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Direction-of-Arrival Estimation of Ultra-Wideband Signals in Narrowband Interference Environment Based on Power Inversion and Complex-Valued Neural Networks

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Abstract

We propose two-stage null-steering direction-of-arrival (DoA) estimation of ultra wideband (UWB) signals with power inversion algorithm and complex spatio-temporal neural network (CVSTNN). This method can estimate DoA more accurately than conventional methods in narrowband interference (NBI) environment. For null steering in UWB systems, it is necessary to adjust the amplitude and phase of tapped delay lines (TDLs) of CVSTNN. However, with a conventional CVSTNN, it often fails to estimate the arrival direction because of the NBI. We aim to reduce the influence of NBI in the learning process to avoid falling into a local solution by setting the initial weights of the TDLs with power inversion. In simulation results, it is shown that the two-stage method can realize higher DoA estimation accuracy than conventional methods.

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References

  1. Van Veen BD, Buckley KM (1988) Beamforming: a versatile approach to spatial filtering. IEEE ASSP Mag 5:4–24

    Article  Google Scholar 

  2. Capon J (1969) High-resolution frequency-wavenumber spectrum analysis. Proc IEEE 57:1408–1418

    Article  Google Scholar 

  3. Schmidt R (1986) Multiple emitter location and signal parameter estimation. IEEE Trans Antennas Propag 34:276–280

    Article  Google Scholar 

  4. Roy R, Kailath T (1989) ESPRIT-estimation of signal parameters via rotational invariance techniques. IEEE Trans Acoust Speech Signal Process 37:984–995

    Article  MATH  Google Scholar 

  5. Hirose A (1994) Fractal variation of attractors in complex-valued neural networks. Neural Process Lett 1:6–8

    Article  Google Scholar 

  6. Hirose A (2012) Complex-valued neural networks, 2nd edn. Springer, Berlin

    Book  MATH  Google Scholar 

  7. Rakkiyappan R, Cao J, Velmurugan G (2015) Existence and uniform stability analysis of fractional-order complex-valued neural networks with time delays. IEEE Trans Neural Netw Learn Syst 26:84–97

    Article  MathSciNet  MATH  Google Scholar 

  8. Yang WH, Chan KK, Chang PR (1994) Complex-valued neural network for direction of arrival estimation. Electron Lett 30:574–575

    Article  Google Scholar 

  9. Fonseca N, Coudyser M, Laurin JJ, Brault JJ (2010) On the design of a compact neural network-based DOA estimation system. IEEE Trans Antennas Propag 58:357–366

    Article  Google Scholar 

  10. Suksmono AB, Hirose A (2005) Beam forming of ultra-wideband pulses by a complex-valued spatio-temporal multilayer neural network. Int J Neural Syst 15:85–91

    Article  Google Scholar 

  11. Terabayashi K, Natsuaki R, Hirose A (2014) Ultrawideband direction-of-arrival estimation using complex-valued spatiotemporal neural networks. IEEE Trans Neural Netw Learn Syst 25:1727–1732

    Article  Google Scholar 

  12. Compton RT (1979) The power-inversion adaptive array: concept and performance. IEEE Trans Aerosp Electron Syst AES 15:803–814

    Article  Google Scholar 

  13. Kikuta K, Hirose A (2016) Narrowband interference mitigation in UWB systems utilizing frequency dependence of null formation in array antennas. IEEE Access 4:8715–8720

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. Department of Electrical Engineering and Information Systems, The University of Tokyo, Tokyo, 113-8656, Japan

    Kazutaka Kikuta & Akira Hirose

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  1. Kazutaka Kikuta
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  2. Akira Hirose
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Correspondence to Kazutaka Kikuta.

Additional information

A part of this work was presented at International Conference on Neural Information Processing (ICONIP) 2016 Kyoto.

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Kikuta, K., Hirose, A. Direction-of-Arrival Estimation of Ultra-Wideband Signals in Narrowband Interference Environment Based on Power Inversion and Complex-Valued Neural Networks. Neural Process Lett 47, 921–933 (2018). https://doi.org/10.1007/s11063-017-9669-4

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