodes and the least degree of congestion. However, non‐line of sight (NLOS) nodes prevent the establishment and sustenance of connectivity between the vehicular nodes. In this paper, a hybrid seagull and thermal exchange optimization (TEO) algorithm‐based NLOS node detection technique is proposed for enhancing cooperative data dissemination in VANETs. It inherits three different versions of the proposed hybridized algorithm; three different approaches for localization of NLOS nodes depending upon its distance from the reference nodes are incorporated. It is considered as a reliable attempt in effective NLOS node localization as it is predominant in maintaining the balancing the degree of exploration and exploitation in the search process. In the first variant, the method of the roulette wheel is utilized for selecting one among the two optimization algorithm. In the second adoption, this hybridization algorithm combines TEO algorithm only after the iteration of SEOA algorithm. In the final adoption, the predominance of the seagull attack mode is enhanced by including the heat exchange formula of TEO algorithms for improving exploitation capability. The simulation experiments of the proposed HS‐TEO‐NLOS‐ND scheme conducted using EstiNet 8.1 exhibited its reliability in improving the emergency message delivery rate by 14.86%, a neighborhood awareness rate by 13%, and the channel utilization rate by 11.24%, compared to the benchmarked techniques under the evaluation done with different number of vehicular nodes and NLOS nodes in the network. 相似文献
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针对当前室外蜂窝网多基站定位需要基站之间时间同步、数据同步的要求,以及NLOS环境造成的非服务区基站的信号可测性问题,该文提出基于B-LM圆环模型的NLOS信息约束单基站定位算法。首先根据散射体、目标和基站间的几何位置关系以及NLOS多路径信息构建定位方程,然后将定位方程转化为最小二乘优化问题,之后基于LM算法海森矩阵修正思想和拟牛顿2阶偏导构造思想提出B-LM算法,保证算法收敛于最优解,以得到目标位置。仿真结果表明,所提单基站定位算法能在宏蜂窝NLOS环境实现较高的定位精度。 相似文献
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Linear Least Squares (LLS) estimation is a low complexity but sub-optimum method for estimating the location of a mobile terminal (MT) from some measured distances. It requires selecting one of the known fixed terminals (FTs) as a reference FT for obtaining a linear set of expressions. In this paper, the choosing of the reference FT is investigated. By analyzing the objective function of LLS algorithm, a new method for selecting the reference FT is proposed, which selects the reference FT based on the minimum residual (denoted as MR-RS) rather than the smallest measured distance and improves the localization accuracy significantly in Line of sight (LOS) environment. In Non-line of sight (NLOS) environment, we combine MR-RS algorithm with two other existing algorithms (residual weighting algorithm and three-stage algorithm) to form new algorithms, which also improve the localization accuracy comparing with the two algorithms. Moreover, the time complexity of the proposed algorithms is analyzed. Simulation results show that the proposed methods are always better than the existing methods for arbitrary geometry position of the MT and the LOS/NLOS conditions. 相似文献
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The problem of locating mobile sensors has received considerable attention, particularly in the field of wireless communications. It is well-known that the presence of non-line-of-sight (NLOS) errors in the geo-location problem leads to severe degradation in the localization performance. In this paper, we propose a robust Bayesian method to mitigate the NLOS errors in location estimation of a single moving sensor, whereby the localization is performed using time-of-arrival (TOA) measurements. This method is based on the Markov chain Monte Carlo (MCMC) approach. Numerical simulations results illustrate the promising results of our method in a mixed line-of-sight (LOS) and NLOS environment. 相似文献
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该文提出一种适用于NLOS环境UWB多径信道下低复杂度的选择性RAKE接收机(RC-SRAKE),通过本地参考波形与接收信号的卷积抽样来确定SRAKE的Finger参数,不需要已知信道信息或信道估计过程,降低了复杂度。给出了RC-SRAKE误码率的表达式,分析了Finger数目和信道噪声对RC-SRAKE性能的影响。通过对IEEE.802.15.4a中NLOS信道的仿真实验表明,与能获得准确信道信息的理想SRAKE相比,在Finger数目较少的情况下RC-SRAKE能达到与之相近的性能。 相似文献
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In the process of indoor localization,the existence of the non-line of sight(NLOS)error will greatly reduce the localization accuracy.To reduce the impact of this error,a 3 dimensional(3D)indoor localization algorithm named LMR(LLS-Minimum-Residual)is proposed in this paper.We first estimate the NLOS error and use it to correct the measurement distances,and then calculate the target location with linear least squares(LLS)solution.The final nodes location can be obtained accurately by NLOS error mitigation.Our algorithm can work efficiently in both indoor 2D and 3D environments.The simulation results show that the proposed algorithm has better performance than traditional algorithms and it can significantly improve the localization accuracy. 相似文献