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On the uniform asymptotic convergence of a distributed particle filter

On the uniform asymptotic convergence of a distributed parti...

引用

sensor array and multichannel signal processing workshop

作者： Joaquín Míguez Department of Signal Theory & Communications Universidad Carlos III de Madrid. Leganés Madrid Spain

Distributed signal processing algorithms suitable for their implementation over wireless sensor networks (WSNs) and ad hoc networks with communications and computing capabilities have become a hot topic during the past years. One class of algorithms that have received special attention are particles filters. However, most distributed versions of this type of methods involve various heuristic or simplifying approximations and, as a consequence, classical convergence theorems for standard particle filters do not hold for their distributed counterparts. In this paper, we look into a distributed particle filter scheme that has been proposed for implementation in both parallel computing systems and WSNs, and prove that, under certain stability assumptions regarding the physical system of interest, its asymptotic convergence is guaranteed. Moreover, we show that convergence is attained uniformly over time. this means that approximation errors can be kept bounded for an arbitrarily long period of time without having to progressively increase the computational effort.

关键词： Convergence signal processing algorithms Approximation methods Wireless sensor networks signal processing Approximation algorithms Monte Carlo methods

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Envelope only TDOA estimation for sensor network self calibration

Envelope only TDOA estimation for sensor network self calibr...

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sensor array and multichannel signal processing workshop

作者： Dan Ohev Zion Hagit Messer School of Electrical Engineering Tel Aviv University

Self localization of nodes in wireless sensor networks (WSN) attracts wide interest in the past few years. the main challenge is to adopt calibration algorithms to the low-power/ low-bandwidth/ low-cost constrains on each sensor in the network. In this paper we present a novel approach, in which position-known anchors transmit special calibration signals simultaneously. Each node measures only the received signal strength (RSSI), i.e. envelope of the sum of received signals, and estimates time difference of arrivals (TDOA) of the signals. Two or more TDOA measurements allow the node to estimate its own position in the WSN. Based on an analysis of the appropriate Cramer Rao Lower Bound (CRLB) on the TDOA estimates, we suggest the choice of calibrating signals which provide optimal performance. the theoretical results are supported by simulations of the Maximum Likelihood (ML) estimators and numerical evaluation of the CRLB for a specific scenario of interest.

关键词： Conferences Wireless sensor networks Position measurement

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Tracking simplified shapes using a stochastic boundary

Tracking simplified shapes using a stochastic boundary

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sensor array and multichannel signal processing workshop

作者： Antonio Zea Florian Faion Marcus Baum Uwe D. Hanebeck Intelligent Sensor-Actuator-Systems Laboratory (ISAS) Karlsruhe Institute of Technology (KIT) Germany University of Connecticut USA

When tracking extended objects, it is often the case that the shape of the target cannot be fully observed due to issues of visibility, artifacts, or high noise, which can change with time. In these situations, it is a common approach to model targets as simpler shapes instead, such as ellipsoids or cylinders. However, these simplifications cause information loss from the original shape, which could be used to improve the estimation results. In this paper, we propose a way to recover information from these lost details in the form of a stochastic boundary, whose parameters can be dynamically estimated from received measurements. the benefits of this approach are evaluated by tracking an object using noisy, real-life RGBD data.

关键词： Robot sensing systems Shape Noise measurement Fitting Q measurement

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signal processing for random access: a case for cross-layer design

Signal processing for random access: a case for cross-layer ...

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ieee workshop on signal processing Advances in Wireless Communications (SPAWC)

作者： L. Tong School of ECE Cornell University Ithaca NY USA

Summary form only given. the role of signal processing has traditionally been assumed away beyond the physical layer. the idea of transmitting one user at a time forms the basis of most MAC protocols. In this talk, we argue that a cross-layer design that takes into account signal processing capabilities at the physical layer will result in substantial gains in network throughput and stability margin. We consider the applications in the reach-back problem for a large scale sensor network and the use of an antenna array in wireless LAN.

关键词： signal processing Cross layer design sensor arrays Physical layer Media Access Protocol Access protocols array signal processing throughput Stability Large-scale systems

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New design and advanced processing for frac jobs monitoring

New design and advanced processing for frac jobs monitoring

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4th EAGE Passive Seismic workshop

作者： Rebel-Schissele, E. Pandolfi, D. Chambefort, M. Bardainne, T. CGGVeritas Services SA United States

the main goal of frac monitoring is to obtain a clear definition of event characterization to ultimately compute SRV. Enhancement in signal-to-noise ratio is one of the key elements used to discriminate a successful technique from others. While in the buried sensors design the noise reduction is a wellaccepted advantage, the simple layout of surface sensors arrayis still under discussion. this abstract presents results obtained with a new surface design used in hydraulic fracturation monitoring showing how geometry and spatial distribution of the sensors can improve SNR and therefore sensitivity. this new design is named'patch design'.the name is self-explanatory: OnePatch consists in a given number of sensors closely distributed;a patch design is a series of patches sparsely distributed above the region of interest. this design has several advantages;we will discuss here the economic and technical benefits of this method. sensor deployment can be easily adapted to the environment optimizing permitting, line clearing, access and avoiding noise prone areas. the economic advantage does not weaken the technical benefit: At the patch scale, the short distance between sensors allowsadvanced summation to optimallypreserve the signal and reduce the noise. the patch design provides a much higher signal-tonoise ratio compared to the usual surface designs. Real cases examples will show how the patch design combines the advantages of both surface and shallow buried array designs.

关键词： signal to noise ratio

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A sparse Bayesian learning algorithm with dictionary parameter estimation

A sparse Bayesian learning algorithm with dictionary paramet...

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sensor array and multichannel signal processing workshop

作者： thomas L. Hansen Mihai A. Badiu Bernard H. Fleury Bhaskar D. Rao Dept. of Electronic Systems Aalborg University Aalborg Denmark Dept. of Electrical and Computer Engineering University of California at San Diego CA USA

this paper concerns sparse decomposition of a noisy signal into atoms which are specified by unknown continuous-valued parameters. An example could be estimation of the model order, frequencies and amplitudes of a superposition of complex sinusoids. the common approach is to reduce the continuous parameter space to a fixed grid of points, thus restricting the solution space. In this work, we avoid discretization by working directly with the signal model containing parameterized atoms. Inspired by the “fast inference scheme” by Tipping and Faul we develop a novel sparse Bayesian learning (SBL) algorithm, which estimates the atom parameters along with the model order and weighting coefficients. Numerical experiments for spectral estimation with closely-spaced frequency components, show that the proposed SBL algorithm outperforms state-of-the-art subspace and compressed sensing methods.

关键词： signal processing algorithms Dictionaries Computational modeling Bayes methods Estimation signal to noise ratio Atomic clocks

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Non-Linear Source Separation Under the Langmuir Model for Chemical sensors

Non-Linear Source Separation Under the Langmuir Model for Ch...

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sensor array and multichannel signal processing workshop

作者： Pierre Maho Simon Barthelmé Pierre Comon CNRS Univ. Grenoble Alpes Grenoble France

Electronic nose is a promising bio-inspired instrument for the detection of Volatil Organic Compounds (VOCs), meaning a compound containing carbon which easily evaporates. One of the most important parts of these devices is a set of non-specific chemical sensors, which will interact with the VOC and output valuable information for its identification. the nonspecificity of these chemical sensors ensures the universality of the instrument. the main task achieved by this instrument is the detection of individual VOC. However, in many real-life applications, mixtures of VOCs are observed. the recovery of the mixture composition, meaning the individual signatures and their relative contribution, is a challenging task which can be studied in a Blind Source Separation framework. In this paper, we propose a non-linear mixture model for a particular type of chemical sensors. this model is based on the Langmuir isotherm for a multi-component gas. We study the joint identifiability of signatures and concentrations, and propose a necessary identification condition. Finally, we propose an algorithm for the blind estimation of the parameters and assess its performance through simulations.

关键词： Chemical and biological sensors sensor arrays Chemicals array signal processing signal processing algorithms Mathematical model

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Cramér-Rao Bounds for a Coupled Mixture of Polynomial Phase and Sinusoidal FM signals

Cramér-Rao Bounds for a Coupled Mixture of Polynomial Phase...

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sensor array and multichannel signal processing workshop

作者： Pu Wang Philip V. Orlik Kota Sadamoto Wataru Tsujita Yoshitsugu Sawa Mitsubishi Electric Research Laboratories Cambridge MA 02139 USA Mitsubishi Electric Corporation Advanced Technology R&D Center Amagasaki City 661-8661 Japan

this letter introduces a new coupled mixture of polynomial phase signal (PPS) and sinusoidal frequency modulated (FM) signal, motivated by real-world applications, for example, contactless linear encoders. Specifically, the coupling is introduced to express the sinusoidal FM frequency as a function of the PPS-related parameters. Given the coupling mixture, it generalizes two existing models: the pure PPS model and the independent mixture model. Performance bounds of parameter estimation for the coupled mixture model are established in terms of the Cramér-Rao bound (CRB). Unlike the pure PPS case, the derived CRB shows its dependence on the PPS-related and sinusoidal FM-related parameters due to the coupling mixture. On the other hand, the derived CRBs for the PPS-related parameters are lower than their counterparts of the independent mixture model, as the sinusoidal FM frequency provides additional information on the PPS parameters.

关键词： Frequency modulation Mixture models Couplings Indexes array signal processing sensor arrays

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How Should IRSs Scale to Harden Multi-Antenna Channels?

How Should IRSs Scale to Harden Multi-Antenna Channels?

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sensor array and multichannel signal processing workshop

作者： Ali Bereyhi Saba Asaad Chongjun Ouyang Ralf R. Mü ller Rafael F. Schaefer H. Vincent Poor Friedrich-Alexander Universit&#x00E4 t Erlangen-N&#x00FC rnberg (FAU) Beijing University of Posts and Telecommunications University of Siegen Princeton University

this work extends the concept of channel hardening to multi-antenna systems that are aided by intelligent reflecting surfaces (IRSs). For fading links between a multi-antenna transmitter and a single-antenna receiver, we derive an accurate approximation for the distribution of the input-output mutual information when the number of reflecting elements grows large. the asymptotic results demonstrate that by increasing the number of elements on the IRS, the end-to-end channel hardens as long as the physical dimensions of the IRS grow as well. the growth rate however need not to be of a specific order and can be significantly sub-linear. the validity of the analytical result is confirmed by numerical experiments.

关键词： Fading channels Transmitters array signal processing Conferences Receivers Surface treatment Mutual information

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Quantifying the advantages of joint processing in TDOA estimation

Quantifying the advantages of joint processing in TDOA estim...

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sensor array and multichannel signal processing workshop

作者： Arie Yeredor School of Electrical Engineering Tel Aviv University Tel-Aviv Israel

We address the problem of passive estimation of the Time-Difference of Arrival (TDOA) of an unknown, stochastic signal, at two sensors. the key question addressed here is whether additional sensors, receiving the same signal at various relative delays, can serve to improve the accuracy in estimating the TDOA of interest between the first two sensors (without exploiting any underlying parameterization, such as dependence on the transmitter's location). We derive the Cramér-Rao Lower Bound (CRLB) on the resulting joint estimation error in a model which possibly includes multipath reflections. We show analytically, that in a multipath-free scenario, at high to moderate signal to Noise Ratios, additional sensors do not offer any improvement in accuracy. However, we also demonstrate (numerically) that in the presence of multipath reflections (possibly received at all sensors), the additional sensors can indeed assist in estimating the TDOA of interest with improved accuracy.

关键词： Delay signal to noise ratio Accuracy Vectors Estimation error

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