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Maximum likelihood identification of glint noise

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1 Author(s)
Wen-Rong Wu ; Dept. of Commun. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan

If the non-Gaussian distribution function of radar glint noise is known, the Masreliez filter can be applied to improve target tracking performance. We investigate the glint identification problem using the maximum likelihood (ML) method. Two models for the glint distribution are used, a mixture of two Gaussian distributions and a mixture of a Gaussian and a Laplacian distribution. An efficient initial estimate method based on the QQ-plot is also proposed. Simulations show that the ML estimates converge to truths.

Published in:

Aerospace and Electronic Systems, IEEE Transactions on  (Volume:32 ,  Issue: 1 )