基于粒子群算法的Sigma-Delta调制器设计与优化

L. Li, Ge Chen
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引用次数: 1

摘要

本文提出了一种自适应的Sigma-Delta调制器,简化了参数调谐过程,进一步改善了噪声性能。传统的Sigma-Delta调制器主要是利用二阶传感元件来提高信噪比,而本文提出了一种五阶Sigma-Delta调制器来获得更高的信噪比。具体而言,在AFE和量化器之间插入一个额外的三阶数字环路积分器,这增加了整个环路的阶数,从而为Sigma-Delta调制器提供了更高的信噪比,并且通过群智能算法对三阶数字环路积分器的参数进行了优化。在[5-150Hz]的频率范围内,得到了5阶Sigma-Delta调制器的仿真结果,信噪比>122 dB,本底噪声在-170dB以下。在进一步的仿真中,分析了所提出的5阶Sigma-Delta调制器的鲁棒性。
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Designing and Optimizing of Sigma-Delta Modulator Using PSO Algorithm
A self-adaptive Sigma-Delta modulator, which offers opportunity to simplify the process of tuning parameters and further improve the noise performance, is presented in this paper. Traditional Sigma-Delta modulator mainly focused on using a 2nd order sensing element to improve the SNR, whereas this paper presents a 5th order Sigma-Delta modulator to obtain higher SNR. Specifically, an additional 3rd order digital loop integrator is inserted between the AFE and the quantizer, which increases overall loop order to produce much higher SNR for Sigma-Delta modulator and the parameters of the 3rd order digital loop integrator are optimized by swarm intelligent algorithm. Simulation results with respect to the proposed 5th order Sigma-Delta modulator, SNR >122 dB and the noise floor under -170dB are obtained in frequency range of [5-150Hz]. In further simulation, the robustness of the proposed 5th order Sigma-Delta modulator is analyzed.
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