Description: 无线传感器网络中移动节点定位仿真程序。采用基于序列蒙特卡洛方法进行移动节点定位。-Wireless sensor network node localization in mobile simulation program. Monte Carlo method based on the sequence of positioning mobile nodes. Platform: |
Size: 50176 |
Author:netest08 |
Hits:
Description: 无线传感器网络 CAB定位仿真程序
这是无线传感器节点定位CAB算法的仿真程序，由matlab完成-Wireless sensor network simulation program CAB positioning is CAB localization algorithm for wireless sensor nodes in the simulation program, completed by the matlab Platform: |
Size: 1024 |
Author:范玉红 |
Hits:
Description: Estimating the positions of sensor nodes is a fundamental and
crucial problem in ad hoc wireless sensor networks (WSNs).
In this paper, an accurate node localization method for WSNs
is devised based on the weighted least squares technique with
the use of time-of-arrival measurements. Computer simulations
are included to evaluate the performance of the proposed
approach by comparing with the classical multidimensional
scaling method and Cram´ er-Rao lower bound. Platform: |
Size: 518144 |
Author:pravin jadhav |
Hits:
Description: 此Matlab程序为IEEE TRANSACTIONS ON SIGNAL PROCESSING信号源被动定位与跟踪领域经典文章“An Approximately Efficient TDOA Localization Algorithm in Closed-Form for Locating Multiple Disjoint Sources With Erroneous Sensor Positions”的实现程序，该算法实现在感知节点位置错误时利用TDOA信息对多个目标联合定位的目的！-This Matlab program for the IEEE TRANSACTIONS ON SIGNAL PROCESSING source areas passive localization and tracking classic article " An Approximately Efficient TDOA Localization Algorithm in Closed-Form for Locating Multiple Disjoint Sources With Erroneous Sensor Positions" of the implementation process, the algorithm in location-aware nodes error using TDOA information for the purpose of co-locating multiple targets! Platform: |
Size: 503808 |
Author:haobenjian |
Hits:
Description: 提出了基于无线传感器网络的浮标网络水下GPS定位系统模型，分析了
该模型的结构、功能以及工作过程，并从几何角度探讨了水下目标的声学定位算
法。结合Range-Free算法与分布式算法的思想，设计了一种传感器节点自定位算
法，称为BSR（Beacons Signal Ring）定位算法，并对该算法的性能进行了评估与
比较。该算法在锚节点处的信标信号中引入能量等级的机制，无需相邻传感器节
点间信息交换，有效降低了算法复杂度与通信开销。性能分析结果显示，该算法
性能良好，在应用环境下相比于APIT算法与质心算法具有更低的位置估计误差。
论文还研究了基于双元检测传感器的协作式的目标跟踪策略，对相应的跟踪过程
进行了描述。提出了使用加权质心算法的目标位置估计模型，以及线性预测机制，
使跟踪过程具有较小的计算和通信代价。-In this thesis,we presents a buoy network of underwater GPS positioning system
model based on the wireless sensor network.The structure,function and process in the
model were analyzed.Underwater target acoustic localization algorithm were explored
through geometry way.Combined with the idea of Range-Free algorithm and distributed
algorithm,a sensor nodes self-localization algorithm were designed,which called BSR
(Beacons Signal Ring)localization algorithm,the algorithm performance evaluation and
comparison has also been presented.The algorithm use a small number of anchor nodes.
Each anchor emits beacons at different power levels.This mechanism does not required
information exchange between neighboring sensors,and reduced the complexity of the
algorithm and communication overhead effectively.The results of performance analysis
showed that BSR provides a lower position estimation error than APIT and Centroid
under a wide range of conditions.The thesis introduced process of ta Platform: |
Size: 1416192 |
Author:lq |
Hits:
Description: Monitoring applications define an important
class of applications used in wireless sensor networks.
In these applications the network perceives
the environment and searches for event
occurrences (phenomena) by sensing different
physical properties, such as temperature, humidity,
pressure, ambient light, movement, and presence
(for target tracking). In such cases the
location information of both phenomena and
nodes is usually required for tracking and correlation
purposes. In this work we summarize most
of the concepts related to localization systems for
WSNs as well as how to localize the nodes in
these networks (which allows the localization of
phenomena). By dividing the localization systems
into three distinct components — distance/angle
estimation, position computation, and localization
algorithm — besides providing a didactic
viewpoint, we show that these components can
be seen as subareas of the localization problem
that need to be analyzed and studied separately. Platform: |
Size: 134144 |
Author:ginanjar |
Hits:
Description: 针对基本无线传感器网络DV-Hop定位算法中，计算平均跳距时产生偏小误差的原因，提出了基于平均跳距修正的DV-Hop算法。改进算法中，引入信标节点个数比例、所有信标节点平均跳距的最大值以及所有信标节点平均跳距的平均值三个因子，并采用它们对平均跳距进行修正。通过Matlab软件对算法进行仿真验证，结果表明，改进后的 DV-Hop 算法有效降低了未知节点的定位误差，是一种可行的无线传感器网络节点定位解决方案。-DV-Hop localization algorithm for wireless sensor networks, we calculate the average hop distance small error of reasons, raised the DV-Hop algorithm based on the average hop distance correction. Improved algorithm, the proportion of the number of nodes, the introduction of beacons, the beacon node average maximum jump distance as well as all the beacon nodes average jump from the average of three factors, and their average hop distance correction. Matlab software simulation results show that the improved DV-Hop algorithm effectively reduce the unknown node positioning error, the solution is a viable wireless sensor network node positioning algorithm. Platform: |
Size: 3072 |
Author:Lisa |
Hits:
Description: 质心定位算法源码，分三种情况考虑，只有锚节点，被定位到的未知节点也作为锚节点，有邻居锚节点的未知节点只利用邻居锚节点进行定位，没有邻居锚节点的未知节点才利用已经定位了的邻居未知节点进行定位。
-Centroid localization algorithm source，Three cases to consider.Only the anchor nodes,unknown nodes to be positioned as anchor nodes,neighbor anchor node of the unknown node using only neighbor anchor node positioning, not unknown neighbor anchor node node neighbor has positioned the unknown node positioning. Platform: |
Size: 435200 |
Author:yidianyuan |
Hits:
Description: 提供多种路由方式，能很好对比节点间的定位效果，可以绘出节点的定位误差和节点间的连接图。-Offers a variety of routing can be a good contrast between the nodes positioning effect, you can draw the connection diagram of the the node positioning error and node. Platform: |
Size: 6569984 |
Author:l7114161 |
Hits:
Description: Ns2 localization code which is used to find the location of nodes through reference nodes Platform: |
Size: 34816 |
Author:loganathan |
Hits:
Description: 定位技术是无线传感器网络中关键的基础支撑技术, 目前提出了许多静态网络的节点定位算
法, 移动无线传感器网络的定位研究相对较少. 针对定位节点和参考节点随机运动的网络模型, 提出了
一个基于动态网格划分的蒙特卡罗定位算法. 算法中当接收的参考节点数超过一定阈值时使用最远距
离节点选择模型, 选出部分参考节点参与定位和信息转发, 节约能耗. 接着基于选择的或所有接收的参
考节点构建采样区域, 进行网格划分, 使用网格单元数计算最大采样次数, 在采样区域内采样并使用误
差补偿的运动模型进行过滤, 提高了采样效率, 减少了计算开销, 并保证了较好的定位精度. 仿真实验表
明算法在定位精度, 计算开销、能耗等方面都具有较好的性能.-Positioning technology is critical in wireless sensor networks based supporting technologies, currently made many static network node localization algorithms, the positioning of mobile wireless sensor network research is relatively small. Locate node and a reference node for random motion network model, proposed a Dynamic meshing based Monte Carlo localization algorithm. algorithm when the received reference nodes exceeds a certain threshold, the most distant node selection model selects some reference nodes involved locating and forwarding information, save energy. then based on the selection or building all received reference node sampling area, meshing, the number of grid cells used to calculate the maximum sampling frequency, the sampling area sampling and using motion model error compensation filter to improve sampling efficiency, reducing the computational overhead and to ensure a better positioning accuracy. Simulation experiments show that the algorithm in positioning accuracy, Platform: |
Size: 576512 |
Author:Jeff |
Hits:
Description: Wireless Sensor Networks have been proposed for a multitude of
location-dependent applications. For such systems, the cost and
limitations of the hardware on sensing nodes prevent the use of
range-based localization schemes that depend on absolute pointto-
point distance estimates. Because coarse accuracy is sufficient
for most sensor network applications, solutions in range-free
localization are being pursued as a cost-effective alternative to
more expensive range-based approaches. Platform: |
Size: 224256 |
Author:ali |
Hits:
Description: Localization in wireless sensor networks is the process of determining the geographical positions of
sensors. Only some of the sensors (anchors) in the networks have prior knowledge about their geographical
positions. Localization algorithms use the location information of anchors and estimates
of distances between neighbouring nodes to determine the positions of the rest of the sensors. Platform: |
Size: 1506304 |
Author:vinod |
Hits:
Description: wireless sensor network is large scale sensor network . it consists of hundred or thousand of sensor nodes Platform: |
Size: 1965056 |
Author:wlafifi
|
Hits:
Description: 通过随机部署信标节点来定位目标，当距离最近三个信标节点之间相互连接时，出现在信标节点组成的网格内，可以定位目标对象(The target object is located by the random deployment of beacon nodes. When the nearest three beacon nodes are connected to each other, the target object can be located in the grid of the beacon nodes.) Platform: |
Size: 6707200 |
Author:running |
Hits:
Description: 改进DV-Hop定位算法
首先设置初始量，布置了一个范围为100×100m2的区域，其上随机分布100个传感器节点，其中有10个信标节点，节点的通信半径为30m。
第二步在正方形区域内产生均匀分布的随机拓扑，随机产生节点坐标并将其中十个选定为信标节点，其余九十个设为未知节点，然后画出节点分布图。
第三步通过最短路径法计算未知节点与每个信标节点的最小跳数。
第四步根据前面记录的其他信标节点的位置信息和相距跳数估算平均每跳的实际距离，用跳数估计距离的方法得出未知节点到信标节点的距离。
第五步用极大似然估计法求未知节点坐标
(Improved DV-Hop localization algorithm first set the initial amount, layout 100100m2 the area of a range of 100 sensor nodes randomly distributed on the 10 beacon node, the node communication radius of 30m. The second step in the square area to generate uniformly distributed random topology, random coordinates of the nodes and ten of the selected beacon node, the remaining 90 is set to unknown node, and then draw the node distribution diagram. The third step is to calculate the minimum number of hops of the unknown node and each beacon node through the shortest path method. The fourth step according to the location information of the other beacon nodes in the previous record and away from hops to estimate the average hop distance and hop count to estimate the distance to come to the distance of the unknown node to beacon nodes. The fifth step maximum likelihood estimation method and the unknown coordinates of the nodes) Platform: |
Size: 1024 |
Author:robinkk4 |
Hits:
Description: 基于TOA测量和DOA测量的目标节点定位可以比RSS测量获得更高精度的位置参数(The location of target nodes based on TOA and DOA measurement can obtain higher precision position parameters than RSS measurement) Platform: |
Size: 92160 |
Author:你好track |
Hits:
Search - localization of nodes