Skip to main content
SpringerLink
Log in

Robust cooperative localization using peer-to-peer ranging measurements

  • Published:
Peer-to-Peer Networking and Applications Aims and scope Submit manuscript

Abstract

In order to perform cooperative localization for Unmanned Systems (USs) in Global Navigation Satellite System (GNSS)-denied environments, the problem of cooperative localization based on peer-to-peer ranging measurements is addressed in this paper. We first develop a weighted least square method to estimate the relative distances among the US agents, and the estimations on relative positions and relative velocities are introduced based on Multi-Dimensional Scaling (MDS). Then, a continuous cooperative localization framework with the assistance of the estimation on relative velocity is presented. A step further, We proposed a practical Kalman Filter (KF) to estimate the relative motion parameters for those invisible links, so that the noisy and fault Euclidean Distance Matrix (EDM) could be recovered. Subsequently, the cooperative localization could be still available in the case of node failure, mutual occlusion and electromagnetic interference. The performance of the proposed algorithm is evaluated by simulation, and the results show that the proposed estimator outperforms the existing methods in accuracy and robustness.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Data availability

Data will be made available on request.

References

  1. Bezouska W, Barnhart D (2019) Decentralized cooperative localization with relative pose estimation for a spacecraft swarm. In: 2019 IEEE Aerospace Conference, pp. 1–13. IEEE

  2. Loomis BD, Rachlin KE, Wiese DN, Landerer FW, Luthcke SB (2020) Replacing GRACE/GRACE-FO with satellite laser ranging: Impacts on antarctic ice sheet mass change. Geophys Res Lett 47(3):2019–085488

    Article  Google Scholar 

  3. Qi D, Zhang J, Liang X, Li Z, Zuo J, Lei P (2021) Autonomous reconnaissance and attack test of UAV swarm based on mosaic warfare thought. In: 2021 6th International Conference on Robotics and Automation Engineering (ICRAE), pp 79–83. IEEE

  4. Tian Y, Liu K, Ok K, Tran L, Allen D, Roy N, How JP (2020) Search and rescue under the forest canopy using multiple UAVs. Int J Robot Res 39(10–11):1201–1221

    Article  Google Scholar 

  5. Pádua L, Vanko J, Hruška J, Adão T, Sousa JJ, Peres E, Morais R (2017) UAS, sensors, and data processing in agroforestry: A review towards practical applications. Int J Remote Sens 38(8–10):2349–2391

    Article  Google Scholar 

  6. Partsinevelos P, Chatziparaschis D, Trigkakis D, Tripolitsiotis A (2020) A novel UAV-assisted positioning system for GNSS-denied environments. Remote Sensing 12(7):1080

    Article  Google Scholar 

  7. Morales JJ, Khalife JJ, Kassas ZM (2022) Event-based communication strategies for collaborative inertial radio SLAM. IEEE Trans Aerosp Electron Syst

  8. Yun S, Lee YJ, Sung S (2013) IMU/Vision/Lidar integrated navigation system in GNSS denied environments. In: 2013 IEEE Aerospace Conference, pp 1–10. IEEE

  9. Wang Q, Yang L, Yu J, Chiu PWY, Zheng Y-P, Zhang L (2020) Real-time magnetic navigation of a rotating colloidal microswarm under ultrasound guidance. IEEE Trans Biomed Eng 67(12):3403–3412

    Article  Google Scholar 

  10. Qin T, Li P, Shen S (2018) VINS-mono: A robust and versatile monocular visual-inertial state estimator. IEEE Trans Robot 34(4):1004–1020

    Article  Google Scholar 

  11. Xiong J, Xiong Z, Cheong JW, Xu J, Yu Y, Dempster AG (2020) Cooperative positioning for low-cost close formation flight based on relative estimation and belief propagation. Aerosp Sci Technol 106:106068

    Article  Google Scholar 

  12. Fishberg A, How JP (2022) Multi-agent relative pose estimation with UWB and constrained communications. In: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 778–785. IEEE

  13. Li J, Yang G, Cai Q, Niu H, Li J (2022) Cooperative navigation for UAVs in GNSS-denied area based on optimized belief propagation. Measurement 192:110797

    Article  Google Scholar 

  14. Jao C-S, Abdallah AA, Chen C, Seo M, Kia SS, Kassas ZM, Shkel AM (2022) Sub-meter accurate pedestrian indoor navigation system with dual ZUPT-aided INS, machine learning-aided LTE, and UWB signals. In: Proceedings of the 35th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2022), pp 1108–1126

  15. Queralta JP, Almansa CM, Schiano F, Floreano D, Westerlund T (2020) UWB-based system for UAV localization in GNSS-denied environments: Characterization and dataset. In: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp 4521–4528. IEEE

  16. Luckinger F, Sauter T (2022) Software-based AUTOSAR-compliant precision clock synchronization over CAN. IEEE Trans Industr Inf 18(10):7341–7350

    Article  Google Scholar 

  17. Xue B, Li Z, Lei P, Wang Y, Zou X (2021) Wicsync: A wireless multi-node clock synchronization solution based on optimized UWB two-way clock synchronization protocol. Measurement 183:109760

    Article  Google Scholar 

  18. An X, Zhao S, Cui X, Liu G, Lu M (2022) Robust vehicle positioning based on multi-epoch and multi-antenna TOAs in harsh environments. IEEE Trans Intell Transp Syst

  19. Liu W, Luo X, Wei G, Liu H (2022) Node localization algorithm for wireless sensor networks based on static anchor node location selection strategy. Comput Commun 192:289–298

    Article  Google Scholar 

  20. Prager S, Haynes MS, Moghaddam M (2020) Wireless subnanosecond RF synchronization for distributed ultrawideband software-defined radar networks. IEEE Trans Microw Theory Tech 68(11):4787–4804

    Article  Google Scholar 

  21. Denis B, Pierrot J-B, Abou-Rjeily C (2006) Joint distributed synchronization and positioning in UWB ad hoc networks using TOA. IEEE Trans Microw Theory Tech 54(4):1896–1911

    Article  Google Scholar 

  22. Ahmad A, Serpedin E, Nounou H, Nounou M (2013) Joint node localization and time-varying clock synchronization in wireless sensor networks. IEEE Trans Wirel Commun 12(10):5322–5333

    Article  Google Scholar 

  23. Shi Q, Cui X, Zhao S, Xu S, Lu M (2020) Blas: Broadcast relative localization and clock synchronization for dynamic dense multiagent systems. IEEE Trans Aerosp Electron Syst 56(5):3822–3839

    Article  Google Scholar 

  24. Kawdungta R, Kawdungta S, Torrungrueng D, Phongcharoenpanich C (2021) Switched beam multi-element circular array antenna schemes for 2D single-anchor indoor positioning applications. IEEE Access 9:58882–58892

    Article  Google Scholar 

  25. Gu X, Zhou G, Li J, Xie S (2020) Joint time synchronization and ranging for a mobile wireless network. IEEE Commun Lett 24(10):2363–2366

    Article  Google Scholar 

  26. Rajan RT, Leus G, Veen A-J (2015) Joint relative position and velocity estimation for an anchorless network of mobile nodes. Signal Process 115:66–78

    Article  Google Scholar 

  27. Guo X, Chu L, Ansari N (2018) Joint localization of multiple sources from incomplete noisy Euclidean distance matrix in wireless networks. Comput Commun 122:20–29

    Article  Google Scholar 

  28. Fan Y, Qi X, Liu L (2020) Fault-tolerant cooperative localization of 3D mobile networks via two-layer filter multidimensional scaling. IEEE Sens J 21(6):8354–8366

    Article  Google Scholar 

  29. Kim E, Lee S, Kim C, Kim K (2010) Mobile beacon-based 3D-localization with multidimensional scaling in large sensor networks. IEEE Commun Lett 14(7):647–649

    Article  Google Scholar 

  30. Fan Y, Ding K, Qi X, Liu L (2021) Cooperative localization of 3D mobile networks via relative distance and velocity measurement. IEEE Commun Lett 25(9):2899–2903

    Article  Google Scholar 

  31. Chen R, Yang B, Zhang W (2020) Distributed and collaborative localization for swarming UAVs. IEEE Internet Things J 8(6):5062–5074

    Article  Google Scholar 

  32. Saeed N, Nam H, Haq MIU, Muhammad Saqib DB (2018) A survey on multidimensional scaling. ACM Comput Surv (CSUR) 51(3):1–25

  33. Chepuri SP, Leus G, Veen A-J (2014) Rigid body localization using sensor networks. IEEE Trans Signal Process 62(18):4911–4924

    Article  MathSciNet  MATH  Google Scholar 

  34. Vaghefi RM, Buehrer RM (2015) Cooperative joint synchronization and localization in wireless sensor networks. IEEE Trans Signal Process 63(14):3615–3627

    Article  MathSciNet  MATH  Google Scholar 

  35. Borg I, Groenen PJ (2005) Modern Multidimensional Scaling: Theory and Applications. Springer, New York

    MATH  Google Scholar 

  36. Rajan RT, Veen A-J (2012) Joint motion estimation and clock synchronization for a wireless network of mobile nodes. In: 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 2845–2848. IEEE

  37. García R, Puig J, Ridao P, Cufi X (2002) Augmented state kalman filtering for auv navigation. In: Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No. 02CH37292) 4:4010–4015. IEEE

  38. Kay SM (1993) Fundamentals of Statistical Signal Processing: Estimation Theory. Prentice-Hall Inc, New Jersey

    MATH  Google Scholar 

Download references

Funding

This work was supported in part by the National Natural Science Foundation of China under grant 62101138, in part by the Guangdong Natural Science Foundation under grant 2022A1515012573, and in part by the Guangzhou Basic and Applied Basic Research Project under grant 202201010346.

Author information

Authors and Affiliations

  1. School of Automation, Guangdong University of Technology, Guangzhou, 510006, Guangdong Province, China

    Peiyue Jiang, Chengye Zheng, Qinchun Ke & Xiaobo Gu

  2. Key Laboratory of Intelligent Detection and The Internet of Things in Manufacturing, Ministry of Education, Guangdong University of Technology, Guangzhou, 510006, Guangdong Province, China

    Xiaobo Gu

Authors
  1. Peiyue Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chengye Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Qinchun Ke
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiaobo Gu
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Xiaobo Gu supervised for the research activity planning and execution, developed the methodology, Peiyue Jiang and Xiaobo Gu wrote the main manuscript. Peiyue Jiang and Chengye Zheng designed the computer programs. Peiyue Jiang and Qinchun Ke conducted a simulation process, specifically performing the experiments, and data collection. All authors reviewed the manuscript.

Corresponding author

Correspondence to Xiaobo Gu.

Ethics declarations

Ethics approval

Not applicable.

Consent to publish

We confirm that the work has not been published before, the publication has been approved by all co-authors and our contribution is original and that we have full power to make this consent.

Conflict of interest

We declare there is no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the Topical Collection: 1- Track on Networking and Applications

Guest Editor: Vojislav B. Misic

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jiang, P., Zheng, C., Ke, Q. et al. Robust cooperative localization using peer-to-peer ranging measurements. Peer-to-Peer Netw. Appl. 16, 2103–2112 (2023). https://doi.org/10.1007/s12083-023-01525-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12083-023-01525-6

Keywords

Search

Navigation