Journal ArticleDOI
On Received-Signal-Strength Based Localization with Unknown Transmit Power and Path Loss Exponent
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TLDR
This letter derives a weighed least squares (WLS) formulation to jointly estimate the sensor node location and the transmit power, based on the unscented transformation (UT) for the case of unknown transmit power and unknown PLE.Abstract:
In this letter, we consider the received-signal-strength (RSS) based localization problem with unknown transmit power and unknown path loss exponent (PLE). For the case of unknown transmit power, we derive a weighed least squares (WLS) formulation to jointly estimate the sensor node location and the transmit power, based on the unscented transformation (UT). For the case of unknown PLE, we propose an alternating estimation procedure to alternatively estimate the sensor node location and the PLE. The estimation procedure can also be applied to the case when both the transmit power and the PLE are unknown. Simulation results confirm the effectiveness of the proposed method.read more
Citations
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Journal ArticleDOI
RSS-Based Localization in Wireless Sensor Networks Using Convex Relaxation: Noncooperative and Cooperative Schemes
TL;DR: New approaches based on convex optimization to address the received signal strength (RSS)-based noncooperative and cooperative localization problems in wireless sensor networks (WSNs) are proposed by using an array of passive anchor nodes to collect noisy RSS measurements from radiating source nodes in WSNs.
Journal ArticleDOI
3-D Target Localization in Wireless Sensor Networks Using RSS and AoA Measurements
TL;DR: A novel nonconvex estimator is derived based on the least squares criterion based on range and angle measurement models, and it is shown that the developed estimator can be transformed into a generalized trust region subproblem framework, by following the squared range approach, for noncooperative WSNs.
Journal ArticleDOI
A Survey of Machine Learning for Indoor Positioning
TL;DR: A comprehensive survey of ML enabled localization techniques using most common wireless technologies for accurate indoor positioning and how the ML algorithms can be effectively used for fusing different technologies and algorithms to achieve a comprehensive IPS is provided.
Journal ArticleDOI
Robust Differential Received Signal Strength-Based Localization
Yongchang Hu,Geert Leus +1 more
TL;DR: A new whitened model for DRSS-based localization with unknown transmit powers is first presented and investigated, and a robust semidefinite programming (SDP)-based estimator (RSDPE) is presented, which can cope with model uncertainties (imperfect PLE and inaccurate anchor location information).
Journal ArticleDOI
UAV-Aided Cellular Communications with Deep Reinforcement Learning Against Jamming
TL;DR: In this paper, an unmanned aerial vehicle (UAV) aided cellular framework against jamming is presented, in which an UAV uses reinforcement learning to choose the relay policy for a mobile user whose serving base station is attacked by a jammer.
References
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Book
Wireless Communications: Principles and Practice
TL;DR: WireWireless Communications: Principles and Practice, Second Edition is the definitive modern text for wireless communications technology and system design as discussed by the authors, which covers the fundamental issues impacting all wireless networks and reviews virtually every important new wireless standard and technological development, offering especially comprehensive coverage of the 3G systems and wireless local area networks (WLANs).
Journal ArticleDOI
A new method for the nonlinear transformation of means and covariances in filters and estimators
TL;DR: A new approach for generalizing the Kalman filter to nonlinear systems is described, which yields a filter that is more accurate than an extendedKalman filter (EKF) and easier to implement than an EKF or a Gauss second-order filter.
Journal ArticleDOI
Locating the nodes: cooperative localization in wireless sensor networks
Neal Patwari,Joshua N. Ash,Spyros Kyperountas,Alfred O. Hero,Randolph L. Moses,Neiyer S. Correal,Neiyer S. Correal +6 more
TL;DR: Using the models, the authors have shown the calculation of a Cramer-Rao bound (CRB) on the location estimation precision possible for a given set of measurements in wireless sensor networks.
Journal ArticleDOI
Relative location estimation in wireless sensor networks
TL;DR: This work derives CRBs and maximum-likelihood estimators (MLEs) under Gaussian and log-normal models for the TOA and RSS measurements, respectively for sensor location estimation when sensors measure received signal strength or time-of-arrival between themselves and neighboring sensors.
Journal ArticleDOI
Exact and Approximate Solutions of Source Localization Problems
Amir Beck,Petre Stoica,Jian Li +2 more
TL;DR: Numerical simulations suggest that the exact SR-LS and SRD-LS estimates outperform existing approximations of the SR- LS and SRd-LS solutions as well as approximated solutions which are based on a semidefinite relaxation.