In passive sonar, adaptive algorithms can be used to cancel strong sinusoidal self-interferences. In order to correctly recover low-power target signals during the early stages of processing, these adaptive algorithms must provide fast convergence and, at the same time, narrow notches at the frequencies of the sinusoids. In this respect, the gradient adaptive lattice (GAL) algorithm is a very attractive choice. However, the GAL algorithm with a constant step-size parameter has to compromise between the convergence rate and notch bandwidths. Therefore, in this article, we propose a variable step-size scheme for the GAL algorithm that can achieve both a fast convergence rate and narrow notches. Simulation results demonstrate the efficiency of the proposed algorithm compared to both the conventional GAL algorithm and transversal adaptive filter combined with the variable step-size scheme.
In this paper, we propose a high-order lattice adaptive notch filter (LANF) that can robustly track multiple sinusoids. Unlike the conventional cascade structure, the proposed high-order LANF has robust tracking characteristics regardless of the frequencies of reference sinusoids and initial notch frequencies. The proposed high-order LANF is applied to a narrowband adaptive noise cancellation (ANC) to mitigate the effect of the broadband disturbance in the reference signal. By utilizing the gradient adaptive lattice (GAL) ANC algorithm and approximately combining it with the proposed high-order LANF, a computationally efficient narrowband ANC system is obtained. Experimental results demonstrate the robustness of the proposed high-order LANF and the effectiveness of the obtained narrowband ANC system.
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