On adaptive multiband signal detection with the SMI algorithm

In a nonstationary and/or nonhomogeneous interference environment, an adaptive system for target detection may suffer a severe performance degradation due to the lack of a sufficient amount of data from which the system can learn (estimate) the statistics of the environment. The detection performance of an adaptive system, which employs a frequency diversity (multiband) signaling waveform and a multiband sample matrix inversion algorithm (SMI), is analyzed. By comparison with the corresponding single-band system under the chosen system constraint, it is shown that the multiband system can significantly outperform the single band when the amount of data available from a single frequency band is severely limited by the environment. >

[1]  David Knox Barton Frequency Agility and Diversity , 1977 .

[2]  Hong Wang,et al.  On adaptive multiband signal detection with GLR algorithm , 1991 .

[3]  I. Reed,et al.  Rapid Convergence Rate in Adaptive Arrays , 1974, IEEE Transactions on Aerospace and Electronic Systems.

[4]  Ramon Nitzberg,et al.  Losses for Frequency Diversity Waveform Systems , 1978, IEEE Transactions on Aerospace and Electronic Systems.

[5]  Ramon Nitzberg Detection Loss of the Sample Matrix Inversion Technique , 1984, IEEE Transactions on Aerospace and Electronic Systems.

[6]  V. Vannicola,et al.  Detection of Slow Fluctuating Targets with Frequency Diversity Channels , 1974, IEEE Transactions on Aerospace and Electronic Systems.

[7]  Hong Wang,et al.  On performance improvement of tone frequency estimation , 1988, IEEE Trans. Acoust. Speech Signal Process..

[8]  L. Cai,et al.  Adaptive filtering for moving-target-detection in severely inhomogeneous clutter , 1989, International Conference on Acoustics, Speech, and Signal Processing,.