Angle-of-arrival estimation for localization and communication in wireless networks

M. Li, Yilong Lu

Research output: Contribution to conferencePaper

Abstract

As one of the major methods for location positioning, angle of-arrival (AOA) measurement is a significant technology in wireless sensor networks (WSN), which can be explored for node and target localization, improving communication quality, location-based routing, sensor management, and other diverse applications. Due to the size, cost and energy constraints typical of a sensor node and the sophisticated resident environment, popular high resolution AOA estimation methods may malfunction and perform poorly. In this paper, we propose an algorithm for bearing estimation in unknown noise fields and harsh WSN scenarios. By modelling the noise covariance as a linear combination of known weighting matrices, a maximum likelihood (ML) criterion is established. And a particle swarm optimization (PSO) paradigm is presented for optimization of the ML cost function. Simulation results demonstrate that the paired estimator PSO-ML significantly outperforms other popular techniques and produces superior bearing estimates, especially in unfavourable scenarios typical of a sensor network.

Conference

Conference16th European Signal Processing Conference
CityLausanne, Switzerland
Period25/08/0829/08/08

Fingerprint

Bearings (structural)
Maximum likelihood
Wireless networks
Particle swarm optimization (PSO)
Sensor networks
Communication
Sensor nodes
Cost functions
Sensors
Costs

Keywords

  • Angle-of-arrival
  • localization
  • communication
  • wireless networks

Cite this

Li, M., & Lu, Y. (2008). Angle-of-arrival estimation for localization and communication in wireless networks. Paper presented at 16th European Signal Processing Conference, Lausanne, Switzerland, .
Li, M. ; Lu, Yilong. / Angle-of-arrival estimation for localization and communication in wireless networks. Paper presented at 16th European Signal Processing Conference, Lausanne, Switzerland, .
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abstract = "As one of the major methods for location positioning, angle of-arrival (AOA) measurement is a significant technology in wireless sensor networks (WSN), which can be explored for node and target localization, improving communication quality, location-based routing, sensor management, and other diverse applications. Due to the size, cost and energy constraints typical of a sensor node and the sophisticated resident environment, popular high resolution AOA estimation methods may malfunction and perform poorly. In this paper, we propose an algorithm for bearing estimation in unknown noise fields and harsh WSN scenarios. By modelling the noise covariance as a linear combination of known weighting matrices, a maximum likelihood (ML) criterion is established. And a particle swarm optimization (PSO) paradigm is presented for optimization of the ML cost function. Simulation results demonstrate that the paired estimator PSO-ML significantly outperforms other popular techniques and produces superior bearing estimates, especially in unfavourable scenarios typical of a sensor network.",
keywords = "Angle-of-arrival, localization, communication, wireless networks",
author = "M. Li and Yilong Lu",
year = "2008",
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language = "English",
note = "16th European Signal Processing Conference ; Conference date: 25-08-2008 Through 29-08-2008",

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Li, M & Lu, Y 2008, 'Angle-of-arrival estimation for localization and communication in wireless networks' Paper presented at 16th European Signal Processing Conference, Lausanne, Switzerland, 25/08/08 - 29/08/08, .

Angle-of-arrival estimation for localization and communication in wireless networks. / Li, M.; Lu, Yilong.

2008. Paper presented at 16th European Signal Processing Conference, Lausanne, Switzerland, .

Research output: Contribution to conferencePaper

TY - CONF

T1 - Angle-of-arrival estimation for localization and communication in wireless networks

AU - Li, M.

AU - Lu, Yilong

PY - 2008/8

Y1 - 2008/8

N2 - As one of the major methods for location positioning, angle of-arrival (AOA) measurement is a significant technology in wireless sensor networks (WSN), which can be explored for node and target localization, improving communication quality, location-based routing, sensor management, and other diverse applications. Due to the size, cost and energy constraints typical of a sensor node and the sophisticated resident environment, popular high resolution AOA estimation methods may malfunction and perform poorly. In this paper, we propose an algorithm for bearing estimation in unknown noise fields and harsh WSN scenarios. By modelling the noise covariance as a linear combination of known weighting matrices, a maximum likelihood (ML) criterion is established. And a particle swarm optimization (PSO) paradigm is presented for optimization of the ML cost function. Simulation results demonstrate that the paired estimator PSO-ML significantly outperforms other popular techniques and produces superior bearing estimates, especially in unfavourable scenarios typical of a sensor network.

AB - As one of the major methods for location positioning, angle of-arrival (AOA) measurement is a significant technology in wireless sensor networks (WSN), which can be explored for node and target localization, improving communication quality, location-based routing, sensor management, and other diverse applications. Due to the size, cost and energy constraints typical of a sensor node and the sophisticated resident environment, popular high resolution AOA estimation methods may malfunction and perform poorly. In this paper, we propose an algorithm for bearing estimation in unknown noise fields and harsh WSN scenarios. By modelling the noise covariance as a linear combination of known weighting matrices, a maximum likelihood (ML) criterion is established. And a particle swarm optimization (PSO) paradigm is presented for optimization of the ML cost function. Simulation results demonstrate that the paired estimator PSO-ML significantly outperforms other popular techniques and produces superior bearing estimates, especially in unfavourable scenarios typical of a sensor network.

KW - Angle-of-arrival

KW - localization

KW - communication

KW - wireless networks

UR - http://www.eurasip.org/Proceedings/Eusipco/Eusipco2008/program.html

UR - http://www.eurasip.org/Proceedings/Eusipco/Eusipco2008/papers/1569105149.pdf

M3 - Paper

ER -

Li M, Lu Y. Angle-of-arrival estimation for localization and communication in wireless networks. 2008. Paper presented at 16th European Signal Processing Conference, Lausanne, Switzerland, .