2,668 research outputs found
Improved Distributed Estimation Method for Environmental\ud time-variant Physical variables in Static Sensor Networks
In this paper, an improved distributed estimation scheme for static sensor networks is developed. The scheme is developed for environmental time-variant physical variables. The main contribution of this work is that the algorithm in [1]-[3] has been extended, and a filter has been designed with weights, such that the variance of the estimation errors is minimized, thereby improving the filter design considerably\ud
and characterizing the performance limit of the filter, and thereby tracking a time-varying signal. Moreover, certain parameter optimization is alleviated with the application of a particular finite impulse response (FIR) filter. Simulation results are showing the effectiveness of the developed estimation algorithm
A Positioning Scheme Combining Location Tracking with Vision Assisting for Wireless Sensor Networks
This paper presents the performance of an adaptive location-estimation technique combining Kalman filtering (KF)with vision assisting for wireless sensor networks. For improving the accuracy of a location estimator, a KF procedureis employed at a mobile terminal to filter variations of the location estimate. Furthermore, using a vision-assistedcalibration technique, the proposed approach based on the normalized cross-correlation scheme is an accuracyenhancement procedure that effectively removes system errors causing uncertainty in real dynamic environments.Namely, according to the vision-assisted approach to extract the locations of the reference nodes as landmarks, a KFbasedapproach with the landmark information can calibrate the location estimation and reduce the corner effect of alocation-estimation system. In terms of the location accuracy estimated from the proposed approach, the experimentalresults demonstrate that more than 60 percent of the location estimates have error distances less than 1.4 meters in aZigBee positioning platform. As compared with the non-tracking algorithm and non-vision-assisted approach, theproposed algorithm can achieve reasonably good performance
Change Sensor Topology When Needed: How to Efficiently Use System Resources in Control and Estimation Over Wireless Networks
New control paradigms are needed for large networks
of wireless sensors and actuators in order to efficiently
utilize system resources. In this paper we consider when
feedback control loops are formed locally to detect, monitor, and counteract disturbances that hit a plant at random instances in time and space. A sensor node that detects a disturbance dynamically forms a local multi-hop tree of sensors and fuse the data into a state estimate. It is shown that the optimal estimator over a sensor tree is given by a Kalman filter of certain structure. The tree is optimized such that the overall transmission energy is minimized but guarantees a specified level of estimation accuracy. A sensor network reconfiguration algorithm is presented that leads to a suboptimal solution and has low computational complexity. A linear control law based
on the state estimate is applied and it is argued that it leads to a closed-loop control system that minimizes a quadratic cost function. The sensor network reconfiguration and the feedback control law are illustrated on an example
On the genericity properties in networked estimation: Topology design and sensor placement
In this paper, we consider networked estimation of linear, discrete-time
dynamical systems monitored by a network of agents. In order to minimize the
power requirement at the (possibly, battery-operated) agents, we require that
the agents can exchange information with their neighbors only \emph{once per
dynamical system time-step}; in contrast to consensus-based estimation where
the agents exchange information until they reach a consensus. It can be
verified that with this restriction on information exchange, measurement fusion
alone results in an unbounded estimation error at every such agent that does
not have an observable set of measurements in its neighborhood. To over come
this challenge, state-estimate fusion has been proposed to recover the system
observability. However, we show that adding state-estimate fusion may not
recover observability when the system matrix is structured-rank (-rank)
deficient.
In this context, we characterize the state-estimate fusion and measurement
fusion under both full -rank and -rank deficient system matrices.Comment: submitted for IEEE journal publicatio
Gossip Algorithms for Distributed Signal Processing
Gossip algorithms are attractive for in-network processing in sensor networks
because they do not require any specialized routing, there is no bottleneck or
single point of failure, and they are robust to unreliable wireless network
conditions. Recently, there has been a surge of activity in the computer
science, control, signal processing, and information theory communities,
developing faster and more robust gossip algorithms and deriving theoretical
performance guarantees. This article presents an overview of recent work in the
area. We describe convergence rate results, which are related to the number of
transmitted messages and thus the amount of energy consumed in the network for
gossiping. We discuss issues related to gossiping over wireless links,
including the effects of quantization and noise, and we illustrate the use of
gossip algorithms for canonical signal processing tasks including distributed
estimation, source localization, and compression.Comment: Submitted to Proceedings of the IEEE, 29 page
Adaptive Controller Placement for Wireless Sensor-Actuator Networks with Erasure Channels
Wireless sensor-actuator networks offer flexibility for control design. One
novel element which may arise in networks with multiple nodes is that the role
of some nodes does not need to be fixed. In particular, there is no need to
pre-allocate which nodes assume controller functions and which ones merely
relay data. We present a flexible architecture for networked control using
multiple nodes connected in series over analog erasure channels without
acknowledgments. The control architecture proposed adapts to changes in network
conditions, by allowing the role played by individual nodes to depend upon
transmission outcomes. We adopt stochastic models for transmission outcomes and
characterize the distribution of controller location and the covariance of
system states. Simulation results illustrate that the proposed architecture has
the potential to give better performance than limiting control calculations to
be carried out at a fixed node.Comment: 10 pages, 8 figures, to be published in Automatic
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