Optimal Sensor Placement for TDOA-Based Source Localization with Sensor Location Errors (2410.20703v1)
Abstract: The accuracy of time difference of arrival (TDOA)-based source localization is influenced by sensor location deployment. Many studies focus on optimal sensor placement (OSP) for TDOA-based localization without sensor location noises (OSP-WSLN). In practice, there are sensor location errors due to installation deviations, etc, which implies the necessity of studying OSP under sensor location noises (OSP-SLN). There are two fundamental problems: What is the OSP-SLN strategy? To what extent do sensor location errors affect the performance of OSP-SLN? For the first one, under the assumption of the near-field and full set of TDOA, minimizing the trace of the Cramer-Rao bound is used as optimization criteria. Based on this, a concise equality, namely Eq. (18), is proven to show that OSP-SLN is equivalent to OSP-WSLN. Extensive simulations validate both equality and equivalence and respond to the second problem: not large sensor position errors give an ignorable negative impact on the performance of OSP-SLN quantified by the trace of CRB. Also, simulations show source localization accuracy with OSP-SLN outperforms that with random placement. These simulations validate our derived OSP-SLN and its effectiveness. We have open-sourced the code for community use.
- J. Tiemann and C. Wietfeld, “Scalable and precise multi-uav indoor navigation using tdoa-based uwb localization,” in 2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2017, pp. 1–7.
- F. Gustafsson and F. Gunnarsson, “Mobile positioning using wireless networks: possibilities and fundamental limitations based on available wireless network measurements,” IEEE Signal Processing Magazine, vol. 22, no. 4, pp. 41–53, 2005.
- R. Zekavat and R. M. Buehrer, “Handbook of position location: theory, practice, and advances,” 2019.
- R. O. Schmidt, “A new approach to geometry of range difference location,” IEEE Transactions on Aerospace and Electronic Systems, vol. AES-8, no. 6, pp. 821–835, 1972.
- Y. Chan and K. Ho, “A simple and efficient estimator for hyperbolic location,” IEEE Transactions on Signal Processing, vol. 42, no. 8, pp. 1905–1915, 1994.
- K. Ho and Y. Chan, “Solution and performance analysis of geolocation by tdoa,” IEEE Transactions on Aerospace and Electronic Systems, vol. 29, no. 4, pp. 1311–1322, 1993.
- K. C. Ho and L. M. Vicente, “Sensor allocation for source localization with decoupled range and bearing estimation,” IEEE Transactions on Signal Processing, vol. 56, no. 12, pp. 5773–5789, 2008.
- B. Yang and J. Scheuing, “Cramer-rao bound and optimum sensor array for source localization from time differences of arrival,” in Proceedings. (ICASSP ’05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., vol. 4, 2005, pp. iv/961–iv/964 Vol. 4.
- ——, “A theoretical analysis of 2d sensor arrays for tdoa based localization,” in 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings, vol. 4, 2006, pp. IV–IV.
- B. Yang, “Different sensor placement strategies for tdoa based localization,” in 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP ’07, vol. 2, 2007, pp. II–1093–II–1096.
- A. N. Bishop, B. Fidan, B. D. Anderson, P. N. Pathirana, and K. Dogancay, “Optimality analysis of sensor-target geometries in passive localization: Part 2 - time-of-arrival based localization,” in 2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information, 2007, pp. 13–18.
- J. T. Isaacs, D. J. Klein, and J. P. Hespanha, “Optimal sensor placement for time difference of arrival localization,” in Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, 2009, pp. 7878–7884.
- K. Panwar, G. Fatima, and P. Babu, “Optimal sensor placement for hybrid source localization using fused toa–rss–aoa measurements,” IEEE Transactions on Aerospace and Electronic Systems, vol. 59, no. 2, pp. 1643–1657, 2023.
- K. Tang, S. Xu, Y. Yang, H. Kong, and Y. Ma, “Optimal sensor placement using combinations of hybrid measurements for source localization,” in 2024 IEEE Radar Conference (RadarConf24), 2024, pp. 1–6.
- N. Sahu, L. Wu, P. Babu, B. S. M. R., and B. Ottersten, “Optimal sensor placement for source localization: A unified admm approach,” IEEE Transactions on Vehicular Technology, vol. 71, no. 4, pp. 4359–4372, 2022.
- Y. Yang, J. Zheng, H. Liu, K. Ho, Y. Chen, and Z. Yang, “Optimal sensor placement for source tracking under synchronization offsets and sensor location errors with distance-dependent noises,” Signal Processing, vol. 193, p. 108399, 2022. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0165168421004369
- M. Theunissen, I. Fantoni, E. Malis, and P. Martinet, “Robustness study of optimal geometries for cooperative multi-robot localization,” in IEEE/RSJ International Conference on Intelligent Robots and Systems., 2024.
- F. M. Dekking, C. Kraaikamp, H. P. Lopuhaä, and L. E. Meester, “A modern introduction to probability and statistics,” Springer Texts in Statistics, 2005.
Sponsor
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.