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无线传慼器网络是一门获取和处理信息的新兴技术.文章针对无线传感器网络节点定位问题进行了研究,提出了一种新的节点定位算法.方法是在传感器网络中预先部署十分少量已知位置信息的伪节点,然后通过时钟定位算法,实现对节点位置的估计.仿真显示该算法具有较好的实用性. 相似文献
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为了解决普适计算环境下室内外无缝定位问题,提出了一种卫星定位和无线传感器网络组合定位的算法.算法主要利用了GPS卫星定位系统伪距观测数据和无线传感器网络距离观测数据联合进行位置解算.仿真结果表明,算法与传统的GPS定位相比,增加定位的适应范围,实现少于4颗可用卫星情况下的定位;与无线传感器网络定位算法相比,提高了定位精度. 相似文献
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环境监测无线传感器网络节点定位算法研究 总被引:1,自引:0,他引:1
李忠成 《计算机应用与软件》2010,27(2):241-243,276
无线传感器网络节点的定位技术是其关键技术之一,具有十分重要的地位。传感器节点采集到的数据必须结合其位置信息才有意义。结合环境监测无线传感器网络,通过对节点定位的基本原理和近几年国内外典型定位算法的分析研究,采用信号强度测距(RSSI)方法对其进行节点定位。为了提高定位精度,进一步对该方法进行了算法改进及节点坐标修正,最终实现了对目标的有效定位。通过仿真结果分析比较表明该方法平均定位误差小,是一种可行的定位算法。 相似文献
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为了提高无线传感器网络( WSNs)使用寿命,对WSNs的目标跟踪方式进行研究,提出基于无迹Kalman滤波( UKF)的WSNs Sink节点动态跟踪算法,以实现高效节能的资源管理和利用方式。首先利用UKF算法对目标节点的下一位置进行预测,然后通过四圆区域定位交叉定位算法对Sink节点的位置区域进行局部准确定位。实验结果表明:这种动态的Sink节点预测定位算法能够有效缩短数据发射传感器和Sink点之间的距离,减少跳数,从而实现负载均衡降低能耗的效果。 相似文献
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传统无线传感器网络(WSNs)位置隐私保护方案难以解决安全性与网络能耗之间的均衡,为了提高网络隐私信息的安全性,提出一种鲁棒性强的无线传感器网络位置隐私保护方案.首先通过增加伪源节点和伪汇聚节点防止攻击者获得关键节点的位置信息;然后采用伪汇聚节点分组、概率丢弃冗余数据包降低网络资源消耗;最后在Matlab 2012平台下进行仿真对比实验.结果表明:该方案可以提高网络攻击事件检测率,降低网络时延,有效地保护源节点和汇聚节点的位置隐私. 相似文献
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针对无线传感器网络节点自身定位问题,提出一种新的节点定位算法,介绍算法的基本原理和实现方法。算法假设网络中有一定比例的锚节点(位置已知的节点)。通过未知节点和其无线射程范围内的锚节点之阃的通信约束和几何关系,得出该未知节点所处的圆弧区域,将该圆弧区域的质心作为未知节点的估计位置。该算法是一种完全基于网络连通性的无需测距技术的分布式算法,算法设计简单,计算量小。节点间通信开销少。仿真结果显示,该算法适合于各种规模的无线传感器网络的节点定位。 相似文献
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研究无线传感器网络在位置信息不确定时,同时定位无线传感器网络节点并跟踪移动目标。利用RSSI测量节点对之间的距离,多维定标技术根据距离矩阵完成传感器网络的初始定位。估计与更新阶段提出了压缩EKF滤波确定传感器节点位置和目标位置。仿真结果显示:算法在较低的网络覆盖率下有较高的定位和跟踪准确度,在初始定位误差为5m时,节点和跟踪误差均小于3m,特别是在长距离的跟踪任务中有很好的精度和实时性。 相似文献
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Device-free localization (DFL) is the method of using distributed wireless sensors to localize the target without carrying any devices. Existing DFL methods leverage the variation of narrowband received signal strength (NRSS) which is vulnerable to multipath fading, and thus results in considerable performance degradation in indoor environments. Moreover, the inefficient sensor deployment of traditional DFL involves huge human efforts, which is not suitable for emergency scenarios. In this paper, we utilize sensors transmitting ultra-wideband (UWB) signals to solve both problems. We proposed two RSS variation estimation methods based on the channel impulse response (CIR) measurements provided by UWB sensors, which turn out to be more robust to multipath than NRSS due to the fine multipath resolution of UWB signals. We also employ a higher operating frequency to enhance the shadowing loss for mitigating the multipath effect. Additionally, satisfactory sensor self-localization is achieved under the cooperative localization framework owing to the accurate ranging capability of UWB sensors. We conducted experiments in three different environments to explore the feasibility of our method. The results show that the proposed method gains much better localization performance and requires less human efforts than narrowband DFL. 相似文献
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针对免携带设备定位DFL( Device Free Localization)精度低,近距离定位目标不易区分等问题,提出了一种结合菲涅尔理论的定位估计方法。该方法首先通过无线层析成像RTI( Radio Tomographic Imaging)原理,粗定位出人体目标位置,其次计算环境参量,划分限制区域,考虑肩宽、头宽等具体人体参数,对限制域中满足菲涅尔理论的位置点进行拟合加权,实现精确定位;在出现近距离目标时,对比人体参数的实验值与理论值,判断是否为多目标。实测数据下的定位仿真结果表明,与传统的RTI方法相比,该方法在定位的准确度上提高了30%,同时实现了近距离目标数目的判决。 相似文献
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针对基于接收信号强度指数(Received Signal Strength Indicator,RSSI)的多目标定位问题,结合点估计与椭圆估计算法,提出一种新的分布式多边融合定位(Distributed Multi-lateral Fusion Localization,DMFL)算法.首先,通过多边定位算法进行粗定位,估计目标的大致位置.其次,基于区间分析理论在线获取泰勒展式高阶余项的边界,并通过集员递归算法求解多目标定位问题.最后,通过实验和仿真验证该算法的定位性能.结果表明,在相同的节点布置条件下,与最新的RSSI定位算法相比,该算法的定位精度更高,最大误差小于0.3 m,并可提供保证包含目标真实位置的最优区域. 相似文献
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This work explores the novel use of Bayesian compressive sensing (BCS) in radio tomographic imaging (RTI), which aims at addressing the performance degradation of shadow fade imaging due to multipath interferences, through the sophisticated efforts on enhancing BCS with the capability of heterogeneous-noise-variance learning. Our contribution is twofold. Firstly, we incorporate a hierarchical model of heterogeneous noise variances into sparse Bayesian learning, which can contribute to the enhancement of BCS in terms of noise-variance awareness. Then, under our enhanced BCS (namely heterogeneous BCS) framework, we develop two learning algorithms for the RTI reconstruction. Theoretical analysis will show the potential advantages of using our heterogeneous BCS in mitigating the effect of multipath interferences, as well as in improving the RTI performance with our learning algorithms. Finally, the experimental results in the context of device-free localization and tracking are reported to demonstrate the effectiveness of the proposed approach. 相似文献
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Due to the low cost and capabilities of sensors, wireless sensor networks (WSNs) are promising for military and civilian surveillance of people and vehicles. One important aspect of surveillance is target localization. A location can be estimated by collecting and analyzing sensing data on signal strength, time of arrival, time difference of arrival, or angle of arrival. However, this data is subject to measurement noise and is sensitive to environmental conditions, so its location estimates can be inaccurate. In this paper, we add a novel process to further improve the localization accuracy after the initial location estimates are obtained from some existing algorithm. Our idea is to exploit the consistency of the spatial–temporal relationships of the targets we track. Spatial relationships are the relative target locations in a group and temporal relationships are the locations of a target at different times. We first develop algorithms that improve location estimates using spatial and temporal relationships of targets separately, and then together. We prove mathematically that our methods improve the localization accuracy. Furthermore, we relax the condition that targets should strictly keep their relative positions in the group and also show that perfect time synchronization is not required. Simulations were also conducted to test the algorithms. They used initial target location estimates from existing signal-strength and time-of-arrival algorithms and implemented our own algorithms. The results confirmed improved localization accuracy, especially in the combined algorithms. Since our algorithms use the features of targets and not the underlying WSNs, they can be built on any localization algorithm whose results are not satisfactory. 相似文献
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