基于无线传感网的目标检测与跟踪系统研究

无线传感器网络能够实时检测和采集网络分布区域内的各种监测对象的信息,因此基于无线传感器网络的目标检测与跟踪系统研究成为当前的研究热点.在研究时差到达(TDOA)技术的基础上,设计了一种基于无线传感器网络的超声波和无线电相结合的小范围移动目标检测与跟踪系统,用基于距离和角度计算来精确定位,并根据定位信息绘制其轨迹图,达到检测与跟踪的目的.理论及实践证明了该方案的有效性,并有着广泛的应用前景.     

An algorithmic strategy for in-network distributed spatial analysis in wireless sensor networks

A wireless sensor network (WSN) can be construed as an intelligent, largely autonomous, instrument for scientific observation at fine temporal and spatial granularities and over large areas. The ability to perform spatial analyses over sensor data has often been highlighted as desirable in areas such as environmental monitoring. Whilst there exists research on computing topological changes of dynamic phenomena, existing proposals do not allow for more expressive in-network spatial analysis. This paper addresses the challenges involved in using WSNs to identify, track and report topological relationships between dynamic, transient spatial phenomena and permanent application-specific geometries focusing on cases where the geometries involved can be characterized by sets of nodes embedded in a finite 2-dimensional space. The approach taken is algebraic, i.e., analyses are expressed as algebraic expressions that compose primitive operations (such as Adjacent, or AreaInside). The main contributions are distributed algorithms for the operations in the proposed algebra and an empirical evaluation of their performance in terms of bit complexity, response time, and energy consumption.     

Contour tracking with automatic motion model switching

In this paper we present an efficient contour-tracking algorithm which can track 2D silhouette of objects in extended image sequences. We demonstrate the ability of the tracker by tracking highly deformable contours (such as walking people) captured by a static camera. We represent contours (silhouette) of moving objects by using a cubic B-spline. The tracking algorithm is based on tracking a lower dimensional shape space (as opposed to tracking in spline space). Tracking the lower dimensional space has proved to be fast and efficient. The tracker is also coupled with an automatic motion-model switching algorithm, which makes the tracker robust and reliable when the object of interest is moving with multiple motion. The model-based tracking technique provided is capable of tracking rigid and non-rigid object contours with good tracking accuracy.     

An In-Network Querying Framework for Wireless Sensor Networks

In contrast to traditional wireless sensor network (WSN) applications that perform only data collection and aggregation, the new generation of information processing applications such as pursuit-evasion games, tracking, evacuation, and disaster relief applications require in-network information storage and querying. Due to the resource limitations of WSNs, it is challenging to implement in-network querying in a distributed, lightweight, resilient, and energy-efficient manner. We address these challenges by exploiting location information and the geometry of the network and propose an in-network querying framework, namely, the Distributed Quad-Tree (DQT). DQT is distance sensitive for querying of an event: the cost of answering a query for an event is at most a constant factor (2sqrt{2} in our case) of the distance “d” to the event. DQT construction is local and does not require any communication. Moreover, due to its minimalist infrastructure and stateless nature, DQT shows graceful resilience to node failures and topology changes. Since event-based querying is inherently limited to the anticipated types of inquiries, we further extend our framework to achieve complex range-based querying. To this end, we use a multiresolution algorithm, which is optimal with respect to least square errors that models the data in a decentralized way. Our model-based scheme answers queries with approximate values accompanied by certainty levels with increased resolution at lower layers of the DQT hierarchy. Our analysis and experiments show that our framework achieves distance sensitivity and resiliency for event-based querying, as well as greatly reduces the cost of complex range querying.     

有源传感网络中目标跟踪的传感器调度方法

Wireless sensor network (WSN) of active sensors suffers from serious inter-sensor interference (ISI) and imposes new design and implementation challenges. In this paper, based on the ultrasonic sensor network, two time-division based distributed sensor scheduling schemes are proposed to deal with ISI by scheduling sensors periodically and adaptively respectively. Extended Kalman filter (EKF) is used as the tracking algorithm in distributed manner. Simulation results show that the adaptive sensor scheduling scheme can achieve superior tracking accuracy with faster tracking convergence speed.     

A Deformable Object Tracking Algorithm Based on the Boundary Element Method that is Robust to Occlusions and Spurious Edges

The manipulation of deformable objects is an important problem in robotics and arises in many applications including biomanipulation, microassembly, and robotic surgery. For some applications, the robotic manipulator itself may be deformable. Vision-based deformable object tracking can provide feedback for these applications. Computer vision is a logical sensing choice for tracking deformable objects because the large amount of data that is collected by a vision system allows many points within the deformable object to be tracked simultaneously. This article introduces a template based deformable object tracking algorithm, based on the boundary element method, that is able to track a wide range of deformable objects. The robustness of this algorithm to occlusions and to spurious edges in the source image is also demonstrated. A robust error measure is used to handle the problem of occlusion and an improved edge detector based on the Canny edge operator is used to suppress spurious edges. This article concludes by quantifying the performance increase provided by the robust error measure and the robust edge detector. The performance of the algorithm is also demonstrated through the tracking of a sequence of cardiac MRI images.     

Heuristic algorithm for finding boundary cycles in location-free low density wireless sensor networks

Wireless sensor networks (WSNs) comprise a large number of sensor nodes, which are spread out within a region to be monitored and communicate using wireless links. In some WSN applications, recognizing boundary nodes is important for topology discovery, geographic routing, tracking and guiding. In this paper, we study the problem of identifying the boundary nodes of a WSN. In a WSN, close-by nodes can establish direct communications with their neighbors and have the ability to estimate distances to nearby nodes, but not necessarily the true distances. Our objective is to find the boundary nodes by using only the connectivity relation and neighbor distance information without any other knowledge of node locations. Moreover, our main aim is to design a distributed algorithm that works even when the average degree is low. We propose a heuristic algorithm to find the boundary nodes which are connected in a boundary cycle of a location-free, low density (average degree 5–6), randomly deployed WSN. We develop the key ideas of our boundary detection algorithm in the centralized scenario and extend these ideas to the distributed scenario. The distributed implementation is more realistic for real WSNs, especially for sparse networks when all local information cannot be collected very well due to sparse connectivity. In addition, the distributed implementation can tolerate faults by recomputing the boundary locally when a boundary node is faulty. Simulations in ns-2 show that the distributed implementation outperforms the centralized one with higher quality of boundaries.     

基于粒子滤波的无线传感器网络目标跟踪算法

传感器节点的组织和路由对无线传感器网络(WSN)目标跟踪算法的性能有重大影响.为此,针对具有簇一树型网络拓扑结构的WSN,首先给出集中式粒子滤波跟踪算法(CPFTA)实现的具体步骤,然后提出一种分布式粒子滤波跟踪算法(DPFTA),构建性能评价体系,通过仿真实验给出两种跟踪算法的定量比较,结果表明DPFTA的跟踪精度稍低于CPFTA,但能大幅度减少通信开销,而且具有更小的跟踪反应时间;最后仿真分析了传感器覆盖密度和检测周值对跟踪算法性能的影响.     

An analytical study of central and in-network data processing for wireless sensor networks

This paper compares the performance of centralized and in-network data processing for wireless sensor networks (WSNs) under various deployment conditions on the real sensor hardware Sun SPOT from Sun Microsystems. We define several criteria to measure the quality of responses in WSN applications. Guided by an extensive experimental study, we discuss in detail the performance impacts of different deployment factors on algorithms that implement both centralized and in-network computing. Finally, performance guidelines are given to algorithm designers for WSN applications.     

An adaptive in-network aggregation operator for query processing in wireless sensor networks

A wireless sensor network (WSN) is composed of tens or hundreds of spatially distributed autonomous nodes, called sensors. Sensors are devices used to collect data from the environment related to the detection or measurement of physical phenomena. In fact, a WSN consists of groups of sensors where each group is responsible for providing information about one or more physical phenomena (e.g., group for collecting temperature data). Sensors are limited in power, computational capacity, and memory. Therefore, a query engine and query operators for processing queries in WSNs should be able to handle resource limitations such as memory and battery life. Adaptability has been explored as an alternative approach when dealing with these conditions. Adaptive query operators (algorithms) can adjust their behavior in response to specific events that take place during data processing. In this paper, we propose an adaptive in-network aggregation operator for query processing in sensor nodes of a WSN, called ADAGA (ADaptive AGgregation Algorithm for sensor networks). The ADAGA adapts its behavior according to memory and energy usage by dynamically adjusting data-collection and data-sending time intervals. ADAGA can correctly aggregate data in WSNs with packet replication. Moreover, ADAGA is able to predict non-performed detection values by analyzing collected values. Thus, ADAGA is able to produce results as close as possible to real results (obtained when no resource constraint is faced). The results obtained through experiments prove the efficiency of ADAGA.     

基于CPCRLB和一致性算法的分散式传感器管理

针对无线传感器网络中的目标跟踪问题,基于条件后验克拉美—罗下界（CPCRLB）提出一种分散式传感器节点管理方法．基于一致性策略给出一种CPCRLB的分布式迭代算法,并且基于分布式粒子滤波器给出该算法的数值逼近实现．对层次结构的无线传感器网络,将CPCRLB作为传感器管理的准则,基于平均一致性给出一种迭代的局部搜索算法,实现了无线传感器网络下观测节点的分散式在线选择．仿真结果表明了基于CPCRLB的分散式传感器管理方法在目标跟踪精度方面的有效性．     

基于改进 L-K 光流的 WebAR 信息可视分析方法

摘 要：信息可视化技术结合移动增强现实(MAR)技术在目标跟踪领域仍然存在设备计算 负载过大的问题。若仍坚持采用同跟踪平面图像特征点的方案来跟踪立体对象各角度的特征点, 则目标跟踪过程所需要获取的多角度特征点数据无疑会加重跟踪过程的计算压力,进而导致移 动设备负载过大,最终影响模型渲染,所渲染的模型常出现剧烈抖动、卡顿或运动滞后于目标 物的现象。针对上述问题,提出了一种基于改进的 L-K (Lucas-Kanade)光流跟踪算法的 WebAR (基于 Web 端的 MAR 技术)解决方案,将特征点的跟踪问题转化为光流估计问题以及一种优化 的三维信息可视化交互策略。实验结果表明,该方法能够提高 MAR 在跟踪目标时的计算效率 和稳定性,丰富信息可视化的呈现效果和交互方式。     

无线传感器网络基于分组协商的数字水印算法

无线传感器网络通常具有分布式数据采集与网内数据处理的特点,因此基于传统数字水印的安全技术难以直接用于传感器网络;针对传感器网络聚类分层的体系结构,通过在簇内建立分组协商机制来生成待嵌入水印,在此基础上实现了一种新的分布式数字水印算法。传感器节点以分组的形式嵌入水印,计算复杂度低,水印具有良好的抗攻击性和对有损压缩的鲁棒性。实验结果表明用该算法嵌入的水印可检测性强,能够成功地鉴别数据是否被非法篡改,保护传感器网络数据安全。     

A low-complexity sensor fusion algorithm based on a fiber-optic gyroscope aided camera pose estimation system

Visual tracking, as a popular computer vision technique, has a wide range of applications, such as camera pose estimation. Conventional methods for it are mostly based on vision only, which are complex for image processing due to the use of only one sensor. This paper proposes a novel sensor fusion algorithm fusing the data from the camera and the fiber-optic gyroscope. In this system, the camera acquires images and detects the object directly at the beginning of each tracking stage; while the relative motion between the camera and the object measured by the fiber-optic gyroscope can track the object coordinate so that it can improve the effectiveness of visual tracking. Therefore, the sensor fusion algorithm presented based on the tracking system can overcome the drawbacks of the two sensors and take advantage of the sensor fusion to track the object accurately. In addition, the computational complexity of our proposed algorithm is obviously lower compared with the existing approaches(86% reducing for a 0.5 min visual tracking). Experiment results show that this visual tracking system reduces the tracking error by 6.15% comparing with the conventional vision-only tracking scheme(edge detection), and our proposed sensor fusion algorithm can achieve a long-term tracking with the help of bias drift suppression calibration.     

基于分布式动态簇结构的WSN自适应目标跟踪算法

目标跟踪是无线传感器网络应用研究的一个重要问题,如何在传感器节点随机分布的条件下对目标进行实时、准确的跟踪,并尽可能地降低网络能耗是目标跟踪问题的一个难点。文章基于分布式动态簇结构和并行粒子滤波算法对目标进行跟踪,提出一种跟踪采样周期自适应调整算法来降低网络能耗,同时也提高了跟踪的稳定性。仿真结果表明,文章提出的算法达到了实时、准确和节能的要求,具有一定的实际应用价值。     

基于粒子滤波的分布式目标跟踪算法

根据无线传感器网络分布式目标跟踪的特性,提出一种改进粒子滤波算法。将簇内各节点最新的观测数据用极大似然估计法得到目标的状态信息,该信息作为参考分布更换粒子滤波部分粒子,引入模糊推理的数据融合方法为各个节点滤波结果分配不同权值,通过加权平均法得到目标的状态信息。仿真实验表明该算法能有效提高目标跟踪的精度。     

In-network wireless sensor network query processors: State of the art,challenges and future directions

In wireless sensor networks (WSNs), energy is valuable because it is scarce. This causes their life time to be determined by their ability to use the available energy in an effective and frugal manner. In most of the earlier sensor network applications, the main requirement consisted mainly of data collection but transmitting all of the raw data out of the network may be prohibitively expensive (in terms of communication) or impossible at given data collection rates.In the last decade, the use of the database paradigm has emerged as a feasible solution to manage data in a WSN context. There are various sensor network query processors (SNQPs) (implementing in-network declarative query processing) that provide data reduction, aggregation, logging, and auditing facilities. These SNQPs view the wireless sensor network as a distributed database over which declarative query processor can be used to program a WSN application with much less effort. They allow users to pose declarative queries that provide an effective and efficient means to obtain data about the physical environment, as users would not need to be concerned with how sensors are to acquire the data, or how nodes transform and/or transmit the data.This paper surveys novel approaches of handling query processing by the current SNQP literature, the expressiveness of their query language, the support provided by their compiler/optimizer to generate efficient query plans and the kind of queries supported. We introduce the challenges and opportunities of research in the field of in-network sensor network query processing as well as illustrate the current status of research and future research scopes in this field.     

无线传感器网络的路由算法研究

无线传感器网络能够实时监测和采集网络分布区域内的各种监测对象信息,有着广泛的应用前景.设计有效的路由算法来提高通信连接性、降低能量损耗、延长网络的生命周期成为无线传感器网络的核心问题.本文对无线传感器网络的各种典型路由算法进行分类,分析了各类算法的特点.通过结合各类路由算法的设计特点,提出一种适合于大规模网络的路由算法的设计,但仍需进一步改进和完善.仿真证明了该算法的有效性.     

Fusing force and vision feedback for manipulating deformable objects

This article describes a framework that fuses vision and force feedback for the control of highly deformable objects. Deformable active contours, or snakes, are used to visually observe changes in object shape over time. Finite‐element models of object deformations are used with force feedback to predict expected visually observed deformations. Our approach improves the performance of large, complex deformable contour tracking over traditional computer vision tracking techniques. This same approach of combining deformable active contours with finite‐element material models is modified so that a vision sensor, i.e., a charge‐coupled device (CCD) camera, can be used as a force sensor. By visually tracking changes in contours on the object, material deflections can be transformed into applied stress estimates through finite element modeling. Therefore, internal object stresses due to object manipulation can be visually observed and controlled, thus creating a framework for deformable object manipulation. A pinhole camera model is used to accomplish vision and force sensor feedback assimilation from these two sensing modalities during manipulation. © 2001 John Wiley & Sons, Inc.     

An enhanced edge tracking method using a low resolution tactile sensor

Edge detection plays an important role in object recognition and exploration. In this paper, we propose an efficient tracking algorithm, which uses a coarse resolution tactile sensor set, for edge detection of a 2D shape object. Although many researchers have often used a tactile sensor with high resolution such as a 10×10 or higher for edge detection, in this research, we use a 2×2 tactile sensor to track the edges of an object. Using this type of low resolution sensor, we can reduce the manufacturing cost of the sensor and simplify the calculation and control process. In our algorithm, we only need to control the sensor to make it move along the vertical axis, Oy, or the horizontal axis, Ox. The sensor is moved along a suitable direction according to the sensing signals receiving from it. A set of simulations for both convex and concave shapes has been done to verify the algorithm. In addition, methods to increase the accuracy of the algorithm are also discussed.