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Target tracking in wireless sensor networks using adaptive ...

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Aug 07, 2011· Li H, Fang J. Distributed adaptive quantization and estimation for wireless sensor networks. IEEE Signal Process Lett, 2007, 14: 669–672. Article Google Scholar 14. Vemula M, Bugallo M F, Djuri P M. Particle filteringbased target tracking in binary sensor networks using adaptive thresholds.

Target Tracking by Particle Filtering in Binary Sensor ...

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adshelp[at] The ADS is operated by the Smithsonian Astrophysical Observatory under NASA Cooperative Agreement NNX16AC86A

James H. Michels IEEE Xplore Author Details

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His current research interests include detection, estimation, multichannel adaptive signal processing, multi and hyperspectral image processing, time series analyses, spacetime adaptive processing (STAP), change detection, particle filtering, and stochastic resonance.

Distributed Particle Filters for Object Tracking in Sensor ...

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Collaborative Signal Processing in Sensor Networks . . . . . . . 19 ... Approaches to Maintaining a Particle Filter in a Sensor Network 26 ... Architecture of the sensor network. The binary sensor of each mote has a detection region, and an associated probability of ...

A distributed particle filter for nonlinear tracking in ...

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Wireless sensor network Particle filters Distributed filtering Target tracking abstract The use of distributed particle filters for tracking in sensor networks has become popular in recent years. The distributed particle filters proposed in the literature up to now are ... the signal processing tasks associated to target

Multiple Target Tracking With Binary Proximity Sensors

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Additional Key Words and Phrases: Target Tracking, Sensor Networks, Binary Sensing, Counting Resolution, Particle Filters 1. INTRODUCTION We investigate the problem of tracking targets using a network of binary proximity sensors. Each sensor produces a single bit of output, which is 1 when one or more targets are in its sensing range and 0 ...

EURASIP Journal on Advances in Signal Processing | Articles

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EURASIP Journal on Advances in Signal Processing is a peerreviewed open access journal published under the brand SpringerOpen. ... Saliency area detection algorithm of electronic information and image processing based on multisensor data fusion. ... Low noise moving target detection in high resolution radar using binary codes. Radar ...

Particle Filtering for Nonlinear/NonGaussian Systems With ...

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In this paper, the particle filtering problem is investigated for a class of nonlinear/nonGaussian systems with energy harvesting sensors subject to randomly occurring sensor saturations (ROSSs). The random occurrences of the sensor saturations are characterized by a series of Bernoulli distributed stochastic variables with known probability distributions.

Hierarchical Particle Filtering in Multimodal Networks

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We call this variation of the particle filter, a hierarchical particle filter (HPF). Hierarchical models are natural in multimodal networks since each sensor measures a specific component of the state vector. These hierarchical dependencies are ignored in the earlier approaches.

Multitarget Tracking Using Virtual Measurement of Binary ...

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A binary sensor network, perhaps, is the sim tion and target states is nonlinear. As a consequence, nonlinear filtering techniques, such as particle filter plest prototype of sensor networks that can be used for ing, are often chosen by …

Improved probability hypothesis density filter for multi ...

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First, the transmitting signal of the radar is dedicated for target detection and has ideal ambiguity function. Second, the radar transmitter has higher transmitting power, and the noncooperative bistatic radar has a long probing range. Third, the noncooperative bistatic radar does not significantly rely on the radar network.

Signal Processing

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Target Tracking with Binary Proximity Sensors: Fundamental ...

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Particle filters [5] offer an alternative to Kalman filters in nonGaussian setting, and have been investigated for tracking using sensor networks in [4]. Most prior work on particle filtering assumes more sensed information (with a more desensors. and algorithms.

Detection and Measurement of Radar Signals: A Tutorial

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r = distance between radar antenna and measurement antenna (meters). The variable Pr takes the place of Pp in Eq. B1, and the value for the external attenuation, Aext, becomes: (B3) where all variables are as defined for Eq. B1. For example, suppose a radar transmitter operates at 2800 MHz; that the transmitter produces

A SelfAdaptive Particle Swarm Optimization Based Multiple ...

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ResearchArticle A SelfAdaptive Particle Swarm Optimization Based Multiple Source Localization Algorithm in Binary Sensor Networks LongCheng,1,2 YanWang,2,3 ...

Signal processing by particle filtering for binary sensor ...

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Binary sensor networks are a class of networks that get around these constraints. ... we apply particle filtering for processing signals from tertiary sensor networks with the purpose of …

DICENTRALIZED VARIATIONAL FILTERING FOR …

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classical Particle Filtering. Eff ectiveness of the proposed approach is evaluated in terms of tracking accuracy and localizationprecision. Index Terms Clusterbased, variational method, localization, tracking, binary proximity sensor 1. INTRODUCTION Wirelesssensor networks (WSN)are data centric . Thedata sensed

Target Tracking Based Adaptive Particle Filter in Binary ...

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This paper presents a target tracking method based on distributed adaptive particle filtering in binary wireless sensor network. Based on dynamic clustering, the adaptive particle filter receives the observations from children nodes and formulates the local estimate with the cluster head as the processing center.

Tracking Multiple Targets Using Binary Proximity Sensors

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Experimentation; Keywords: Target Tracking, Sensor Networks, Binary Sensing, Counting Resolution, Particle Filters 1. INTRODUCTION We investigate the problem of tracking targets using a network of binary proximity sensors. Each sensor produces a single bit of output, which is 1 when one or more targets are in its sensing range and 0 otherwise.

Automated Intruder Tracking using Particle Filtering and a ...

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automated position estimation using a wireless network of inexpensive binary motion sensors. The challenge is to incorporate data from a network of noisy sensors that suffer from refractory periods during which they may be unresponsive. We propose an estimation method based on Particle Filtering, a numerical sequential Monte Carlo technique.

Sensor selection for target tracking in binary sensor ...

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Sensor selection for target tracking in binary sensor networks using particle filter. Share on. Authors: Javad Jafaryahya. Dept. Electrical Engineering, Tehran Polytechnic, Amirkabir University of Technology, Tehran, Iran ...

Modified Particle Filtering Algorithm for Single Acoustic ...

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The conventional direction of arrival (DOA) estimation algorithm with static sources assumption usually estimates the source angles of two adjacent moments independently and the correlation of the moments is not considered. In this article, we focus on the DOA estimation of moving sources and a modified particle filtering (MPF) algorithm is proposed with state space model of single …

(PDF) Particle filter based sensor selection in binary ...

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This paper deals with a radar track before detect application in a multi target setting. ... Signal processing by particle filtering for binary sensor networks ... Binary sensor networks are a ...

Target Tracking by Particle Filtering in Binary Sensor ...

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May 16, 2008· We present particle filtering algorithms for tracking a single target using data from binary sensors. The sensors transmit signals that identify them to a central unit if the target is in their neighborhood; otherwise they do not transmit anything. The central unit uses a model for the target movement in the sensor field and estimates the target''s trajectory, velocity, and …

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