Մայիս-հունիսյան օրացույց
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Կրթահամալիրում ուսումնական կիսամյակի ավարին աշխատանքի ժամանակացույց
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Localization of Objects using Stochastic Tunneling
A novel wireless localization scheme in the three dimensional domain that employs stochastic optimization with tunneling transformation to recursively estimate the location of wireless tags in a network from pair wise signal strength measurements. Spatially co-located wireless tags, receiving signals from a common transmitter, exhibit correlation in their Received Signal Strength Indicator (RSSI) values. Hence in a network of wireless tags, with pair wise correlation coefficients available, posterior distribution of the unknown tag separation is used to relatively localize them using maximum a posteriori (MAP) Estimator. However, due to the non-convex/non-tractable nature of this posterior distribution, deterministic optimization methods will end in one of the many local maxima unless the initial guess is close to the region of attraction of the global maximum. In this paper, a novel stochastic localization method called LOCalization Using Stochastic Tunneling (LOCUST) is proposed which utilizes constrained simulated annealing with tunneling transformation to solve this non-tractable posterior distribution. The tunneling transformation allows the optimization search operation to circumvent or “tunnel” through ill-shaped regions in the posterior distribution resulting in faster convergence to global maximum. Finally, simulation results of our localization method are presented
Localization of Objects Using Cross-Correlation of Shadow Fading Noise and Co...
When a radio transmitter is mobile, obstacles in the
radio path can cause temporal variation in Received Signal Strength Indicator (RSSI) measured by receivers due to multipath and shadow fading. While fading, in general, is detrimental to accurately localizing a target, fading correlation between adjacent receivers may be exploited to improve localization accuracy. However, multipath fading correlation is a short range phenomenon that rapidly falls to zero within a wavelength whereas,
shadow fading correlation is independent of signal wavelength and has longer range thereby making it suitable for localization with wireless transceivers that operate at shorter wavelength. Therefore,
this paper presents a novel wireless localization scheme that employs a combination of cross-correlation between shadow fading noise and copula technique to recursively estimate the location of a transmitter. A stochastic filter that models multipath fading as an Ornstein-Uhlenbeck process followed by a Generalized Auto Regressive Conditional Heteroskedasticity (GARCH) filtering is
proposed to extract shadow fading residuals from measured RSSI values. Subsequently, Student-T Copula function is used to create the log likelihood function, which acts as the cost function for localization, by combining spatial shadow fading correlation arising among adjacent receivers due to pedestrian traffic in the area. Maximum Likelihood Estimate (MLE) is used for position estimation as it inherits the statistical consistency and asymptotic
normality. The performance of our proposed localization method is validated over simulations and hardware experiments.
Real Time Localization Using Receiver Signal Strength Indicator
Slides from my dissertation defense. Talks about the error in localizing a transmitter by measuring the signal strength. In addition, it presents new techniques for localization using cross-correlation of fading.
Ուսումնական մեդիա-թատրոն 2-րդ դասարանում
Հոդվածը՝ «Դպիրի» 48-րդ համարում (http://dpir.mskh.am/art.php?id=347)
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Localization of Objects using Stochastic Tunneling
A novel wireless localization scheme in the three dimensional domain that employs stochastic optimization with tunneling transformation to recursively estimate the location of wireless tags in a network from pair wise signal strength measurements. Spatially co-located wireless tags, receiving signals from a common transmitter, exhibit correlation in their Received Signal Strength Indicator (RSSI) values. Hence in a network of wireless tags, with pair wise correlation coefficients available, posterior distribution of the unknown tag separation is used to relatively localize them using maximum a posteriori (MAP) Estimator. However, due to the non-convex/non-tractable nature of this posterior distribution, deterministic optimization methods will end in one of the many local maxima unless the initial guess is close to the region of attraction of the global maximum. In this paper, a novel stochastic localization method called LOCalization Using Stochastic Tunneling (LOCUST) is proposed which utilizes constrained simulated annealing with tunneling transformation to solve this non-tractable posterior distribution. The tunneling transformation allows the optimization search operation to circumvent or “tunnel” through ill-shaped regions in the posterior distribution resulting in faster convergence to global maximum. Finally, simulation results of our localization method are presented
Localization of Objects Using Cross-Correlation of Shadow Fading Noise and Co...
When a radio transmitter is mobile, obstacles in the
radio path can cause temporal variation in Received Signal Strength Indicator (RSSI) measured by receivers due to multipath and shadow fading. While fading, in general, is detrimental to accurately localizing a target, fading correlation between adjacent receivers may be exploited to improve localization accuracy. However, multipath fading correlation is a short range phenomenon that rapidly falls to zero within a wavelength whereas,
shadow fading correlation is independent of signal wavelength and has longer range thereby making it suitable for localization with wireless transceivers that operate at shorter wavelength. Therefore,
this paper presents a novel wireless localization scheme that employs a combination of cross-correlation between shadow fading noise and copula technique to recursively estimate the location of a transmitter. A stochastic filter that models multipath fading as an Ornstein-Uhlenbeck process followed by a Generalized Auto Regressive Conditional Heteroskedasticity (GARCH) filtering is
proposed to extract shadow fading residuals from measured RSSI values. Subsequently, Student-T Copula function is used to create the log likelihood function, which acts as the cost function for localization, by combining spatial shadow fading correlation arising among adjacent receivers due to pedestrian traffic in the area. Maximum Likelihood Estimate (MLE) is used for position estimation as it inherits the statistical consistency and asymptotic
normality. The performance of our proposed localization method is validated over simulations and hardware experiments.
Real Time Localization Using Receiver Signal Strength Indicator
Slides from my dissertation defense. Talks about the error in localizing a transmitter by measuring the signal strength. In addition, it presents new techniques for localization using cross-correlation of fading.
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Localization of Objects using Stochastic Tunneling
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Սովորողների կարողությունների զարգացում կրթական միջավայրի ստեղծման արդյունքում
Սովորողների կարողությունների զարգացում կրթական միջավայրի ստեղծման արդյունքում
Localization of Objects Using Cross-Correlation of Shadow Fading Noise and Co...
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Real Time Localization Using Receiver Signal Strength Indicator
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Português: sílabas e acentuação- Ficha de Trabalho
Português: sílabas e acentuação- Ficha de Trabalho
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Ուսումնական մեդիա-թատրոն 2-րդ դասարանում
Հոդվածը՝ «Դպիրի» 48-րդ համարում (http://dpir.mskh.am/art.php?id=347)
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Մայիս-հունիսյան օրացույց
- 1. ՄԱՅԻՍ-ՀՈՒՆԻՍՅԱՆ ՕՐԱՑՈՒՅՑ 2011Թ. Երևանի «Մխիթար Սեբաստացի» կրթահամալիր