Abstract
In order to solve the high precision and high time efficiency TDOA and FDOA estimation of communication signal in multi-station location system, we proposed an estimation algorithm based on fine classification and combination. Through the design of different fine classification series number, the algorithm can reduce the operation time effectively, and the estimation accuracy of TDOA and FDOA are developed by adopting the quadratic surface fitting. Simulation results show that when the carrier to noise ratio(CNR) is −5 to 5 dB, the estimation accuracy of TDOA is 20–100 ns, the estimation accuracy of FDOA is 45–100 MHz, which are improved by 3–4 times compared with the traditional estimation algorithm. Meanwhile, the operation time is reduced by more than one half according to the different fine classification series.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ho KC, Chan YT (1997) Geolocation of a known altitude object from TDOA and FDOA measurements. IEEE Trans Aerosp Electron Syst 33(3):770–783
Stein S (1981) Algorithms for ambiguity function processing. IEEE Trans Acoust Signal Process 29(3):1467–1472
Weiss LG (1994) Wavelets and wideband correlation processing. IEEE Signal Process Mag:13–32
Robert JU, Evaggelos G (1999) Wideband TDOA/FDOA processing using summation of short-time CAF’s. IEEE Trans Signal Process 47(12):193–200
Robert KO (1989) Frequency difference of arrival accuracy. IEEE Trans Acoust Signal Process 37(2):306–308
Yeredor A, Angel E (2011) Joint TDOA and FDOA estimation: a conditional bound and its use for optimally weighted localization. IEEE Trans Signal Process 59(4):1612–1623
Weiss AJ (2011) Direct geolocation of wideband emitters based on delay and doppler. IEEE Trans Signal Process 59(6):2513–2521
Ho KC (2012) Bias reduction for an explicit solution of source localization using TDOA. IEEE Trans Signal Process 60(5):2101–2114
Yu H, Huang G, Gao J et al (2012) An efficient constrained weighted least squares algorithm for moving source location using TDOA and FDOA measurements. IEEE Trans Wireless Commun 11(1):44–47
Xu B, Sun G, Yu R et al (2013) High-accuracy TDOA-based localization without time synchronization. IEEE Trans Parallel Distrib Syst 24(8):1567–1576
Meng W, Xie L, Xiao W (2013) Decentralized TDOA sensor pairing in multihop wireless sensor networks. IEEE Signal Process Lett 20(2):181–184
Huang J, Wan Q (2012) Analysis of TDOA and TDOA/SS based geolocation techniques in a non-line-of-sight environment. J Commun Netw 14(5):533–539
Hara S, Anzai D, Yabu T et al (2013) A perturbation analysis on the performance of TOA and TDOA localization in mixed LOS/NLOS environments. IEEE Trans Commun 61(2):679–689
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Zhang, C. (2020). The TDOA and FDOA Algorithm of Communication Signal Based on Fine Classification and Combination. In: Liang, Q., Wang, W., Liu, X., Na, Z., Jia, M., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2019. Lecture Notes in Electrical Engineering, vol 571. Springer, Singapore. https://doi.org/10.1007/978-981-13-9409-6_55
Download citation
DOI: https://doi.org/10.1007/978-981-13-9409-6_55
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-9408-9
Online ISBN: 978-981-13-9409-6
eBook Packages: EngineeringEngineering (R0)