Advertisement

Direction of Arrival (DOA) Estimation

Chapter
Part of the Signals and Communication Technology book series (SCT)

Abstract

The importance of DOA estimation in radar processing for automotive applications cannot be overstated. It forms the third component of the radar cube: range, velocity, and angle. In practice, DOA estimation is often complicated by the fact that there will be multiple and unknown number of source signals impinging on the receiver array at the same time, with unknown amplitudes. Additionally, the received source signals are almost always corrupted by additive noise and clutter is present. Besides these challenges, we also have to deal with the multipath problem.

References

  1. 1.
    Van Trees, H.: Optimum Array Processing Part IV. Wiley-Interscience (2002)Google Scholar
  2. 2.
    Karim, H., Viberg, M.: Two decades of array signal processing research. IEEE Sign. Process. Mag. pp. 67–94 (July 1996)Google Scholar
  3. 3.
    Gupta, P., Aditya, K., Datta, A.: Comparison of conventional and subspace based algorithms to estimate Direction of Arrival (DOA). In: 2016 International Conference on Communication and Signal Processing (ICCSP) (6–8 April 2016)Google Scholar
  4. 4.
    Cho S., et al.: A new direction-of-arrival estimation method using automotive radar sensor arrays. Int. J. Distrib. Sens. Netw. 13(6), 1–12 (June 2017)CrossRefGoogle Scholar
  5. 5.
    Van Veen, B.D., Buckley, K.M.: Beamforming-A versatile approach to spatial filtering. IEEE ASSP Mag. pp. 4–24 (April 1988)Google Scholar
  6. 6.
    Capon, J.: High-resolution frequency-wavenumber spectrum analysis. Proc. IEEE 57, 1408–1418 (1969)CrossRefGoogle Scholar
  7. 7.
    Schmidt, R.O.: Multiple emitter location and signal parameter estimation. IEEE Trans. Antennas Propag. 34, 276–280 (1986)CrossRefGoogle Scholar
  8. 8.
    Golub, G.H., Van Loan, C.F.: Matrix Computations, 3rd edn. Johns Hopkins University Press, Baltimore, MD (1996)Google Scholar
  9. 9.
    Forsythe, K.W.: Utilizing waveform features for adaptive beamforming and direction finding with narrowband signals. Lincoln Lab. J. 10(2), 99–126 (1997)Google Scholar
  10. 10.
    Roy, R., Kailath, T.: ESPRIT—estimation of signal parameters via rotational invariance techniques. IEEE Trans. Acoust Speech Sign. Process. 37, 984–995 (1989)CrossRefGoogle Scholar
  11. 11.
    Shan, T.J., Wax, M., Kailath, T.: On spatial smoothing for direction-of-arrival estimation of coherent sources. IEEE Trans. Acoust. Speech Sign. Process. 33(4), 806–811 (August 1985)Google Scholar
  12. 12.
    Pillai, U., Kwon, B.H.: Forward/backward spatial smoothing techniques for coherent signal identification. IEEE Trans. Acoust. Speech Sign. Process. 37(1), 8–15 (January 1989)CrossRefGoogle Scholar
  13. 13.
    Munier, J., Delisle, G.Y.: Spatial analysis using new properties of the cross-spectral matrix. IEEE Trans. Sig. Process 39(3), 746–749 (1991)CrossRefGoogle Scholar
  14. 14.
    Marcos, S., Marsal, A., Benidir, M.: The propagator method for source bearing estimation. Sig. Process. 42(2), 121–138 (1995)CrossRefGoogle Scholar
  15. 15.
    Tufts, D.W., Kumaresan, R.: Estimation of frequencies of multiple sinusoids: making linear prediction perform like maximum likelihood. Proc. IEEE 70, 975–989 (1982)CrossRefGoogle Scholar
  16. 16.
    Kay, S.M.: Modern Spectral Estimation: Theory and Application. Prentice Hall, Englewood Cliffs, NJ (1988)Google Scholar
  17. 17.
    Gamba, J.: On Noise-Compensated Techniques for Time Delay Estimation. Ph.D. Thesis (2005)Google Scholar
  18. 18.
    Makhoul, J.: Linear prediction: a tutorial review. Proc. IEEE 63(4), 561–580 (1975)CrossRefGoogle Scholar
  19. 19.
    Paulraj, A., Ottersten, B., Roy, R., Swindlehurst, A., Xu, G., Kailath, T.: Subspace methods for directions-of-arrival estimation. In: Bose, N.K., Rao, C.R. (eds.) Handbook of Statistics, vol. 10, pp. 693–739. Elsevier Science Publishers B.V. (1993)Google Scholar
  20. 20.
    Viberg, M., Ottersten, B.: Sensor array processing based on subspace fitting. IEEE Trans. Sign. Process. 39, 1110–1121 (May 1991)CrossRefGoogle Scholar
  21. 21.
    Chen, C.-Y., Vaidyanathan, P.P.: Minimum redundancy MIMO radars. In: 2008 IEEE International Symposium on Circuits and Systems, pp. 45–48 (2008)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.TsukubaJapan

Personalised recommendations