Robust Kalman Filtering for Discrete-Time Systems With Measurement Delay

This brief is concerned with robust Kalman filtering for linear discrete-time systems with both instantaneous and single delayed measurements. The norm-bounded parameter uncertainties enter into the system matrix of the state space model. A new approach through the re-organization of measurements is proposed to improve the efficiency of computation. A sufficient condition for the existence of a robust Kalman filter is derived. The performance is clearly demonstrated through analytical results and simulation experiments.     

Robust Color Demosaicking With Adaptation to Varying Spectral Correlations

Almost all existing color demosaicking algorithms for digital cameras are designed on the assumption of high correlation between red, green, blue (or some other primary color) bands. They exploit spectral correlations between the primary color bands to interpolate the missing color samples, but in areas of no or weak spectral correlations, these algorithms are prone to large interpolation errors. Such demosaicking errors are visually objectionable because they tend to correlate with object boundaries and edges. This paper proposes a remedy to the above problem that has long been overlooked in the literature. The main contribution of this work is a hybrid demosaicking approach that supplements an existing color demosaicking algorithm by combining its results with those of adaptive intraband interpolation. This is formulated as an optimal data fusion problem, and two solutions are proposed: one is based on linear minimum mean-square estimation and the other based on support vector regression. Experimental results demonstrate that the new hybrid approach is more robust and eliminates the worst type of color artifacts of existing color demosaicking methods.      

Synchronization in Complex Dynamical Networks With Random Sensor Delay

This brief proposes a new complex dynamical network model, in which nodes are connected by measured outputs experiencing the random sensor delay. This model is totally different from some existing network models. Then, synchronization in the proposed network model is analyzed by the stochastic stability theory. A sufficient synchronization condition is given to ensure that the proposed network model is exponentially mean-square stable. Theoretical analysis and numerical simulation fully verify the main results.      

基于LMI的时变时滞Cohen-Grossberg神经网络鲁棒稳定性

 研究了时变时滞Cohen-Grossberg神经网络的全局鲁棒稳定性问题.基于线性矩阵不等式技术,给出了保证时变时滞Cohen-Grossberg神经网络平衡点唯一性和全局鲁棒稳定性的新判据.这些新判据不依赖于时滞的大小和放大函数,且与现有的一些结果相比,具有易于验证、适用范围广、条件更不保守等特点.仿真结果验证了本文方法的有效性.     

Robust Gain Scheduling Synchronization Method for Quadratic Chaotic Systems With Channel Time Delay

In this paper, a general robust gain scheduling synchronization method is proposed for quadratic chaotic systems with parametric uncertainty and unknown channel time delay. Quadratic systems contain nonlinearity of quadratic form of the systems' states and can always be transformed into linear parameter-varying (LPV) forms. Based on the LPV forms, our approach provides two different gain scheduling structures to achieve global synchronization under the case of having parametric uncertainty and time delay. The convergence of synchronization errors is demonstrated using Lyapunov stability theory.      

En-Route Filtering Techniques in Wireless Sensor Networks: A Survey

Wireless Personal Communications - Majority of wireless sensor networks (WSNs) are deployed in unattended environments and thus sensor nodes can be compromised easily. A compromised sensor node can...     

EETC: Energy Efficient Tree-Clustering in Delay Constrained Wireless Sensor Network

Wireless Personal Communications - Joint employment of multi-hop data forwarding and mobile data-collector is a popular technique for efficient data collection in energy constraint and delay...     

Optimal Power and Rate Control for Minimal Average Delay: The Single-User Case

Contemporary wireless systems combine aspects of network theory such as scheduling, throughput, and delay as well as information theory aspects such as capacity, coding, and power control. Design of such systems requires joint optimization of both network and physical layers. In this paper, we analyze a single-user communication system composed of a transmitter preceded by a queue used for retransmissions, Gaussian block-fading channel, and a receiver. The system average delay is optimized by using combined power/rate control under average power constraints. Dynamic programming is used for calculating the optimized policies using numerical analysis as well as analytic analysis for asymptotically large buffer size. Asymptotic results are obtained for all combinations of fixed or variable power and rate controls. The most important result extends the "water-filling" result for systems with average delay constraint     

Tracking in Wireless Sensor Networks Using Particle Filtering: Physical Layer Considerations

In this paper, a new framework for target tracking in a wireless sensor network using particle filters is proposed. Under this framework, the imperfect nature of the wireless communication channels between sensors and the fusion center along with some physical layer design parameters of the network are incorporated in the tracking algorithm based on particle filters. We call this approach ldquochannel-aware particle filtering.rdquo Channel-aware particle filtering schemes are derived for different wireless channel models and receiver architectures. Furthermore, we derive the posterior Cramer-Rao lower bounds (PCRLBs) for our proposed channel-aware particle filters. Simulation results are presented to demonstrate that the tracking performance of the channel-aware particle filters can reach their theoretical performance bounds even with relatively small number of sensors and they have superior performance compared to channel-unaware particle filters.     

夹角式强度反射型光纤声传感器

介绍了一种基于反射式强度型光纤传感原理的光纤声传感器,该传感器通过光纤模块将发射光纤和接收光纤的夹角固定为60°,同时采用基于微加工技术制作的反射振动膜片敏感声音信号并调制光信号强度.建立了该传感器的理论模型,并通过仿真和实验分析得到系统的最佳工作距离为8 μm,灵敏度为2.49 μW/μm.实验测试结果表明,该声传感器样机对声音的探测灵敏度为30 mV/Pa,同时给出了样机的频率响应及线性度测试结果.     

极化敏感阵列滤波性能分析:完全极化情形

本文研究了完全极化情形下极化敏感阵列滤波性能.期望信号和干扰信号来自任意方向,并且任意极化,推导获得阵列最大输出信号干扰噪声比SINR,它是空间匹配系数和极化匹配系数的函数.与普通阵列相比较,极化敏感阵列不仅可以在空域滤波,而且可以在极化域滤波.当干扰和期望信号到达角差别较大时,阵列通过调整方向特性抑制干扰、增强信号;当干扰信号和期望信号到达角接近时,仍然可以利用它们极化状态的差异提高SINR.对于干扰方来讲,要想获得较好的干扰效果,干扰信号必须要和期望信号具有相同的到达角和极化状态.具体的算例结果验证了理论分析的正确性.     

Delay Constrained Relay Node Placement in Wireless Sensor Networks: A Subtree-and-Mergence-based Approach

Wireless Sensor Networks (WSNs) are applied in many time-critical applications, e.g., industrial automation and smart grid. This highlights the importance of Delay Constrained Relay Node Placement (DCRNP) problem that builds a path fulfilling a specified delay constraint between each sensor and the sink by using a minimum number of relays. Due to the NP-hardness of the DCRNP problem, in this paper, a polynomial time Subtree-and-Mergence-based Algorithm (SMA) is proposed to approximately solve the DCRNP problem. First, a shortest path tree rooted at the sink and connecting all sensors is built to check the feasibility of the DCRNP problem. If the DCRNP problem is feasible, then the paths of this tree are progressively merged at some relays, which are not limited to those relays lying in the originally the originally built shortest path tree, to save deployed relays while maintaining the obedience of delay constraints. With the repetition of this mergence, the number of deployed relays is gradually reduced. Furthermore, the approximation ratio and the time complexity of the proposed SMA are elaborately analyzed. Finally, extensive simulations are conducted to demonstrate the effectiveness of this work. Simulation results show that SMA can significantly save deployed relays comparing with existing algorithms.     

光伏并网发电与有源电力滤波的统一控制研究

论文分析了电能质量光伏并网系统的拓扑结构和工作原理。在此基础上对PQPV系统中谐波抑制和光伏并网最大功率跟踪之间的解耦控制进行了研究,并针对谐波治理过程中负载突变导致系统直流侧电压变化,进而对最大功率输出造成影响这一问题,在PQPV系统的直流侧电压控制环节中引入了输出电流前馈控制,解决了负载变化过程中谐波抑制环节对PQPV系统最大功率跟踪的影响。最后对所提出的前馈控制方法进行了实验研究并得出相应结论。     

Sensor Networks With Mobile Access: Energy and Capacity Considerations

Sensor network with mobile access (SENMA) is an architecture in which randomly deployed low-power sensors are orchestrated by a few powerful mobile access points (APs). This paper considers SENMA from energy-efficiency and information-theoretic perspectives. By allowing sensors to propagate data directly to mobile APs over multiaccess channels, and relieving sensors from energy-consuming network functions, SENMA has the potential of offering orders of magnitude of improvement in energy efficiency over the multihop ad hoc architecture, as demonstrated by our analysis on scalability. Optimization configurations of SENMA such as the altitude, the trajectory, and the coverage of APs are considered next, using the sum-rate as the performance metric. Optimal strategies for single and multiple APs are determined. For multiple APs, the possibility of and the gain due to cooperation (i.e., joint decoding of signals received at different APs) are investigated     

GRAdient Broadcast: A Robust Data Delivery Protocol for Large Scale Sensor Networks

Although data forwarding algorithms and protocols have been among the first set of issues explored in sensor networking, how to reliably deliver sensing data through a vast field of small, vulnerable sensors remains a research challenge. In this paper we present GRAdient Broadcast (GRAB), a new set of mechanisms and protocols which is designed specifically for robust data delivery in face of unreliable nodes and fallible wireless links. Similar to previous work [12,13], GRAB builds and maintains a cost field, providing each sensor the direction to forward sensing data. Different from all the previous approaches, however, GRAB forwards data along a band of interleaved mesh from each source to the receiver. GRAB controls the width of the band by the amount of credit carried in each data message, allowing the sender to adjust the robustness of data delivery. GRAB design harnesses the advantage of large scale and relies on the collective efforts of multiple nodes to deliver data, without dependency on any individual ones. We have evaluated the GRAB performance through both analysis and extensive simulation. Our analysis shows quantitatively the advantage of interleaved mesh over multiple parallel paths. Our simulation further confirms the analysis results and shows that GRAB can successfully deliver over 90% of packets with relatively low energy cost, even under the adverse conditions of 30% node failures compounded with 15% link message losses.Fan Ye received his B.E. in Automatic Control in 1996 and MS in Computer Science in 1999, both from Tsinghua University, Beijing, China. After that, he has been pursuing a Ph.D. degree at UCLA. His research interests are in network protocol design, with focus on data forwarding, power management and security in large scale sensor networks.Gary Zhong is currently pursuing M.S. degree in computer science at University of California, Los Angeles. He received his B.S. degree in computer science and engineering from University of California, Davis. His research interests include wireless networking, mobile computing, and large scale sensor networks.Songwu Lu received both his M.S. and Ph.D. from University of Illinois at Urbana-Champaign. He is currently an assistant professor at UCLA Computer Science. He received NSF CAREER award in 2001. His research interests include wireless networking, mobile computing, wireless security, and computer networks.Lixia Zhang received her Ph.D in computer science from the Massachusetts Institute of Technology. She was a member of the research staff at the Xerox Palo Alto Research Center before joining the faculty of UCLAs Computer Science Department in 1995. In the past she has served on the Internet Architecture Board, Co-Chair of IEEE Communication Society Internet Technical Committee, the editorial board for the IEEE/ACM Transactions on Networking, and technical program committees for many networking-related conferences including SIGCOMM and INFOCOM. Zhang is currently serving as the vice chair of ACM SIGCOMM.     

机床功率信息随电压波动的变化规律研究

本文给出了电网电压与机床主电机输入功率的关系数学模型，分别用实验的方法和模型计算的方法研究了机床主电机入功率随电网电压波动的变化规律。     

SOI-KF: Distributed Kalman Filtering With Low-Cost Communications Using the Sign of Innovations

When dealing with decentralized estimation, it is important to reduce the cost of communicating the distributed observations-a problem receiving revived interest in the context of wireless sensor networks. In this paper, we derive and analyze distributed state estimators of dynamical stochastic processes, whereby the low communication cost is effected by requiring the transmission of a single bit per observation. Following a Kalman filtering (KF) approach, we develop recursive algorithms for distributed state estimation based on the sign of innovations (SOI). Even though SOI-KF can afford minimal communication overhead, we prove that in terms of performance and complexity it comes very close to the clairvoyant KF which is based on the analog-amplitude observations. Reinforcing our conclusions, we show that the SOI-KF applied to distributed target tracking based on distance-only observations yields accurate estimates at low communication cost