Maximum Likelihood Time of Arrival and Doppler Estimation for Precise Starlink-Based PNT

Wenkai Qin, Zacharias M. Komodromos, Samuel C. Morgan, and Todd E. Humphreys

Peer Reviewed

Abstract:	We present a maximum likelihood (ML) Doppler and time-of-arrival (TOA) estimation framework for opportunistic tracking of Starlink downlink signals. Extending previous approaches that rely solely on known pilot symbols, we incorporate full-frame ML estimation to harness the data payload, significantly improving Doppler and TOA estimation accuracy. Using live Starlink transmissions, we validate our ML estimator and compare its performance against pilot-based cross-ambiguity function (CAF) and pilot-only ML estimation methods. Results show that the full-frame ML estimator achieves a 103 factor improvement in Doppler accuracy over the pilot-only CAF method and 102 factor improvement over the pilot-only ML method, reducing post-fit residual RMSE from 1469.20 Hz and 752.43 to 6.34 Hz, respectively. TOA estimation sees a smaller improvement. The findings highlight the value of leveraging the entire OFDM frame for estimation. Additionally, we newly identify two OFDM symbol modulation schemes in use by Starlink.
Published in:	2025 IEEE/ION Position, Location and Navigation Symposium (PLANS) April 28 - 1, 2025 Salt Lake Marriott Downtown at City Creek Salt Lake City, UT
Pages:	704 - 715
Cite this article:	Qin, Wenkai, Komodromos, Zacharias M., Morgan, Samuel C., Humphreys, Todd E., "Maximum Likelihood Time of Arrival and Doppler Estimation for Precise Starlink-Based PNT," 2025 IEEE/ION Position, Location and Navigation Symposium (PLANS), Salt Lake City, UT, April 2025, pp. 704-715.
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