Contributed Review: Source-localization algorithms and applications using time of arrival and time difference of arrival measurements
Abstract
Locating the position of fixed or mobile sources (i.e., transmitters) based on received measurements from sensors is an important research area that is attracting much research interest. In this paper, we present localization algorithms using time of arrivals (TOA) and time difference of arrivals (TDOA) to achieve high accuracy under line-of-sight conditions. The circular (TOA) and hyperbolic (TDOA) location systems both use nonlinear equations that relate the locations of the sensors and tracked objects. These nonlinear equations can develop accuracy challenges because of the existence of measurement errors and efficiency challenges that lead to high computational burdens. Least squares-based and maximum likelihood-based algorithms have become the most popular categories of location estimators. We also summarize the advantages and disadvantages of various positioning algorithms. As a result, by improving measurement techniques and localization algorithms, localization applications can be extended into the signal-processing-related domains of radar, sonar, the Global Positioning System, wireless sensor networks, underwater animal tracking, mobile communications, and multimedia.
- Publication Date:
- Research Org.:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1249779
- Alternate Identifier(s):
- OSTI ID: 1253850; OSTI ID: 1420615
- Report Number(s):
- PNNL-SA-114716
Journal ID: ISSN 0034-6748
- Grant/Contract Number:
- AC05-76RL01830
- Resource Type:
- Published Article
- Journal Name:
- Review of Scientific Instruments
- Additional Journal Information:
- Journal Name: Review of Scientific Instruments Journal Volume: 87 Journal Issue: 4; Journal ID: ISSN 0034-6748
- Publisher:
- American Institute of Physics
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING; 47 OTHER INSTRUMENTATION; localization; TOA; TDOA
Citation Formats
Li, Xinya, Deng, Zhiqun Daniel, Rauchenstein, Lynn T., and Carlson, Thomas J. Contributed Review: Source-localization algorithms and applications using time of arrival and time difference of arrival measurements. United States: N. p., 2016.
Web. doi:10.1063/1.4947001.
Li, Xinya, Deng, Zhiqun Daniel, Rauchenstein, Lynn T., & Carlson, Thomas J. Contributed Review: Source-localization algorithms and applications using time of arrival and time difference of arrival measurements. United States. https://doi.org/10.1063/1.4947001
Li, Xinya, Deng, Zhiqun Daniel, Rauchenstein, Lynn T., and Carlson, Thomas J. Fri .
"Contributed Review: Source-localization algorithms and applications using time of arrival and time difference of arrival measurements". United States. https://doi.org/10.1063/1.4947001.
@article{osti_1249779,
title = {Contributed Review: Source-localization algorithms and applications using time of arrival and time difference of arrival measurements},
author = {Li, Xinya and Deng, Zhiqun Daniel and Rauchenstein, Lynn T. and Carlson, Thomas J.},
abstractNote = {Locating the position of fixed or mobile sources (i.e., transmitters) based on received measurements from sensors is an important research area that is attracting much research interest. In this paper, we present localization algorithms using time of arrivals (TOA) and time difference of arrivals (TDOA) to achieve high accuracy under line-of-sight conditions. The circular (TOA) and hyperbolic (TDOA) location systems both use nonlinear equations that relate the locations of the sensors and tracked objects. These nonlinear equations can develop accuracy challenges because of the existence of measurement errors and efficiency challenges that lead to high computational burdens. Least squares-based and maximum likelihood-based algorithms have become the most popular categories of location estimators. We also summarize the advantages and disadvantages of various positioning algorithms. As a result, by improving measurement techniques and localization algorithms, localization applications can be extended into the signal-processing-related domains of radar, sonar, the Global Positioning System, wireless sensor networks, underwater animal tracking, mobile communications, and multimedia.},
doi = {10.1063/1.4947001},
journal = {Review of Scientific Instruments},
number = 4,
volume = 87,
place = {United States},
year = {Fri Apr 01 00:00:00 EDT 2016},
month = {Fri Apr 01 00:00:00 EDT 2016}
}
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