pith. machine review for the scientific record. sign in

arxiv: 2604.14413 · v1 · submitted 2026-04-15 · 📡 eess.SP

Recognition: unknown

Comprehensive Review of Doppler Shift Localization Methods: Advances, Limitations, and Research Opportunities

Authors on Pith no claims yet

Pith reviewed 2026-05-10 12:15 UTC · model grok-4.3

classification 📡 eess.SP
keywords Doppler shift localizationFDOASDFgeolocationGNSS-deniedmultipathpassive sensingISAC
0
0 comments X

The pith

Doppler shift techniques enable passive geolocation of emitters at meter-scale accuracy in GNSS-denied environments using commodity hardware.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This review consolidates over a decade of work on Doppler-based localization across radio, acoustic, and satellite domains to create a single taxonomy of five technique families. It compares how algebraic, Bayesian, convex, and neural estimators perform when oscillator drift, multipath, and clock offsets are present. A reader cares because these passive methods support spectrum enforcement, emergency response, autonomous vehicles, and 5G/6G integrated sensing without relying on satellites. The paper shows that low-power prototypes already reach meter-level fixes in tunnels, underwater, and multi-orbit satellite settings while supplying concrete design rules for mobile use.

Core claim

The survey introduces a unifying taxonomy that divides Doppler localization into five families, traces their measurement models and estimator forms, and evaluates them against realistic impairments; it then maps environment-specific results from urban canyons to UAV swarms and satellite orbits, distilling guidelines for tactical operations and naming open problems in frequency-reference stability, multipath modeling, edge computation, and trajectory-aware sensing.

What carries the argument

A unifying taxonomy of five technique families (single-receiver SDF fixes, multi-node FDOA, direct position determination, derivative-enhanced methods, and learning-assisted hybrids) that organizes measurement models, estimator archetypes, and performance comparisons under impairments.

If this is right

  • Derivative Doppler metrics tighten the Cramer-Rao bound at minimal added hardware cost in several scenarios.
  • Meter-scale accuracy is achievable with low size-weight-power payloads in urban, underwater, and satellite deployments.
  • Design recommendations directly support mobile and tactical operations under asynchronous clocks.
  • Remaining open challenges center on frequency-reference integrity and multipath-aware modeling for reliable field use.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The taxonomy naturally suggests hybrid estimators that combine Doppler with other passive cues to reduce sensitivity to single-impairment failures.
  • Emphasis on edge-constrained computation implies a need to test the reviewed methods on actual embedded hardware rather than simulation alone.
  • Trajectory-aware sensing could extend the current static or slowly varying emitter models to predict paths in dynamic multi-agent settings.

Load-bearing premise

The body of literature selected for review accurately and comprehensively represents all relevant advances, limitations, and impairments in Doppler shift localization.

What would settle it

Discovery of a major Doppler localization method or previously unmodeled impairment published after the review cutoff that changes the taxonomy, performance rankings, or design recommendations.

read the original abstract

Reliable geolocation of non-cooperative emitters in environments where Global Navigation Satellite Systems (GNSS) are unavailable or degraded is a key enabler for spectrum regulation, emergency response, autonomous mobility, and Integrated Sensing and Communication (ISAC) services in 5G/6G systems. Doppler-based techniques - from single-receiver Signal Doppler Frequency (SDF) fixes through multi-node Frequency Difference of Arrival (FDOA) and Direct Position Determination (DPD) to derivative-enhanced and learning-assisted hybrids - exploit radial-velocity-induced frequency shifts as a passive, high-resolution localization cue accessible with commodity software-defined radios, millimeter-wave access points, or acoustic sensors. This review consolidates over a decade of research across radio, acoustic, and satellite domains. It introduces a unifying taxonomy that divides the field into five technique families, outlining their evolution, measurement models, and estimator archetypes. It then compares algebraic, Bayesian, convex, and neural inference frameworks under realistic impairments such as oscillator drift, multipath, and asynchronous clocks, highlighting conditions where derivative Doppler metrics tighten the Cramer-Rao bound with minimal hardware cost. Environment-specific deployments are examined, from urban canyons and GNSS-denied tunnels to underwater, radar, UAV-swarm, and multi-orbit satellite scenarios, with prototype accuracies reaching meter scale using low-size, weight, and power payloads. Finally, the survey distils design recommendations for mobile and tactical operations and identifies open research challenges in frequency-reference integrity, multipath-aware modelling, edge-constrained computation, and trajectory-aware sensing.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

0 major / 2 minor

Summary. The manuscript is a comprehensive review of Doppler shift localization methods for GNSS-denied environments. It consolidates over a decade of work across radio, acoustic, and satellite domains by introducing a taxonomy of five technique families (including SDF, FDOA, DPD, and hybrids), comparing algebraic/Bayesian/convex/neural estimators under impairments such as oscillator drift and multipath, surveying environment-specific results (urban, underwater, UAV, satellite) with reported meter-scale prototype accuracies, distilling design recommendations for mobile/tactical use, and identifying open challenges in frequency-reference integrity, multipath-aware modeling, edge computation, and trajectory-aware sensing.

Significance. If the coverage is thorough, the review would provide a valuable consolidated reference for researchers working on passive localization, ISAC in 5G/6G, and spectrum management. The explicit taxonomy, impairment comparisons, and distilled recommendations could accelerate progress by highlighting where derivative Doppler metrics improve bounds with low hardware cost and by flagging practical gaps such as asynchronous clocks and multipath.

minor comments (2)
  1. [Abstract] Abstract: the claim of 'prototype accuracies reaching meter scale' would be strengthened by citing the specific environments, hardware (e.g., SDR vs. mmWave), and conditions under which this performance was achieved, rather than leaving it as a general statement.
  2. [Taxonomy] The taxonomy section should include a clear table or diagram mapping the five families to representative papers, measurement models, and estimator types to improve readability for readers new to the field.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for the positive and detailed summary of our manuscript, as well as for recognizing its potential value as a consolidated reference for Doppler-based localization research. The recommendation for minor revision is noted. As the report contains no specific major comments, we have no point-by-point issues to address and will incorporate only minor editorial refinements in the revised version.

Circularity Check

0 steps flagged

Review paper with no internal derivations or self-referential reductions

full rationale

This is a survey paper that consolidates over a decade of external literature on Doppler shift localization techniques. It introduces a taxonomy of five technique families, compares inference frameworks under impairments, examines environment-specific deployments, and distils design recommendations and open challenges, all by referencing prior work across radio, acoustic, and satellite domains. No new equations, predictions, or derivations are presented that could reduce to inputs defined within the paper; the central contribution is synthesis and taxonomy rather than novel computation. All quantitative claims and comparisons trace to cited external sources, satisfying the criteria for a self-contained review without circularity.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

As a review paper the central claims rest on synthesis of cited literature rather than new derivations, parameters, or entities.

pith-pipeline@v0.9.0 · 5574 in / 1015 out tokens · 46176 ms · 2026-05-10T12:15:30.713255+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

76 extracted references · 68 canonical work pages

  1. [1]

    Effectiveness of Mobile Emitter Location by Cooperative Swarm of Unmanned Aerial Vehicles in Various Environmental Conditions,

    J. M. Kelner and C. Ziółkowski, “Effectiveness of Mobile Emitter Location by Cooperative Swarm of Unmanned Aerial Vehicles in Various Environmental Conditions,” Sensors, vol. 20, no. 9, Art. no. 9, Jan. 2020, doi: 10.3390/s20092575

  2. [2]

    Influence of transmitter motion on received signal parameters – Analysis of the Doppler effect,

    J. Rafa and C. Ziółkowski, “Influence of transmitter motion on received signal parameters – Analysis of the Doppler effect,” Wave Motion, vol. 45, no. 3, pp. 178–190, Jan. 2008, doi: 10.1016/j.wavemoti.2007.05.003

  3. [3]

    Spatial Doppler method for locating radio signal sources ([POL] Przestrzenna dopplerowska metoda lokalizacji źródeł sygnałów radiowych),

    P. Gajewski, C. Ziółkowski, and J. M. Kelner, “Spatial Doppler method for locating radio signal sources ([POL] Przestrzenna dopplerowska metoda lokalizacji źródeł sygnałów radiowych),” Biul. Wojsk. Akad. Tech., vol. 60, no. 4, pp. 187–200, 2011

  4. [4]

    The use of SDF technology to BPSK and QPSK emission sources’ location.,

    Kelner, J.M.; Ziółkowski, C., “The use of SDF technology to BPSK and QPSK emission sources’ location.,” Przegląd Elektrotechniczny, no. 91, pp. 61–65, 2015, doi: doi:10.15199/48.2015.03.14

  5. [5]

    Ziółkowski and J

    C. Ziółkowski and J. Kelner, “Application of the SDF method to locate sources emitting signals with phase manipulation. ([POL] Zastosowanie metody SDF do lokalizacji źródeł emitujących sygnały z manipulacją fazy.),” Przegląd Telekomun. Wiad. Telekomun., vol. 87, no. 6, pp. 205–208, Jun. 2014

  6. [6]

    SDF technology in location and navigation procedures: A survey of applications,

    J. Kelner and C. Ziółkowski, “SDF technology in location and navigation procedures: A survey of applications,” presented at the XI Conference on Reconnaissance and Electronic Warfare Systems (CREWS), in 10418. Ołtarzew, Polska, 2016. doi: 10.1117/12.2269512

  7. [7]

    Two -Stage Overlapping Algorithm for Signal Doppler Frequency Location Method,

    R. Szczepanik and J. Kelner, “Two -Stage Overlapping Algorithm for Signal Doppler Frequency Location Method,” presented at the SPSympo 2023, Karpacz, Sep. 2023. doi: 10.23919/spsympo57300.2023.10302723

  8. [8]

    Using SDF method for simultaneous location of multiple radio transmitters,

    P. Gajewski, C. Ziółkowski, and J. M. Kelner, “Using SDF method for simultaneous location of multiple radio transmitters,” in 2012 19th International Conference on Microwaves, Radar & Wireless Communications, May 2012, pp. 634–637. doi: 10.1109/MIKON.2012.6233581

  9. [9]

    Kelner and C

    J. Kelner and C. Ziółkowski, “Estimation of signal source location in conditions of multipath radio wave propagation. ([POL] Estymacja położenia źródła sygnału w warunkach wielodrogowej propagacji fal radiowych.),” Przegląd Telekomun. Wiad. Telekomun., vol. 85, no. 4, pp. 436–439, May 2012

  10. [10]

    Localization by Doppler Derivatives and Doppler -Shifted Frequencies,

    X. Ke and K. C. Ho, “Localization by Doppler Derivatives and Doppler -Shifted Frequencies,” IEEE Trans. Signal Process., vol. 72, pp. 2890–2904, 2024, doi: 10.1109/TSP.2024.3401679

  11. [11]

    SDF method implementation on software -defined radio platform. ([POL] Implementacja metody SDF na platformie radia programowalnego).,

    R. Szczepanik and J. Kelner, “SDF method implementation on software -defined radio platform. ([POL] Implementacja metody SDF na platformie radia programowalnego).,” Elektron. Konstr. Technol. Zastos., vol. 3, no. 60, pp. 30–35, Mar. 2019, doi: 10.15199/13.2019.3.7

  12. [12]

    Doppler Effect Emulation for Testing USRP B200mini-Based Location Sensor. ISBN: 978-83-956020-9-2,

    R. Szczepanik, J. Wojtuń, and K. Bednarz, “Doppler Effect Emulation for Testing USRP B200mini-Based Location Sensor. ISBN: 978-83-956020-9-2,” in 2024 International Radar Symposium (IRS), Jul. 2024, pp. 271–275

  13. [13]

    Frequency Instability Impact of Low -Cost SDRs on Doppler -Based Localization Accuracy,

    K. Bednarz, J. Wojtuń, J. M. Kelner, and K. Różyc, “Frequency Instability Impact of Low -Cost SDRs on Doppler -Based Localization Accuracy,” Sensors, vol. 24, no. 4, Art. no. 4, Jan. 2024, doi: 10.3390/s24041053

  14. [14]

    Implementation of Doppler -Based Location Sensor on Unmanned Aerial Vehicle,

    R. Szczepanik, “Implementation of Doppler -Based Location Sensor on Unmanned Aerial Vehicle,” Int. J. Electron. Telecommun., vol. 70, no. 3, Art. no. 3, Jul. 2024, doi: 10.24425/ijet.2024.149605

  15. [15]

    Leveraging Digital Maps to Visualize Data in Doppler Effect-based Localization System Relying on GNSS,

    R. Szczepanik and P. Skokowski, “Leveraging Digital Maps to Visualize Data in Doppler Effect-based Localization System Relying on GNSS,” J. Telecommun. Inf. Technol., pp. 62–68, Dec. 2024, doi: 10.26636/jtit.2024.4.1753

  16. [16]

    Localization Accuracy Assessment of Tactical Radio Based on Acoustic Doppler Effect in Laboratory Conditions. ISSN: 2155 -5753.,

    K. Bednarz, J. Wojtuń, and R. Szczepanik, “Localization Accuracy Assessment of Tactical Radio Based on Acoustic Doppler Effect in Laboratory Conditions. ISSN: 2155 -5753.,” in 2024 International Radar Symposium (IRS), Jul. 2024, pp. 162 – 166

  17. [17]

    Doppler Effect -Based Automatic Landing Procedure for UAV in Difficult Access Environments,

    J. Kelner and C. Ziółkowski, “Doppler Effect -Based Automatic Landing Procedure for UAV in Difficult Access Environments,” J. Adv. Transp., vol. 2017, pp. 1–9, Oct. 2017, doi: 10.1155/2017/8092718

  18. [18]

    RF doppler shift-based mobile sensor tracking and navigation,

    B. Ku et al., “RF doppler shift-based mobile sensor tracking and navigation,” Artic. ACM Trans. Sens. Netw., vol. 7, Sep. 2010, doi: 10.1145/1806895.1806896

  19. [19]

    Sequential Doppler -Shift-Based Optimal Localization and Synchronization With TOA.,

    S. Zhao, N. Guo, X. -P. Zhang, X. Cui, and M. Lu, “Sequential Doppler -Shift-Based Optimal Localization and Synchronization With TOA.,” IEEE Internet Things J., vol. 9, no. 17, pp. 16234 –16246, Sep. 2022, doi: 10.1109/JIOT.2022.3150564

  20. [20]

    ISBN: 978-1-63081-564-6

    Nicholas O’Donoughue, Emitter Detection and Geolocation for Electronic Warfare. ISBN: 978-1-63081-564-6. 2019

  21. [21]

    A Look at the Recent Wireless Positioning Techniques With a Focus on Algorithms for Moving Receivers,

    A. Tahat, G. Kaddoum, S. Yousefi, S. Valaee, and F. Gagnon, “A Look at the Recent Wireless Positioning Techniques With a Focus on Algorithms for Moving Receivers,” IEEE Access, vol. 4, pp. 6652 –6680, 2016, doi: 10.1109/ACCESS.2016.2606486

  22. [22]

    An Emitter Localization Method Based on Multiple Differential Doppler Measurements,

    W. De Carvalho Rodrigues and J. Antonio Apolinario, “An Emitter Localization Method Based on Multiple Differential Doppler Measurements,” IEEE Lat. Am. Trans., vol. 20, no. 4, pp. 537–544, Apr. 2022, doi: 10.1109/TLA.2022.9675458

  23. [23]

    3 -D Target Localization and Motion Analysis Based on Doppler Shifted Frequencies,

    M. M. Ahmed, K. C. Ho, and G. Wang, “3 -D Target Localization and Motion Analysis Based on Doppler Shifted Frequencies,” IEEE Trans. Aerosp. Electron. Syst., vol. 58, no. 2, pp. 815 –833, Apr. 2022, doi: 10.1109/TAES.2021.3122737

  24. [24]

    Direct Position Determination of Narrowband Radio Frequency Transmitters,

    A. J. Weiss, “Direct Position Determination of Narrowband Radio Frequency Transmitters,” IEEE Signal Process. Lett., vol. 11, no. 5, pp. 513–516, May 2004, doi: 10.1109/LSP.2004.826501

  25. [25]

    An Iterative Direct Position Determination Approach Based on Doppler Frequency Shifts,

    Z. Wang, Y. Sun, L. Xie, N. Liu, and Q. Wan, “An Iterative Direct Position Determination Approach Based on Doppler Frequency Shifts,” IEEE Trans. Veh. Technol., vol. 73, no. 2, pp. 2431–2443, Feb. 2024, doi: 10.1109/TVT.2023.3311521

  26. [26]

    A Computationally Efficient Direct Position Determination Algorithm Based on OFDM System,

    Z. Wang, K. Hao, Y. Sun, L. Xie, and Q. Wan, “A Computationally Efficient Direct Position Determination Algorithm Based on OFDM System,” IEEE Commun. Lett., vol. 27, no. 3, pp. 841–845, Mar. 2023, doi: 10.1109/LCOMM.2022.3231548

  27. [27]

    Direct Position Determination of Moving Sources Based on Delay and Doppler,

    F. Ma, F. Guo, and L. Yang, “Direct Position Determination of Moving Sources Based on Delay and Doppler,” IEEE Sens. J., vol. 20, no. 14, pp. 7859–7869, Jul. 2020, doi: 10.1109/JSEN.2020.2980012

  28. [28]

    High-Resolution Direct Position Determination Using MVDR,

    L. Tzafri and A. J. Weiss, “High-Resolution Direct Position Determination Using MVDR,” IEEE Trans. Wirel. Commun., vol. 15, no. 9, pp. 6449–6461, Sep. 2016, doi: 10.1109/TWC.2016.2585116

  29. [29]

    High resolution localization of narrowband radio emitters based on doppler frequency shifts,

    T. Tirer and A. J. Weiss, “High resolution localization of narrowband radio emitters based on doppler frequency shifts,” Signal Process., vol. 141, pp. 288–298, Dec. 2017, doi: 10.1016/j.sigpro.2017.06.019

  30. [30]

    Direct position determination of multiple radio signals,

    A. Amar and A. J. Weiss, “Direct position determination of multiple radio signals,” in 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, Montreal, Que., Canada: IEEE, 2004, pp. ii -81–4. doi: 10.1109/ICASSP.2004.1326199

  31. [31]

    A Computational Efficient Maximum Likelihood Direct Position Determination Approach for Multiple Emitters Using Angle and Doppler Measurements,

    Z. Wang, Y. Sun, Q. Wan, L. Xie, and N. Liu, “A Computational Efficient Maximum Likelihood Direct Position Determination Approach for Multiple Emitters Using Angle and Doppler Measurements,” 2021, arXiv. doi: 10.48550/ARXIV.2112.02218

  32. [32]

    Direct Localization of Multiple Stationary Narrowband Sources Based on Angle and Doppler,

    J. Yin, D. Wang, Y. Wu, and R. Liu, “Direct Localization of Multiple Stationary Narrowband Sources Based on Angle and Doppler,” IEEE Commun. Lett., vol. 21, no. 12, pp. 2630–2633, Dec. 2017, doi: 10.1109/LCOMM.2017.2755656

  33. [33]

    A Decoupled Direct Positioning Algorithm for Strictly Noncircular Sources Based on Doppler Shifts and Angle of Arrival.,

    T. Qin, Z. Lu, B. Ba, and D. Wang, “A Decoupled Direct Positioning Algorithm for Strictly Noncircular Sources Based on Doppler Shifts and Angle of Arrival.,” IEEE Access, vol. 6, pp. 34449–34461, 2018, doi: 10.1109/ACCESS.2018.2849574

  34. [34]

    Direct Localization for Massive MIMO,

    N. Garcia, H. Wymeersch, E. G. Larsson, A. M. Haimovich, and M. Coulon, “Direct Localization for Massive MIMO,” IEEE Trans. Signal Process., vol. 65, no. 10, pp. 2475–2487, May 2017, doi: 10.1109/TSP.2017.2666779

  35. [35]

    Joint Spatiotemporal Multipath Mitigation in Large-Scale Array Localization,

    Y. Wang, Y. Wu, and Y. Shen, “Joint Spatiotemporal Multipath Mitigation in Large-Scale Array Localization,” IEEE Trans. Signal Process., vol. 67, no. 3, pp. 783–797, Feb. 2019, doi: 10.1109/TSP.2018.2879625

  36. [36]

    Sparse Bayesian Inference -Based Direct Off -Grid Position Determination in Multipath Environments,

    K. Hao and Q. Wan, “Sparse Bayesian Inference -Based Direct Off -Grid Position Determination in Multipath Environments,” IEEE Wirel. Commun. Lett., vol. 10, no. 6, pp. 1148–1152, Jun. 2021, doi: 10.1109/LWC.2021.3057502

  37. [37]

    One -Bit Direct Position Determination of Narrowband Gaussian Signals,

    A. Weiss and G. W. Wornell, “One -Bit Direct Position Determination of Narrowband Gaussian Signals,” in 2021 IEEE Statistical Signal Processing Workshop (SSP), Rio de Janeiro, Brazil: IEEE, Jul. 2021, pp. 466 –470. doi: 10.1109/SSP49050.2021.9513768

  38. [38]

    Distributed Direct Position Determination,

    F. Ma, Z.-M. Liu, and F. Guo, “Distributed Direct Position Determination,” IEEE Trans. Veh. Technol., vol. 69, no. 11, pp. 14007–14012, Nov. 2020, doi: 10.1109/TVT.2020.3025386

  39. [39]

    Unsynchronized OFDM network positioning in multipath,

    O. Bialer, D. Raphaeli, and A. J. Weiss, “Unsynchronized OFDM network positioning in multipath,” Signal Process., vol. 168, p. 107344, Mar. 2020, doi: 10.1016/j.sigpro.2019.107344

  40. [40]

    Single -platform passive emitter localization with bearing and Doppler -shift measurements using pseudolinear estimation techniques,

    N. H. Nguyen and K. Doğançay, “Single -platform passive emitter localization with bearing and Doppler -shift measurements using pseudolinear estimation techniques,” Signal Process., vol. 125, pp. 336 –348, Feb. 2016, doi: 10.1016/j.sigpro.2016.01.023

  41. [41]

    An algebraic method for moving source localization using TDOA, FDOA, and differential Doppler rate measurements with receiver location errors,

    Z. Liu, D. Hu, Y. Zhao, and Y. Zhao, “An algebraic method for moving source localization using TDOA, FDOA, and differential Doppler rate measurements with receiver location errors,” EURASIP J. Adv. Signal Process., vol. 2019, no. 1, p. 25, Dec. 2019, doi: 10.1186/s13634-019-0621-9

  42. [42]

    Altitude constrained source localization using TDOA, FDOA and differential Doppler rate,

    F. Ma, Z. -M. Liu, L. Yang, and F. Guo, “Altitude constrained source localization using TDOA, FDOA and differential Doppler rate,” Digit. Signal Process., vol. 123, p. 103385, Apr. 2022, doi: 10.1016/j.dsp.2022.103385

  43. [43]

    Vehicle Localization Using Doppler Shift and Time of Arrival Measurements in a Tunnel Environment,

    R. Halili et al., “Vehicle Localization Using Doppler Shift and Time of Arrival Measurements in a Tunnel Environment,” Sensors, vol. 22, no. 3, p. 847, Jan. 2022, doi: 10.3390/s22030847

  44. [44]

    Cooperative Multi-Rigid-Body Localization in Wireless Sensor Networks Using Range and Doppler Measurements,

    Q. Yu, Y. Wang, Y. Shen, and X. Shi, “Cooperative Multi-Rigid-Body Localization in Wireless Sensor Networks Using Range and Doppler Measurements,” IEEE Internet Things J., vol. 10, no. 24, pp. 22748 –22763, Dec. 2023, doi: 10.1109/JIOT.2023.3305051

  45. [45]

    Trajectory Optimization for Target Localization Using Time Delays and Doppler Shifts in Bistatic Sonar-Based Internet of Underwater Things,

    C. Zhang, W. Shi, Z. Gong, Q. Zhang, and C. Li, “Trajectory Optimization for Target Localization Using Time Delays and Doppler Shifts in Bistatic Sonar-Based Internet of Underwater Things,” IEEE Internet Things J., vol. 10, no. 18, pp. 16427– 16439, Sep. 2023, doi: 10.1109/JIOT.2023.3268151

  46. [46]

    Moving Target Localization in Multistatic Sonar By Differential Delays and Doppler Shifts,

    L. Yang, L. Yang, and D. Ho, “Moving Target Localization in Multistatic Sonar By Differential Delays and Doppler Shifts,” IEEE Signal Process. Lett., vol. 23, pp. 1–1, Sep. 2016, doi: 10.1109/LSP.2016.2582043

  47. [47]

    A Bias -Reduced Solution for Multistatic Localization Using Differential Delays and Doppler Shifts,

    Q. Qi, Y. Li, and Q. Guo, “A Bias -Reduced Solution for Multistatic Localization Using Differential Delays and Doppler Shifts,” IEEE Trans. Aerosp. Electron. Syst., pp. 1–14, 2023, doi: 10.1109/TAES.2023.3247380

  48. [48]

    Localization of a Moving Object With Sensors in Motion by Time Delays and Doppler Shifts,

    T. Jia, K. C. Ho, H. Wang, and X. Shen, “Localization of a Moving Object With Sensors in Motion by Time Delays and Doppler Shifts,” IEEE Trans. Signal Process., vol. 68, pp. 5824–5841, 2020, doi: 10.1109/TSP.2020.3023972

  49. [49]

    A Doppler Effect Based Framework for Wi-Fi Signal Tracking in Search and Rescue Operations,

    Y.-Y. Shih, A.-C. Pang, and P.-C. Hsiu, “A Doppler Effect Based Framework for Wi-Fi Signal Tracking in Search and Rescue Operations,” IEEE Trans. Veh. Technol., vol. 67, no. 5, pp. 3924–3936, May 2018, doi: 10.1109/TVT.2017.2752766

  50. [50]

    Leveraging the Doppler Effect for Channel Charting,

    F. Euchner, P. Stephan, and S. ten Brink, “Leveraging the Doppler Effect for Channel Charting,” Apr. 15, 2024, arXiv: arXiv:2404.09620. doi: 10.48550/arXiv.2404.09620

  51. [51]

    IEEE Global Communications Conference (GLOBECOM 2022) , month =

    H. Chen, F. Jiang, Y. Ge, H. Kim, and H. Wymeersch, “Doppler-Enabled Single-Antenna Localization and Mapping Without Synchronization,” in GLOBECOM 2022 - 2022 IEEE Global Communications Conference, Rio de Janeiro, Brazil: IEEE, Dec. 2022, pp. 6469–6474. doi: 10.1109/GLOBECOM48099.2022.10001351

  52. [52]

    Micro -Doppler Signature-Based Detection, Classification, and Localization of Small UAV With Long Short -Term Memory Neural Network,

    Y. Sun, S. Abeywickrama, L. Jayasinghe, C. Yuen, J. Chen, and M. Zhang, “Micro -Doppler Signature-Based Detection, Classification, and Localization of Small UAV With Long Short -Term Memory Neural Network,” IEEE Trans. Geosci. Remote Sens., vol. 59, no. 8, pp. 6285–6300, Aug. 2021, doi: 10.1109/TGRS.2020.3028654

  53. [53]

    Integrated Sensing and Communication Signals Toward 5G -A and 6G: A Survey,

    Z. Wei et al., “Integrated Sensing and Communication Signals Toward 5G -A and 6G: A Survey,” 2023, doi: 10.48550/ARXIV.2301.03857

  54. [54]

    Direct Position Determination Sensitivity to NLOS Propagation Effects on Doppler -Shift,

    J. S. Picard and A. J. Weiss, “Direct Position Determination Sensitivity to NLOS Propagation Effects on Doppler -Shift,” IEEE Trans. Signal Process., vol. 67, no. 14, pp. 3870–3881, Jul. 2019, doi: 10.1109/TSP.2019.2923152

  55. [55]

    Analysis of the Underwater Multi-Path Reflections on Doppler Shift Estimation.,

    Z. Gong, C. Li, and F. Jiang, “Analysis of the Underwater Multi-Path Reflections on Doppler Shift Estimation.,” IEEE Wirel. Commun. Lett., vol. 9, no. 10, pp. 1758–1762, Oct. 2020, doi: 10.1109/LWC.2020.3003743

  56. [56]

    A Millimeter -Wave Scattering Channel Model for Indoor Human Activity Sensing,

    M. Liu, Z. Cui, Y. Miao, M. Kim, and S. Pollin, “A Millimeter -Wave Scattering Channel Model for Indoor Human Activity Sensing,” IEEE Open J. Antennas Propag., Dec. 2024, doi: 10.1109/OJAP.2024.3516533

  57. [57]

    A Real-Time Beat Tracking System with Zero Latency and Enhanced Controllability,

    P. Meier, C.-Y. Chiu, and M. Müller, “A Real-Time Beat Tracking System with Zero Latency and Enhanced Controllability,” Trans. Int. Soc. Music Inf. Retr., vol. 7, pp. 213–227, Oct. 2024, doi: 10.5334/tismir.189

  58. [58]

    Direct Position Determination in Asynchronous Sensor Networks.,

    F. Ma, Z. -M. Liu, and F. Guo, “Direct Position Determination in Asynchronous Sensor Networks.,” IEEE Trans. Veh. Technol., vol. 68, no. 9, pp. 8790–8803, Sep. 2019, doi: 10.1109/TVT.2019.2928638

  59. [59]

    Doppler effect in radio navigation and localization. ([POL] Efekt Dopplera w radiowej nawigacji i lokalizacji).,

    C. Ziółkowski, “Doppler effect in radio navigation and localization. ([POL] Efekt Dopplera w radiowej nawigacji i lokalizacji).,” Electron. – Des. Technol. Appl., vol. 1, no. 2, pp. 29–35, Feb. 2018, doi: 10.15199/13.2018.2.7

  60. [60]

    RFID indoor localization based on Doppler effect,

    D. A. Tesch, E. L. Berz, and F. P. Hessel, “RFID indoor localization based on Doppler effect,” in Sixteenth International Symposium on Quality Electronic Design, Santa Clara, CA, USA: IEEE, Mar. 2015, pp. 556 –560. doi: 10.1109/ISQED.2015.7085487

  61. [61]

    mmTrack: Passive Multi -Person Localization Using Commodity Millimeter Wave Radio,

    C. Wu, F. Zhang, B. Wang, and K. J. Ray Liu, “mmTrack: Passive Multi -Person Localization Using Commodity Millimeter Wave Radio,” in IEEE INFOCOM 2020 - IEEE Conference on Computer Communications, Toronto, ON, Canada: IEEE, Jul. 2020, pp. 2400–2409. doi: 10.1109/INFOCOM41043.2020.9155293

  62. [62]

    RAPID: Retrofitting IEEE 802.11ay Access Points for Indoor Human Detection and Sensing,

    J. Pegoraro, J. O. Lacruz, F. Meneghello, E. Bashirov, M. Rossi, and J. Widmer, “RAPID: Retrofitting IEEE 802.11ay Access Points for Indoor Human Detection and Sensing,” IEEE Trans. Mob. Comput., vol. 23, no. 5, pp. 4501 –4519, May 2024, doi: 10.1109/TMC.2023.3291882

  63. [63]

    A novel position estimation method for wayside pass-by noise sources based on Doppler effect correction,

    H. Liu, J. Zhou, J. Wang, G. Xi, Y. Yao, and Q. Xiao, “A novel position estimation method for wayside pass-by noise sources based on Doppler effect correction,” Mech. Syst. Signal Process., vol. 206, p. 110911, Jan. 2024, doi: 10.1016/j.ymssp.2023.110911

  64. [64]

    Extended Bezier Model -Based Human Target Localization Algorithm by Doppler Radar,

    Y. Ding, S. Gao, Y. Sun, X. Xu, and J. Zhang, “Extended Bezier Model -Based Human Target Localization Algorithm by Doppler Radar,” IEEE Geosci. Remote Sens. Lett., vol. 19, pp. 1–5, 2022, doi: 10.1109/LGRS.2020.3041421

  65. [65]

    Target Localization Algorithm for Doppler Radar Based on Hough Transform and IF Correction,

    Y. Peng, Y. Ding, J. Cao, Y. Zhang, and Y. Jiang, “Target Localization Algorithm for Doppler Radar Based on Hough Transform and IF Correction,” IEEE Geosci. Remote Sens. Lett., vol. 21, pp. 1–5, 2024, doi: 10.1109/LGRS.2024.3355251

  66. [66]

    Phased Array Weather Radar Architectures for Doppler Estimation With Space -Time Processing,

    Y.-S. Kim, D. Schvartzman, R. D. Palmer, T.-Y. Yu, F. Nai, and C. D. Curtis, “Phased Array Weather Radar Architectures for Doppler Estimation With Space -Time Processing,” IEEE Trans. Radar Syst., vol. 2, pp. 725 –738, 2024, doi: 10.1109/TRS.2024.3444785

  67. [67]

    Doppler effects in UAV -to-vehicle multipath channels under 6D mobility,

    J. Bao, Z. Cui, Y. Miao, Q. Zhu, K. Mao, and B. Hua, “Doppler effects in UAV -to-vehicle multipath channels under 6D mobility,” IET Microw. Antennas Propag., vol. 18, no. 12, pp. 1042–1054, 2024, doi: 10.1049/mia2.12527

  68. [68]

    Localization of Modulated Signal Emitters Using Doppler -based Method Implemented on Single UAV,

    R. Szczepanik and J. M. Kelner, “Localization of Modulated Signal Emitters Using Doppler -based Method Implemented on Single UAV,” presented at the Communication and Information Technologies (KIT), Vysoké Tatry, Slovakia, Sep. 2023. doi: 10.1109/kit59097.2023.10297098

  69. [69]

    Improved COSPAS-SARSAT locating with geostationary satellite data,

    B. L. Gambhir, R. G. Wallace, D. W. Affens, and J. E. Bellantoni, “Improved COSPAS-SARSAT locating with geostationary satellite data,” IEEE Trans. Aerosp. Electron. Syst., vol. 32, no. 4, pp. 1405–1411, Oct. 1996, doi: 10.1109/7.543861

  70. [70]

    Positioning Method for Unmanned Aerial Vehicle (UAV) Based on Airborne Two - Dimensional Laser Doppler Velocimeter: Experiment and Dead Reckoning,

    L. Chen, C. Xi, S. Jin, and J. Zhou, “Positioning Method for Unmanned Aerial Vehicle (UAV) Based on Airborne Two - Dimensional Laser Doppler Velocimeter: Experiment and Dead Reckoning,” Drones, vol. 8, no. 12, p. 751, Dec. 2024, doi: 10.3390/drones8120751

  71. [71]

    Implementation of the SDF method on a programmable radio platform. ([POL] Implementacja metody SDF na platformie radia programowalnego.), Thesis,

    R. Szczepanik, “Implementation of the SDF method on a programmable radio platform. ([POL] Implementacja metody SDF na platformie radia programowalnego.), Thesis,” Wojskowa Akademia Techniczna, Warszawa, 2019

  72. [72]

    Parallel Radars: From Digital Twins to Digital Intelligence for Smart Radar Systems,

    Y. Liu et al., “Parallel Radars: From Digital Twins to Digital Intelligence for Smart Radar Systems,” Sensors, vol. 22, no. 24, p. 9930, Jan. 2022, doi: 10.3390/s22249930

  73. [73]

    In: GLOBECOM 2023 - 2023 IEEE Global Communications Conference

    A. Nordio, C. F. Chiasserini, and E. Viterbo, “Robust Localization of UAVs in OTFS-Based Networks,” in GLOBECOM 2023 - 2023 IEEE Global Communications Conference, Kuala Lumpur, Malaysia: IEEE, Dec. 2023, pp. 7471 –7477. doi: 10.1109/GLOBECOM54140.2023.10437569

  74. [74]

    Sequential Doppler -Shift-Based Optimal Localization and Synchronization With TOA

    “Sequential Doppler -Shift-Based Optimal Localization and Synchronization With TOA.” Accessed: Apr. 14, 2025. [Online]. Available: https://ieeexplore-1ieee-1org-100001bnc00cf.han.wat.edu.pl/document/9709530

  75. [75]

    DC -Loc: Accurate Automotive Radar Based Metric Localization with Explicit Doppler Compensation,

    P. Gao, S. Zhang, W. Wang, and C. X. Lu, “DC -Loc: Accurate Automotive Radar Based Metric Localization with Explicit Doppler Compensation,” in 2022 International Conference on Robotics and Automation (ICRA), May 2022, pp. 4128 –

  76. [76]

    doi: 10.1109/ICRA46639.2022.9811561