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TDOA positioning in NLOS scenarios by particle filtering
by
De Angelis, Guido
, Valigi, Paolo
, Boccadoro, Mauro
in
Accounting
/ Algorithms
/ Communications Engineering
/ Computer Communication Networks
/ Computer simulation
/ Electrical Engineering
/ Engineering
/ Estimating techniques
/ Extended Kalman filter
/ Filtering
/ Filtration
/ Hypotheses
/ IT in Business
/ Kalman filters
/ Line of sight
/ Localization
/ Markov analysis
/ Networks
/ Noise
/ Normal distribution
/ Propagation
/ Studies
/ Wireless networks
2012
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TDOA positioning in NLOS scenarios by particle filtering
by
De Angelis, Guido
, Valigi, Paolo
, Boccadoro, Mauro
in
Accounting
/ Algorithms
/ Communications Engineering
/ Computer Communication Networks
/ Computer simulation
/ Electrical Engineering
/ Engineering
/ Estimating techniques
/ Extended Kalman filter
/ Filtering
/ Filtration
/ Hypotheses
/ IT in Business
/ Kalman filters
/ Line of sight
/ Localization
/ Markov analysis
/ Networks
/ Noise
/ Normal distribution
/ Propagation
/ Studies
/ Wireless networks
2012
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Do you wish to request the book?
TDOA positioning in NLOS scenarios by particle filtering
by
De Angelis, Guido
, Valigi, Paolo
, Boccadoro, Mauro
in
Accounting
/ Algorithms
/ Communications Engineering
/ Computer Communication Networks
/ Computer simulation
/ Electrical Engineering
/ Engineering
/ Estimating techniques
/ Extended Kalman filter
/ Filtering
/ Filtration
/ Hypotheses
/ IT in Business
/ Kalman filters
/ Line of sight
/ Localization
/ Markov analysis
/ Networks
/ Noise
/ Normal distribution
/ Propagation
/ Studies
/ Wireless networks
2012
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Journal Article
TDOA positioning in NLOS scenarios by particle filtering
2012
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Overview
A method is proposed for position estimation from non line of sight time difference of arrivals (TDOA) measurements. A general measurement model for TDOA accounting for non line of sight conditions is developed; then, several simplifying working assumptions regarding this model are discussed to allow the efficient implementation of a particle filter localization algorithm. This algorithm is tested and compared with an extended Kalman filter procedure, both in simulation, generating artificial measures, and with real data.
Publisher
Springer US,Springer Nature B.V
Subject
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