Mobility-Aided Wireless Sensor Network Localization via Semidefinite Programming

In this paper, considering a mobile wireless sensor network, we study the problem of exploiting sensor mobility information in the process of sensor localization under two range measurement models, namely the time-of-arrival (TOA) model and the received signal strength (RSS) model. To do so, for eac...

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Veröffentlicht in:IEEE transactions on wireless communications Jg. 12; H. 12; S. 5966 - 5978
Hauptverfasser: Salari, Soheil, Shahbazpanahi, Shahram, Ozdemir, Kemal
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.12.2013
Institute of Electrical and Electronics Engineers
Schlagworte:
Applied sciences
convex programming
Detection, estimation, filtering, equalization, prediction
Distance measurement
Equipments and installations
Exact sciences and technology
Information, signal and communications theory
Kalman filters
mobile localization
Mobile radiocommunication systems
mobile sensor networks
Optimization
Radiocommunication specific techniques
Radiocommunications
Robot sensing systems
semi-definite programming
semi-definite relaxation
Sensor localization
Services and terminals of telecommunications
Signal and communications theory
Signal, noise
Systems, networks and services of telecommunications
Telecommunications
Telecommunications and information theory
Telemetry. Remote supervision. Telewarning. Remote control
Vectors
Velocity measurement
Wireless sensor networks
Performance evaluation
Positioning
Wireless telecommunication
Speed measurement
Convex programming
Optimization
Remote sensing
Relaxation
Localization
Signal detection
Measurement error
Mobile radiocommunication
Range finding
Motion estimation
mobile localization
semi-definite relaxation
Measurement sensor
mobile sensor networks
semi-definite programming
Sensor localization
Arrival time
Simulation
Signal processing
Wireless network
Maximum likelihood
Sensor array
Approximate solution
Software radio
ISSN:1536-1276
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Beschreibung
Zusammenfassung:In this paper, considering a mobile wireless sensor network, we study the problem of exploiting sensor mobility information in the process of sensor localization under two range measurement models, namely the time-of-arrival (TOA) model and the received signal strength (RSS) model. To do so, for each model, we first derive the maximum likelihood (ML) location estimator for the case of error-free velocity measurements. As the corresponding optimization problems are non-convex, we resort to semi-definite relaxation (SDR) techniques to find approximate solutions to each problem using semi-definite programming (SDP). We then extend our results to the cases where the velocity measurements are subject to measurement errors. Our simulation results show that exploiting the mobility information in the localization process can significantly improve the performance of the sensor localization. Moreover, mobility-aided localization has the potential to address some of typical positioning problems, such as sensitivity to the ranging measurement errors and the requirement on the number of the anchors needed to uniquely localize the sensor nodes.
ISSN:1536-1276
DOI:10.1109/TWC.2013.110813.120379