Abstract
The problem of detecting a known signal in colored Gaussian noise of unknown covariance is addressed. The noise is modeled as an autoregressive process of known order but unknown coefficients. By use of the theory of generalized likelihood ratio testing, a detector structure is derived and then analyzed for performance. It is proven that for large data records the detection performance is identical to that of an optimal prewhitener and matched filter, and therefore the detector itself is optimal. Simulation results indicate that the data record length necessary for the asymptotic results to apply can be quite small. Thus, the proposed detector is well suited for practical applications.
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References
H. L. Van Trees (1968) Detection, Estimation, and Modulation Theory vol. I ( New York: McGraw-Hill ).
W. C. Knight, R. G. Pridham, and S. M. Kay (1981) Digital signal processing for sonar, Proc. IEEE 69, 1451–1506.
A. A. Winder (1975) Sonar system technology, IEEE Trans. Sonics Ultrason. SU-22, 291–332.
M. Skolnik (1980) Introduction to Radar Systems ( New York: McGraw-Hill).
S. M. Kay and S. L. Marple, Jr. (1981) Spectrum analysis—a modern perspective, Proc. IEEE 69, 1380–1419.
G. J. Jenkins and D. G. Watts (1968) Spectral Analysis and Its Applications ( San Francisco: Holden-Day).
D. E. Bowyer et al. (1979) Adaptive clutter filtering using autoregressive spectral estimation, IEEE Trans. Aerosp. Electron. Syst. AES-15, 538–546.
C. Gibson et al. (1979) Maximum entropy (adaptive) filtering applied to radar clutter, IEEE ICASSP, Washington, D.C., April 2–4.
Sir M. Kendall and A. Stuart (1977) The Advanced Theory of Statistics vol. I I ( New York: Macmillan ).
C. W. Helstrom (1968) Statistical Theory of Signal Detection ed. 2 ( New York: Pergamon Press ).
A. Nuttall and P. Cable (1972) Operating characteristics for maximum likelihood detection of signals in Gaussian noise of unknown level, NUSC TR 4242, March 27.
L. Scharf and D. Lytle (1971) Signal detection in Gaussian noise of unknown level: an invariance application, IEEE Trans. Inf. Theory IT-17, 404–411.
P. Hoel, S. Port, and C. Stone (1971) Introduction to Statistical Theory (Boston: Houghton Mifflin).
S. Kay (1981) More accurate autoregressive parameter and spectral estimates for short data records, ASSP Workshop on Spectral Estimation, Hamilton, Ontario, Aug. 17–18.
A. T. Whalen (1971) Detection of Signals in Noise ( New York: Academic Press).
S. Kay (1983) Asymptotically optimal detection in unknown colored noise via autoregressive modeling, IEEE Trans. Acoust. Speech Signal Process. ASSP-31, 927–940.
G. E. P. Box and G. J. Jenkins (1970) Time Series Analysis: Forecasting and Control ( San Francisco: Holden-Day).
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© 1985 Springer Science+Business Media Dordrecht
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Kay, S. (1985). Detection for Active Sonars by Means of Autoregressive Noise Modeling. In: Smith, C.R., Grandy, W.T. (eds) Maximum-Entropy and Bayesian Methods in Inverse Problems. Fundamental Theories of Physics, vol 14. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-2221-6_19
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DOI: https://doi.org/10.1007/978-94-017-2221-6_19
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-8418-7
Online ISBN: 978-94-017-2221-6
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