350 rub
Journal Antennas №5 for 2023 г.
Article in number:
Detection and position determination of the signal source in the near-field zone of the circular antenna array
Type of article: scientific article
DOI: https://doi.org/10.18127/j03209601-202305-03
UDC: 654.1
Authors:

O. V. Bolkhovskaya1, V. A. Sergeev2, A. A. Maltsev3
1–3 National Research Lobachevsky State University of Nizhny Novgorod (Nizhny Novgorod, Russia)

Abstract:

The problem of accurate estimating the coordinates (positioning) of signal sources is relevant for many applications such as: passive radio- and hydrolocation, modern mobile communication, positioning and various sensor systems. The use of multi-element antennas in such electronic systems makes it possible to significantly increase the reliability of detection and accuracy of positioning of the radiated sources. However, the vast majority of theoretical works in this field are devoted to the study of detection and angle-of-arrival estimation problems of the radiated sources located in the far-field zone (Fraunhofer zone). At the same time, antenna systems with a sufficiently large number of elements can accurately estimate not only the initial phase, the time-of-arrival and the angle-of-arrival of the signal, but also the signal wavefront form itself. This makes it possible to set and solve a more general problem of detecting and determining the coordinates of the signal source located in the near-field zone of the antenna system (on the order of several Fresnel zones) by accurately measuring all the informative parameters of the wavefront of the signal. In this formulation, the problem of localization of radiated sources has been considered in a relatively small number of studies, usually investigating linear equidistant antenna arrays, which, due to their geometry, have significantly angle restricted zone of confident detection and positioning of the object. Thus, the study of multi-element antennas with geometry more adequate for detection and localization of the radiated sources in the near-field zone is relevant for the modern radio electronic systems.

In the present paper the problem of a signal source detection and localization in the near-field zone of a circular antenna array has been considered. A new two-step algorithm for finding the maximum likelihood estimates of the signal wavefront informative parameters has been proposed. At the first step, rough estimates of the signal initial phase and the angle-of-arrival are found in a linear approximation. At the second step, the curvature of the wavefront is calculated and corrections to the initial signal phase and phase linear trend at the aperture of the virtual linear antenna are found. Theoretical lower Cramer–Rao bounds for estimates variances of all measured parameters have been derived. It has been shown that the proposed signal processing algorithms make it possible to obtain effective estimates of parameters at signal-to-noise ratios greater than some threshold values found by numerical simulations. A scheme of joint signal detection and parameters estimation has been proposed and its characteristics have been investigated. Graphs for the root-mean-square errors of all estimates, detection curves and zones of confident detection have been calculated. As an example, the zones of confident detection (lines for probabilities of correct detection) for a standard mobile device operating in a cellular network and transmitting power of 23 dBm have been constructed.

Pages: 23-37
For citation

Bolkhovskaya O.V., Sergeev V.A., Maltsev A.A. Detection and position determination of the signal source in the near-field zone of the circular antenna array. Antennas. 2023. № 5. P. 23–37. DOI: https://doi.org/10.18127/j03209601-202305-03 (in Russian)

References
  1. Sand S., Dammann A., Mensing C. Positioning in wireless communications systems. John Wiley & Sons. 2014.
  2. Stoica P., Besson O., Gershman A.B. Direction-of-arrival estimation of an amplitude-distorted wavefront. IEEE Transactions on Signal Processing. 2001. V. 49. № 2. P. 269–276. DOI: 10.1109/78.902109.
  3. Ma Y., Zhou G., Wang S. Wi-Fi sensing with channel state information: A survey. ACM Computing Surveys. 2019. V. 52. № 3. P. 1–36. DOI: 10.1145/3310194.
  4. Lomayev A., da Silva C.R.C.M., Maltsev A., Cordeiro C., Sadri A.S. Passive presence detection algorithm for Wi-Fi sensing. Radioengineering. 2020. V. 29. № 3. P. 540–547. DOI: 10.13164/re.2020.0540.
  5. Stoica P., Nehorai A. MUSIC, maximum likelihood and Cramer–Rao bound. IEEE Transactions on Acoustics, Speech, and Signal Processing. 1989. V. 37. № 5. P. 720–741. DOI: 10.1109/29.17564.
  6. Ottersten B., Viberg M., Stoica P., Nehorai A. Exact and large sample ML techniques for parameter estimation and detection in array processing. In: Haykin S., Litva J., Shepherd T.J. (eds) Radar array processing. Springer Series in Information Sciences. V. 25. Springer, Berlin, Heidelberg. 1993. DOI: 10.1007/978-3-642-77347-1_4.
  7. Athley F. Threshold region performance of maximum likelihood direction of arrival estimators. IEEE Transactions on Signal Processing. 2005. V. 53. № 4. P. 1359–1373.
  8. Korso M.N.E., Boyer R., Renaux A., Marcos S. Conditional and unconditional Cramér–Rao bounds for near-field source localization. IEEE Transactions on Signal Processing. 2010. V. 58. № 5. P. 2901–2907. DOI: 10.1109/TSP.2010.2043128.
  9. Torres A.D.J., D’Amico A.A., Sanguinetti L., Win M.Z. Cramér-Rao bounds for near-field localization. 55th Asilomar Conference on Signals, Systems, and Computers. 2021. P. 1250–1254. DOI: 10.1109/IEEECONF53345.2021.9723347.
  10. Bolkhovskaya O., Sergeev V., Maltsev A. A passive system for source detection and distance measurement based on signal wavefront estimation. Journal Radioengineering. 2022. V. 86. № 9. P. 98–112.
  11. Kay S. Fundamentals of statistical signal processing: Detection theory. New York: Prentice Hall. 2013.
  12. Balanis C.A. Antenna theory: analysis and design. 2nd Ed. John Willey & Sons. 1996.
  13. Gorelik G.S. Kolebaniya i volny. Vvedenie v akustiku, radiofiziku i optiku. Pod red. S.M. Rytova. Izd. 3-e. M.: Fizmatlit. 2008. (in Russian)
  14. Bolkhovskaya O.V., Maltsev A.A., Sergeev V.A. The wavefront estimation and signal detection in multi-element antenna arrays at low SNR. 2nd European Conference on Electrical Engineering and Computer Science (EECS). Bern, Switzerland. 2018. P. 497–501. DOI: 10.1109/EECS.2018.00097.
  15. Bolkhovskaya O., Maltsev A., Sergeev V., Keusgen W., Peter M. Accurate iterative algorithm for detection and the signal AoA estimation in low SNR region. 4th International Conference on Computing, Communications and Security (ICCCS). Rome, Italy. 2019. DOI: 10.1109/CCCS.2019.8888112.
  16. Stoica P., Moses R. Spectral analysis of signals. Pearson Prentice Hall. 2005.
  17. Vu D.T., Renaux A., Boyer R., Marcos S. A Cramer Rao bounds based analysis of 3D antenna array geometries made from ULA branches. Multidimensional Systems and Signal Processing. 2013. V. 24. P. 121–155. DOI: 10.1107/s11045-011-0160-5.
  18. Sergeev V., Bolkhovskaya O., Maltsev A. Testing the hypothesis of a plane wave-front of a signal received by a multi-element antenna array. Wave Electronics and its Application in Information and Telecommunication Systems (WECONF). 2022. P. 1–5. DOI: 10.1109/ WECONF55058.2022.9803550.
Date of receipt: 01.09.2023
Approved after review: 18.09.2023
Accepted for publication: 05.10.2023