Wireless Subnanosecond RF Synchronization for Distributed Ultrawideband Software-Defined Radar Networks

In this article, we present a distributed and decentralized synchronization algorithm for wireless sensor networks (WSNs). The proposed method achieves subnanosecond synchronization using low-cost commercial-off-the-shelf (COTS) Universal Software Radio Peripheral (USRP) software-defined radios (SDR...

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Veröffentlicht in:IEEE transactions on microwave theory and techniques Jg. 68; H. 11; S. 4787 - 4804
Hauptverfasser: Prager, Samuel, Haynes, Mark S., Moghaddam, Mahta
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.11.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Atomic clocks
Beamforming
Clocks
Distributed radar
Distributed sensor systems
MIMO (control systems)
multiple-input–multiple-output (MIMO) radar
multistatic radar
Offsets
Protocols
Radar imaging
Radar networks
Sensors
Software radio
software-defined radar (SDRadar)
software-defined radio (SDR)
Structural hierarchy
Synchronism
Synchronization
Ultrawideband radar
Wireless communication
Wireless networks
Wireless sensor networks
wireless sensor networks (WSNs)
wireless synchronization
ISSN:0018-9480, 1557-9670
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Beschreibung
Zusammenfassung:In this article, we present a distributed and decentralized synchronization algorithm for wireless sensor networks (WSNs). The proposed method achieves subnanosecond synchronization using low-cost commercial-off-the-shelf (COTS) Universal Software Radio Peripheral (USRP) software-defined radios (SDRs) and is implemented entirely in software without the need for custom hardware or atomic clocks. In an <inline-formula> <tex-math notation="LaTeX">N </tex-math></inline-formula> sensor network, the proposed protocol results in each sensor having full knowledge of baseband clock offsets, RF carrier phase offsets, and pairwise RF time of flight to subnanosecond precision for the entire network after <inline-formula> <tex-math notation="LaTeX">2N </tex-math></inline-formula> total transmissions, making this method efficiently extendible to larger sensor networks. The method is decentralized and does not rely on a hierarchical master-slave structure, making it robust to sensor dropout in contested or harsh environments. The proposed methodology is validated in simulation and tested in field experiments using a three-sensor network. This work has a wide range of applications, including transmit (TX) beamforming, distributed sensor localization, and coherent multistatic/multiple-input-multiple-output (MIMO) radar imaging for autonomous sensor swarms.
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ISSN:0018-9480
1557-9670
DOI:10.1109/TMTT.2020.3014876