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A linear iterative algorithm for distributed sensor localization
2008
2008 42nd Asilomar Conference on Signals, Systems and Computers
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This paper presents a distributed sensor localization algorithm with inter-sensor distance information in m−dimensional Euclidean space using only m + 1 anchors (sensors that know their exact locations ...
The algorithm is iterative and the iterations on each of the m coordinates (that describe the location of a sensor) are decoupled. ...
CONCLUSIONS The paper studies a linear, iterative and distributed sensor localization algorithm in m−dimensional Euclidean space, R m (m ≥ 1), that finds the location coordinates of the sensors in a sensor ...
doi:10.1109/acssc.2008.5074597
fatcat:2dam5yndlbesfnacqctlq265mq
Distributed consensus-based demodulation: algorithms and error analysis
2010
IEEE Transactions on Wireless Communications
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Based on local message exchanges with single-hop neighboring sensors, two algorithms are developed for distributed demodulation. In the first algorithm, sensors consent on the estimated symbols. ...
Interestingly, only a few consensus iterations (roughly as many as the number of sensors), suffice for the distributed demodulators to approach the performance of their centralized counterparts. ...
DISTRIBUTED LINEAR DEMODULATORS This section introduces a linear distributed demodulation algorithm for solving (3) . ...
doi:10.1109/twc.2010.06.090890
fatcat:wq2ru5ij5ba2bpzmcikq2tce34
Information-Driven Distributed Maximum Likelihood Estimation Based on Gauss-Newton Method in Wireless Sensor Networks
2007
IEEE Transactions on Signal Processing
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advantages for wireless sensor networks. ...
In this paper, we develop an energy-efficient distributed estimation method that can be used in applications such as the estimation of a diffusive source and the localization and tracking of an acoustic ...
Modifications to Improve Performance This algorithm provides a basic framework for the distributed estimation. ...
doi:10.1109/tsp.2007.896267
fatcat:bytwiyojbbam5mdof4atyosewi
Primary Emitter Localization Using Smartly Initialized Metropolis-Hastings Algorithm
2013
Zenodo
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Localization Using MH The Metropolis-Hastings (MH) algorithm is a Markov chain Monte Carlo method for generating a sequence of random samples from a probability distribution for which direct sampling is ...
Linear interpolation algorithm computes the map value based on the triangulation; the value at a location inside a triangle is computed as a linear combination of the sensor measurement at the triangle ...
doi:10.5281/zenodo.43736
fatcat:4ludy2aeebbuvndkgssgwqe6ci
Distributed In-Network Channel Decoding
2009
IEEE Transactions on Signal Processing
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At affordable communication overhead, the resultant distributed decoders rely on local message exchanges among single-hop neighboring sensors to achieve iteratively consensus on the average LLRs per sensor ...
Interestingly, simulated tests corroborating the analytical findings demonstrate that only a few consensus iterations suffice for the novel distributed decoders to approach the performance of their centralized ...
Lemma 1 asserts a linear relationship for ideal inter-sensor links. ...
doi:10.1109/tsp.2009.2023936
fatcat:2vfpo2yl4bfn5mq3s2dvygkady
Consensus in Ad Hoc WSNs With Noisy Links—Part II: Distributed Estimation and Smoothing of Random Signals
2008
IEEE Transactions on Signal Processing
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Maximum a posteriori (MAP) and linear minimum mean-square error (LMMSE) schemes, well appreciated for centralized estimation, are shown possible to reformulate for distributed operation through the iterative ...
For decentralized tracking applications, distributed Kalman filtering and smoothing algorithms are derived for any-time MMSE optimal consensus-based state estimation using WSNs. ...
Ma for kindly pointing out [21] . ...
doi:10.1109/tsp.2007.908943
fatcat:lmtgvmpl7zhy3pmngd3252ycue
A Distributed Localization Algorithm for Wireless Sensor Networks Based on the Solutions of Spatially-Constrained Local Problems
2013
IEEE Sensors Journal
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We present a distributed localization algorithm for wireless sensor networks. Each sensor estimates its position by iteratively solving a set of local spatially-constrained programs. ...
Index Terms-Distributed-localization, wireless sensor networks. ...
ACKNOWLEDGMENT The authors would like to express their appreciation to the anonymous reviewers for their useful remarks. The authors ...
doi:10.1109/jsen.2013.2249660
fatcat:yf3zkidgyjbqnmu3ockfb7mfnm
A new distributed localization method for sensor networks
2013
2013 9th Asian Control Conference (ASCC)
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Our work follows from a seminal paper by Khan et al. [1] where a distributed algorithm, known as DILOC, for sensor localization is given using the barycentric coordinate. ...
Also, a new distributed algorithm is proposed to guarantee the asymptotic localization of all localizable sensor nodes. ...
However, the new linear system may not have a desired eigenvalue distribution like the standard DILOC algorithm to work. We then provide a new distributed iterative algorithm for localization. ...
doi:10.1109/ascc.2013.6606117
dblp:conf/ascc/DiaoLFZ13
fatcat:c2ohlxf2bjgrtbmnylpcclnjxu
Recursive Implementation of the Distributed Karhunen-Loève Transform
2010
IEEE Transactions on Signal Processing
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In the distributed linear source coding problem, a set of distributed sensors observe subsets of a data vector with noise, and provide the fusion center linearly encoded data. ...
This makes it a prime candidate for on-line and real-time implementations of the distributed Karhunen-Loève transform. ...
Geert Leus for his useful remarks and suggestions. ...
doi:10.1109/tsp.2010.2056922
fatcat:ozxkbestlza4zo6zoeg25isryu
Localized Movement-Assisted Sensor Deployment in Wireless Sensor Networks
2006
2006 IEEE International Conference on Mobile Ad Hoc and Sensor Sysetems
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In this paper, we focus on developing a distributed and localized solution, approximating the global optimal solution [1]. ...
In a wireless sensor network (WSN), the sensor distribution is vital to the quality of service (QoS) of the network, because the effectiveness of the network depends on the coverage of the monitoring area ...
A LOCAL SOLUTION FOR THE HUNGARIAN ALGORITHM In this section, we propose a local solution for the Hungarian method. ...
doi:10.1109/mobhoc.2006.278646
dblp:conf/mass/YangWD06
fatcat:xban2zbjcrbpdbqcrod6enxbcq
Consensus in Ad Hoc WSNs With Noisy Links—Part I: Distributed Estimation of Deterministic Signals
2008
IEEE Transactions on Signal Processing
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Using the method of multipliers in conjunction with a block coordinate descent approach we demonstrate how the resultant algorithm can be decomposed into a set of simpler tasks suitable for distributed ...
In particular, we introduce a decentralized scheme for least-squares and best linear unbiased estimation (BLUE) and establish its convergence in the presence of communication noise. ...
Clearly, if adheres to a linear model and is Gaussian distributed , then and consequently (s1) coincides with (s2). Local iterates will turn out to exhibit resilience to communication noise. ...
doi:10.1109/tsp.2007.906734
fatcat:on2uepwxnvfjznjvokikijyk2q
Distributing the Kalman Filter for Large-Scale Systems
2008
IEEE Transactions on Signal Processing
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The assimilation procedure is carried out on the local error covariances with a distributed iterate collapse inversion (DICI) algorithm that we introduce. ...
This paper derives a distributed Kalman filter to estimate a sparsely connected, large-scale, n-dimensional, dynamical system monitored by a network of N sensors. ...
The DICI algorithm is a composition of the linear function (the iterate step in (60)), , followed by the collapse operator, given in (55) for and in [37] for . ...
doi:10.1109/tsp.2008.927480
fatcat:y45lfcqxfzhchg2yclxxoyqit4
Distributed Maximum Likelihood for Simultaneous Self-Localization and Tracking in Sensor Networks
2012
IEEE Transactions on Signal Processing
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For linear Gaussian models, our algorithms can be implemented exactly using a distributed version of the Kalman filter and a novel message passing algorithm. ...
In the non-linear case, a solution based on local linearization in the spirit of the Extended Kalman Filter is proposed. ...
Local linearization as discussed in Sections II-A, III, and IV-A was used to implement the distributed RML algorithm. ...
doi:10.1109/tsp.2012.2205923
fatcat:lrx3acoamfcxxajc4imx74wubm
A Collaborative Training Algorithm for Distributed Learning
2009
IEEE Transactions on Information Theory
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The algorithm is relevant to the problem of distributed learning in wireless sensor networks by virtue of its exploitation of local communication. ...
In this paper, an algorithm is developed for collaboratively training networks of kernel-linear least-squares regression estimators. ...
Predd was a Ph.D. candidate at Princeton University. ...
doi:10.1109/tit.2009.2012992
fatcat:tryqxarkxzdafnej4p7coyj56m
Distributed maximum a posteriori probability estimation of dynamic systems with wireless sensor networks
2012
2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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This paper develops a framework for the estimation of a time-varying random signal using a wireless sensor network. ...
We show that the resulting distributed (D-)MAP algorithm is able to track dynamical signals with a small error. ...
−1 (s n − A s n−1 ) . (18) Substituting this specific function into the primal iteration in (12), it follows that for linear Gaussian autoregressive models the primal iteration of the D-MAP algorithm ...
doi:10.1109/icassp.2012.6288513
dblp:conf/icassp/JakubiecR12
fatcat:t24owrxvy5hahetf7mbee5kdum
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