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

• Published in: IEEE transactions on microwave theory and techniques Vol. 68; no. 11; pp. 4787 - 4804
• Main Authors: Prager, Samuel, Haynes, Mark S., Moghaddam, Mahta
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.11.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 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
• DOI: 10.1109/TMTT.2020.3014876

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.