Target tracking based on the extended H-infinity filter in wireless sensor networks

In this paper, we propose a new target tracking approach for wireless sensor networks (WSNs) by using the extended H-infinity filter. First, the extended H-infinity filter for nonlinear discrete-time systems is deduced through the Krein space analysis scheme. Then, the proposed extended H-infinity filtering algorithm is applied to target tracking in wireless sensor networks. Finally, experiments are conducted through a small wireless sensor network test-bed. Both experimental and simulation results illustrate that the extended H-infinity filtering algorithm is more accurate to track a moving target in wireless sensor networks than using the extended Kalman filter in the case of having no knowledge of the statistics of the environment and the target to be tracked.     

无线传感器网络及其应用

As a result of combination of microsensor technology, low power computing and wireless networking,wireless sensor networks are becoming an active branch of computer science. In this paper, we introduce the up-to-date research work of wireless sensor networks. First, we simply introduce the background of producing wireless sensor networks. Then, we describe their characteristics and application scopes. Finally we suggest the research direction in wireless sensor networks in the future.     

Reliable beacon transmission based MAC protocol for LR-WPANs over WLAN interferences

The use of IEEE 802.15.4 standard based application systems has been rapidly increasing, for example, in medical services, sensor networks, public safety systems, and home automation systems. However, issues arise from the fact that IEEE 802.15.4 standard based low rate wireless personal area networks （LR-WPANs） use the same frequency bands as wireless local area networks （WLANs）, and they interfere with each other. Based on past research on this issue, the interference has a more serious impact on LR-WPANs＇ performance than on WLANs＇ performance. In this paper we propose a method to improve LR-WPANs＇ performance while coexisting with WLANs, which is called the reliable beacon transmission based medium access control （MAC） protocol. Since the reliability of a beacon frame is important, in this method, only the beacon frame is transmitted in interference-free channels, and the data packets are transmitted in interfered channels instead of abandoning the channels altogether. This method increases the reliability of beacon frames as well as overall channel utilizations. The effectiveness of the proposed method was evaluated through extensive simulations, and this paper proves that this method improves the performance of IEEE 802.15.4 based wireless sensor networks （WSNs） over WLANs＇ interferences.     

A minimum-energy path-preserving topology control algorithm for wireless sensor networks

The topology control strategies of wireless sensor networks are very important for reducing the energy consumption of sensor nodes and prolonging the life-span of networks. In this paper, we put forward a minimum-energy path-preserving topology control （MPTC） algorithm based on a concept of none k-redundant edges. MPTC not only resolves the problem of excessive energy consumption because of the unclosed region in small minimum-energy communication network （SMECN）, but also preserves at least one minimum-energy path between every pair of nodes in a wireless sensor network. We also propose an energy-efficient reconfiguration protocol that maintains the minimum-energy path property in the case where the network topology changes dynamically. Finally, we demonstrate the performance improvements of our algorithm through simulation.     

Scoped Bellman-Ford Geographic Routing for Large Dynamic Wireless Sensor Networks

Routing is a fundamental problem in wireless sensor networks. Most previous routing protocols are challenged when used in large dynamic networks as they suffer from either poor scalability or the void problem. In this paper,we propose a new geographic routing protocol,SBFR(Scoped Bellman-Ford Routing),for large dynamic wireless sensor networks. The basic idea is that each node keeps a view scope of the network by computing distance vectors using the distributed BellmanFord method,and maintains a cost for routing to the sink. When forwarding a packet,a node picks the node with minimum cost in its routing table as a temporary landmark. While achieving good scalability,it also solves the void problem in an efficient manner through the combination of Bellman-Ford routing and cost-based geographic routing. Analytical and simulation results show that SBFR outperforms other routing protocols not only because of its robustness and scalability but also its practicality and simplicity.     

Scan of the Issue

In recent years, there have been rapid advances in sensor, sensor-on-a-chip, MEMS and wireless communication technologies. Now. massively distributed sensor networks are capable of linking people and the physical world together, providing platforms for information to be collected, shared, and processed in unprecedented ways. It is commonly recognized that sensor network research will lead to smart sentient spaces for our home and environment, work and leisure. It can help us to fight against disasters, protect us from hazards, and strengthen our defense. For the past few years, sensor networks research     

Energy saving in wireless sensor networks

With the development of low-cost processor, memory, and radio technologies, it becomes possible to build inexpensive wireless micro-sensor nodes. However, energy is the biggest constraint to wireless sensor capabilities and such constraint combined with a typical deployment of large numbers of sensor nodes have posed many challenges to the design and management of sensor networks. Due to their ad-hoc deployment in hazardous environment, once sensor nodes are deployed in a sensor network, they cannot be easily replaced or recharged. Thus, energy saving acts as one of the hottest topics in wireless sensor networks （WSNs） and hence several energy conservation schemes have been proposed in the literature. In this work, we will make a short survey on the main techniques used for energy conservation in sensor networks. Specifically, we will focus primarily on duty cycling schemes which represent the most suitable technique for energy saving. Moreover, we will also survey in-network processing and network coding techniques which can guarantee a significant amount of energy saving in packet transmission. Finally, we will make a review on some communication protocols proposed for sensor networks.     

An energy-driven unequal clustering protocol for heterogeneous wireless sensor networks

Due to the limitation of energy resources, energy efficiency is a key issue in wireless sensor networks (WSNs). Clustering is proved to be an important way to realize hierarchical topology control, which can improve the scalability and prolong the lifetime of wireless sensor networks. In this paper, an energy-driven unequal clustering protocol (EDUC) for heterogeneous wireless sensor networks is proposed. EDUC includes an unequal clustering algorithm and an energy-driven adaptive cluster head rotation method. The unequal size of clusters can balance the energy consumption among clusters, and the energy-driven cluster head rotation method can achieve the balance of energy consumption among nodes within a cluster, which reduces the waste of energy. Simulation experiments show that EDUC balances the energy consumption well among the cluster heads and prolongs the network lifetime.     

Dynamic cluster head for lifetime efficiency in WSN

Saving energy and increasing network lifetime are significant challenges in wireless sensor networks （WSNs）. In this paper, we propose a mechanism to distribute the responsibility of cluster-heads among the wireless sensor nodes in the same cluster based on the ZigBee standard, which is the latest WSN standard. ZigBee supports ad hoc on-demand vector （AODV） and cluster-tree routing protocols in its routing layer. However, none of these protocols considers the energy level of the nodes in the network establishing process or in the data routing process. The cluster-tree routing protocol supports single or multi-cluster networks. However, each single cluster in the multi-cluster network has only one node acting as a cluster head. These cluster-heads are fixed in each cluster during the network lifetime. Consequently, using these cluster-heads will cause them to die quickly, and the entire linked nodes to these cluster-heads will be disconnected from the main network. Therefore, the proposed technique to distribute the role of the cluster head among the wireless sensor nodes in the same cluster is vital to increase the lifetime of the network. Our proposed technique is better in terms of performance than the original structure of these protocols. It has increased the lifetime of the wireless sensor nodes, and increased the lifetime of the WSN by around 50% of the original network lifetime.     

无线传感网络中安全密钥管理机制

Recent advancements in wireless communication and microchip techniques have accelerated the development of wireless sensor networks (WSN). Key management in WSN is a critical and challenging problem because of the inner characteristics of sensor networks: deployed in hostile environments, limited resource and ad hoc nature. This paper investigates the constraints and special requirements of key management in sensor network environment, and some basic evaluation metrics are introduced. The key pre-distribution scheme is thought as the most suitable solution for key management problem in wireless sensor networks. It can be classified into four classes: pure probabilistic key predistribution, polynomial-based, Blom′s matrix-based, and deterministic key predistribution schemes. In each class of methods, the related research papers are discussed based on the basic evaluation metrics. Finally, the possible research directions in key management are discussed.     

Distributed classification of acoustic targets in wireless audio-sensor networks

Target tracking is an important application for wireless sensor networks. One important aspect of tracking is target classification. Classification helps in selecting particular target(s) of interest. In this paper, we address the problem of classification of moving ground vehicles. The basis of classification are the audible signals produced by these vehicles. We present a distributed framework to classify vehicles based on features extracted from acoustic signals of vehicles. The main features used in our study are based on FFT (fast Fourier transform) and PSD (power spectral density). We propose three distributed algorithms for classification that are based on the k-nearest neighbor (k-NN) classification method. An experimental study has been conducted using real acoustic signals of different vehicles recorded in the city of Edmonton. We compare our proposed algorithms with a naive distributed implementation of the k-NN algorithm. Performance results reveal that our proposed algorithms are energy efficient, and thus suitable for sensor network deployment.     

基于数据融合的战场声目标识别系统算法研究

现代战争越来越多地使用高科技武器,各种武器车辆坦克的声音相互混叠,进行声目标识别是极有挑战性的.为了在嘈杂的战场环境中多传感器网络仍能正确识别各种目标信号,结合无线多传感器网络的特点和数据融合理论,设计出了适合于战场环境的声目标识别算法.使用小波包进行预处理及特征提取,人工神经网络进行分类识别,并运用数据融合算法得出最终识别结果.通过对采集到的声目标信号进行识别,结果表明方法应用于战场声目标识别中是可行有效的.     

WSNs中基于隐马尔科夫模型的目标识别问题研究

由于无线传感器网络（Wireless Sensor Networks,WSNs）资源受限,如何有效利用资源,提高目标辨别的准确度,是WSNs中目标识别系统的研究难题。以隐马尔科夫模型为分类框架,对一个声音传感器阵列节点簇内的目标识别问题进行建模;基于节点信号的空间关联性,改进了子节点Viterbi最大似然序列的计算状态,设置了子节点报送间隔,从而有效地判别局部状态。实验证明,改进后的算法在维持判别正确率的同时降低信息传输量10%以上。     

无线传感器网络的短距声通信方法研究

在无线传感器网络(WSNs)所处环境中,由于强电磁或短距无线通信频率共存的原因,传感器节点间的短距无线通信常常会受到干扰甚至中断。针对这个问题,研究了一种短距声通信方式,将信号调制于声信号上,通过空气中声信号的传播来完成节点之间的数据通信。设计了用于验证声通信方法的实验系统结构;介绍了微分相移键控(DPSK)调制与解调原理及相关Matlab程序流程、输出与接收放大电路设计。进行了声通信实验,在室内环境时,声通信的最佳距离为2 m,室外环境时,声通信的最佳距离为5 m,最佳波特率均为294 bps。实验数据表明:本系统所设计的声通信方法是可行的。     

小波变换的无缝钢轨垂向应变信号分离

分析钢轨垂向应变信号基线漂移产生的原因,并采用小波变换对垂向应变信号进行分解与重构,分离信号中由温度引起的应变与轮轨力产生的应变.在Matlab环境下对分布式钢轨应力检测技术与无线传感网系统数据库中垂向应变信号进行处理,结果表明,该方法可以有效地分离信号中的不同成分.     

无线传感器网络分布式多目标跟踪算法研究

由于无线传感器网络的资源有限,集中式多目标跟踪算法在无线传感器网络多目标跟踪中受到限制.在无线声学传感器网络下,基于动态分簇结构,提出了一种分布式多目标跟踪算法.每个传感器的测量为来自单个目标或多个目标的声音信号和环境噪声的叠加.在跟踪过程中,每个目标对应于一个粒子滤波,当目标之间的距离较远时,进行单目标跟踪.当目标之...     

Autonomous wireless radar sensor mote for target material classification

Autonomous wireless sensor networks consisting of different types of sensor modalities have been receiving greater attention from researchers due to their versatility and portability. These autonomous sensor networks commonly include passive sensors such as infrared, acoustic, vibration, and magnetic nodes. However, fusion of active sensors in the integrated sensor network, such as Doppler radars, may offer powerful capabilities for many different sensing and classification tasks. In this work, we demonstrate the design and implementation of an autonomous wireless sensor network integrating a Doppler sensor with commercial off-the-shelf components. We investigate the effect of various types of target materials on the measured radar signal as one of the applications of the newly designed radar–mote network. Different types of materials affect the amount of energy reflected back to the source of an electromagnetic wave. We obtain mathematical and simulation models for the reflectivity of different homogeneous non-conducting materials and study the effect of such reflectivity on the classification of targets. We validate our simulation results using real experimental data collected through our autonomous radar–mote sensor network using various types of targets.     

基于BP神经网络的车辆声音信号识别

声音信号包含着很多的信息量,且获取比较方便.近年来,声音识别技术被广泛应用于各个领域,有着重要的意义.本文主要介绍了小波理论和BP神经网络识别算法.通过对采集到的不同类型车辆的声音信号进行分析和预处理,采用小波变换提取低维的特征参数,构建并成功训练一个三层BP神经网络,从而有效地识别出了车型.     

无线传感器网络中声震信号的特征提取算法

面向无线传感器网络在地面目标声震信号识别方面的应用需求,提出基于局域判别基(Local Discriminant Bases,LDB)算法的特征提取方法.并且,针对现有的基于时频能量图的可分性测度的缺点,提出新的基于概率密度估计的相对微分熵的可分性测度.基于实地采集到的信号的仿真实验表明,该方法在一定程度上提高了目标的正确识别率,降低了特征维数,具有实际的应用价值.     

一种WSN下的Mean Shift跟踪算法*

为有效地利用无线传感器网络跟踪移动目标,提出了一种基于高斯混合模型的Mean Shift跟踪算法。该算法运用高斯混合模型描述网络区域内目标信号分布的统计特征,利用Mean Shift区分目标信号与环境噪声,并对目标进行定位与跟踪。仿真实验结果表明,该算法在网络存在较大噪声,特别是网络存在大量异常传感器节点读数的情况下,定位精度高、受异常传感器节点读数影响较小。较之以往无线传感器网络目标跟踪算法,该算法具有更好的鲁棒性。