基于RFID的智能跟踪机器人的设计

针对国内各种智能机器人的智能跟踪难这一现状,设计出一种基于RFID技术的智能跟踪的机器人,能实现对携有特定电子标签的目标进行实时跟踪。该机器人以STC89C51单片机为核心,采用有源RFID读写器(HR6020C)和电子标签(WS-HT06)构建定位系统,采用单片机控制L298来驱动机器人的两个后轮,整个系统通过单片机进行整合、计算、处理数据,并发出指令,控制机器人对目标进行跟踪,进而达到机器人的智能跟踪的目的。实验结果表明,该机器人达到了智能跟踪的要求。     

改进内测点测试算法在无线传感网络中的定位研究

在无线传感网络定位算法中,三角形内点测试APIT算法和最佳三角内测点PIT算法受节点密度影响较大,在特定情况下会出现In-To-Out Error 和 Out-To-In Error错误,导致目的节点实际坐标往往与三角重叠区域质心位置相差较远,影响定位精准度。本文提出利用内测点三角成形面积有效检测和避免上述两类错误,并在重叠区域采取指纹分布概率以投票方式计算目的节点坐标。仿真实验证明,新算法受节点密度影响较小,拥有更高的定位精度和准确性。     

基于TinyOS的无线传感器网络AODV路由协议的实现与优化

针对无线传感器网络在矿山物联网的应用,本文提出了AODV路由协议在TinyOS操作系统下的实现框架,设计了数据帧、路由表与路由缓存机制。本文针对传统型AODV协议的丢包率与跳数之间呈级数增长的问题,分析了多跳衰减的原因,提出了一种基于RSSI的改进型无线传感器网络RSSI-AODV协议,采用RSSI作为路径选择的依据。实际测试表明：七跳链路总丢包率低至0.3%,优于传统AODV路由协议性能。     

Autonomous localization based energy saving mechanism in indoor MANETs using ACO

The biggest challenge in MANETs is to find most efficient routing due to the changing topology and energy constrained battery operated computing devices. It has been found that Ant Colony Optimization (ACO) is a special kind of optimization technique having characterization of Swarm Intelligence (SI) which is highly suitable for finding the adaptive routing for such a type of volatile network. The proposed ACO routing algorithm uses position information and energy parameters as a routing metric to improve the performance and lifetime of network. Typical routing protocols have fixed transmission power irrespective of the distance between the nodes. Considering limiting factors, like small size, limited computational power and energy source, the proposed solution excludes use of GPS for identifying the distance between nodes for indoor MANETs. The distance between nodes can be determined by using Received Signal Strength Indicator (RSSI) measurements. Thus, an intelligent ACO routing algorithm with location information and energy metric is developed to adaptively adjust the transmission power and distribute the load to avoid critical nodes. Proposed Autonomous Localization based Eligible Energetic Path_with_Ant Colony Optimization (ALEEP_with_ACO) algorithm ensures that nodes in the network are not drained out of the energy beyond their threshold, as the load is shared with other nodes, when the energy of a node in the shortest path has reached its threshold. Hence, the total energy expenditure is reduced, thus prolonging the lifetime of network devices and the network. We simulated our proposal and compared it with the classical approach of AODV and other biological routing approaches. The results achieved show that ALEEP_with_ACO presents the best Packet Delivery Ratio (PDR), throughput and less packet drop specially under high mobility scenarios.     

无线传感网络节点隶属度模糊定位算法研究

无线传感网络RSSI算法定位精度很高,但易受环境干扰。本文针对其不足,提出基于节点隶属度模糊算法,并应用于RSSI定位模型之中。新算法首先利用岭形分布对RSSI初始信号模糊化取得隶属函数,再根据隶属度近似程度反馈求精,通过隶属程度以逐渐逼近方式计算节点坐标区域。仿真实验结果证明,与RSSI和DV-Hop算法相比,新算法可以减少环境干扰和信号波动带来的影响,具有更高的定位精度和稳定性。     

Differential received power measurements over off-body links for obstruction-resilient pedestrian navigation

In this paper, we aim at improving pedestrian navigation experience based on standard narrow-band wireless technologies and simple radio metrics. The proposed solution takes benefits from body shadowing effects traditionally experienced at body-worn devices, for instance over off-body radio links with respect to fixed elements of infrastructure. The main idea is to infer relative angular information between the carrying body's heading and the received signal's direction of arrival. For this purpose, we consider differential received power measurements with judiciously placed on-body nodes. In comparison with related state-of-the-art contributions, a much lighter on-the-fly self-calibration procedure is made possible, based on the full-scale dynamics of the observed power measurements. We also describe a new algorithm that jointly estimates the body's absolute position and orientation, while benefiting from the body's movement continuity over time. The overall solution is validated by means of field experiments with IEEE 802.15.4-compliant devices operating at 2.4 GHz. Overall, the system is shown to be resilient, not only against self-shadowing effects generated by carrying bodies, but also against occasional obstructions caused by moving pedestrians in the vicinity (e.g., in crowded environments).     

基于垂直平分线的非测距定位算法

在无线传感器网络定位机制中,近似三角形内点测试(APIT)定位算法因思想简单、硬件成本低、定位精度高而被广泛应用,但算法性能会因锚节点分布不均匀受到严重影响。为提高节点定位精度和解决APIT定位算法边缘效应的问题,提出一种基于垂直平分线的非测距定位算法。该算法利用接收信号强度指示值(RSSI)值筛选锚节点并与等腰三角形底边中垂线过顶点的几何原理结合进行定位,可以得到比较合理的定理精度,性能相对稳定。仿真结果表明,该算法可有效提高无线传感器网络定位的精度和覆盖率。     

RSSI-based hybrid algorithm for real-time tracking in underground mining by using RFID technology

Knowing the precise and real-time location of underground mining workers is essential for their health and safety in any emergency. However, the standard Global Positioning System (GPS) is insufficient for such indoor environments as it requires new infrastructure based on different technologies and algorithms. Instead, Radio Frequency Identification (RFID)-based real-time indoor localization systems and a hybrid algorithm are developed. The received-signal-strength (RSS) based positioning techniques are investigated and applied in indoor environments. A unique hybrid approach based on fingerprinting is proposed and developed to solve the disadvantages of the existing techniques. Consequently, the accuracy of this one-of-a-kind algorithm is found to be 2.52 m in an office and 3.13 m in an underground mine. We also compared the proposed hybrid algorithm to the Weighted K-Nearest Neighbor (WKNN). WKNN, on the other hand, has an accuracy of 4.01 m in the office and 4.33 m in underground mining environments.     

基于RSSI的无线传感器网络定位系统设计与实现

基于窄带无线信号的路径损耗和阴影衰落,直接建立多个锚节点接收信号强度指示(Received Signal Strength Indication, RSSI)值与待定位节点未知坐标估计量的解析关系,避免传统RSSI定位方法中常用的对两节点距离量的直接求解,减少信息丢失,提高定位精度。仿真分析了锚节点数量、遮挡因子、路径损耗指数等对定位精度的影响。采用CC2530无线传感芯片实现基于RSSI的无线传感器网络(Wireless Sensor Network, WSN)定位系统。系统采用8个锚节点分别在边长4米和10米的两个正方形区域内展开定位实际测试,结果显示其平均定位误差可分别降到0.175米和0.824米。     

基于四节点RSSI的三维空间定位算法

针对提高室内三维空间的定位精度和速度的问题,从减少节点数量、建立特定坐标系的角度提出了一种基于四节点和特定坐标系的三维空间定位算法。该算法引入位置相对固定的四个节点,提高解算速度;充分考虑有效反射区对衰减指数影响,根据伯鲁斯特角将天线辐射场区分为叠加加强区和叠加减弱区,建立三维坐标系进行定位,结合信号强度指示(Received Signal Strength Indicator, RSSI)衰减模型,在叠加减弱区定位,把三维空间问题转化到二维空间,降低定位算法的复杂度。文中分别阐述方法的原理与验证,结果表明,四节点定位算法的解算速度比降低复杂度(Complexity-Reduced Trilateration Approach , COLA)定位算法有较大提高,该算法平均定位误差小于2米。