High-Precision and Low-Complexity ToA Estimation for Sensor Networks in GNSS-Denied Scenarios via Waveform–Algorithm Co-Design

Yuan Ma, Guifen Chen, Yijun Wang, Dakun Liu

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DOI: 10.21203/rs.3.rs-10865449/v1
Published: 2026-10-15
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Publisher: Springer Science and Business Media LLC
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BibTeX

@article{allodium:10.21203/rs.3.rs-10865449/v1,
  title = {High-Precision and Low-Complexity ToA Estimation for Sensor Networks in GNSS-Denied Scenarios via Waveform–Algorithm Co-Design},
  author = {Yuan Ma and Guifen Chen and Yijun Wang and Dakun Liu},
  year = {2026},
  doi = {10.21203/rs.3.rs-10865449/v1},
  url = {https://doi.org/10.21203/rs.3.rs-10865449/v1}
}

RIS

TY  - JOUR
TI  - High-Precision and Low-Complexity ToA Estimation for Sensor Networks in GNSS-Denied Scenarios via Waveform–Algorithm Co-Design
AU  - Yuan Ma
AU  - Guifen Chen
AU  - Yijun Wang
AU  - Dakun Liu
PY  - 2026
DO  - 10.21203/rs.3.rs-10865449/v1
UR  - https://doi.org/10.21203/rs.3.rs-10865449/v1
ER  -

APA

Ma, Y., Chen, G., Wang, Y., & Liu, D. (2026). High-Precision and Low-Complexity ToA Estimation for Sensor Networks in GNSS-Denied Scenarios via Waveform–Algorithm Co-Design. https://doi.org/10.21203/rs.3.rs-10865449/v1

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crossref · retrieved 2026-11-09T11:24:56.499Z