Adaptive eigenfilter implementing optimum MTI processor

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Adaptive eigenfilter implementing optimum MTI processor

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The authors present an adaptive eigenfilter implementing the optimum moving target indication (MTI) processor. The method presented shows a fast convergence capability as well as better steady-state performance than the prediction error filter (PEF). Moreover, the arithmetic efficiency of the method results from using modular processing architecture which takes advantage of the Gram-Schmidt (GS) processor.

Inspec keywords: radar signal processing; convergence; covariance matrices; filtering theory; eigenvalues and eigenfunctions; digital arithmetic; adaptive filters; digital filters

Other keywords: modular processing architecture; Gram-Schmidt processor; arithmetic efficiency; adaptive eigenfilter; moving target indication processor; optimum MTI processor; fast convergence capability; steady-state performance

Subjects: Algebra; Signal processing and detection; Radar theory; Digital filters

References

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      • M.G. Larimore . Adaptive convergence of spectral estimation based on Pisarenko harmonicretrieval. IEEE Trans. Acoust., Speech, Signal Proc. , 4 , 955 - 962
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      • S. Haykin . (1990) Modern filters.
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      • D.C. Schleher . (1991) MTI and pulsed Doppler radar.
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      • A. Farina , A. Protopapa . New results on linear prediction for clutter cancellation. IEEE Trans. Aerospace and Electronic Systems , 3 , 275 - 285
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