Coherent detection by function elimination filtering in the presence of sinusoidal interference

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Abstract
The present paper deals with the numerical investigation of a narrowband interference suppression by function elimination filtering (FEF) baaed on linear prediction (LP). This paper mainly dwells on the optimization problem in order to increase the interference immunity in the presence of both a narrowband interference with unknown parameters and a Gaussian random process. The algorithm considered docs not require any auxiliary reference input and it is represented by linear signal processing. It should be emphasized that this FEF permits the suppression of a sinusoidal interference by linear prediction during the strongly limited observation interval. it is shown that this FEF makes possible a signal-to-noise ratio (SNR) that is almost independent of sinusoidal interference with unknown arbitrary parameters. Moreover, this SNR is close to the same ratio that can be obtained by the conventional matched filter, optimal only in the Gaussian noise channel. This property of the proposed algorithm follows from its linear structure and is the most essential difference between it and the previously proposed FEFs (Plotkin 1977, 1978). The numerical results of testing this filter together with a threshold device are given in relation to the coherent detection problem.

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