Detection of determinate signals with a fixed false alarm probability in the case of autoregression model of interference with unknown parameters

Authors

  • Victor S. Golikov Universidad Autónoma del Carmen, Mexico
  • O. M. Lebedeva Independent University of Carmen, Mexico

DOI:

https://doi.org/10.3103/S0735272707030077

Abstract

The paper is devoted to investigation of nonadaptive detection of determinate signals with fixed false alarm probability in the case of unknown covariance matrix of interference components. The interference model represents the Gaussian model of random process of the first-order autoregression (AR-interference). Application of the method of projection in the N-dimensional Hilbert space permitted to formulate the conditions, when the low-rank detectors guaranteed fixed false alarm probability at an unknown covariance matrix of AR-interference. The efficiency of this detector is assessed by the simulation method. It is shown that for the first-order AR-interference an acceptable loss (as compared with the Neumann-Pearson optimal detector) can be achieved.

References

P. S. Akimov, P. A. Bakut, et al., Theory of Signal Detection (Radio i Svyaz’, Moscow, 1984) [in Russian].

L. L. Scharf, Statistical Signal Processing: Detection, Estimation and Time Series Analysis (Addison-Wesley Publishing Company, 1991).

E. J. Kelly, IEEE Trans. on Aerospace and Electronic Systems 22(1), 115 (1986).

V. I. Ponomaryov and L. Nino-de-Rivera, Electromagnetic Waves and Electronic Systems 8(7–8), 99 (2003).

E. Conte, A. De Maio, and G. Galdi, IEEE Trans. on Signal Processing 51, No. 1, 142 (2003).

V. S. Golikov and O. M. Lebedeva, Izv. VUZ. Radioelektronika 47(7), 66 (2004).

S. M. Kay, IEEE Trans. on Acoustic, Speech, and Signal Processing 31(1), 56 (1983).

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Published

2007-03-07

Issue

Vol. 50 No. 3 (2007)

Section

Research Articles