Spectral Analysis of ADC Sampled Signals with Performance Parameter Calculation

Spectral analysis of ADC (Analog-to-Digital Converter) sampled signals involves calculating crucial parameters such as Signal-to-Noise Ratio (SNR) and Effective Number of Bits (ENOB). Spectral analysis helps characterize signal frequency components and energy distribution, enabling assessment of signal quality and performance. SNR calculation determines the ratio between signal and noise power, indicating signal clarity and reliability. ENOB represents the actual effective resolution of ADC output data, reflecting converter precision and accuracy. Implementation typically involves applying FFT algorithms (e.g., using MATLAB's fft() function or Python's numpy.fft) to sampled data, followed by power spectral density estimation. Parameter calculations require proper windowing functions (Hanning, Hamming) to minimize spectral leakage and coherent sampling techniques for accurate results. Thus, spectral analysis with SNR and ENOB computation forms essential ADC performance validation methodology in signal processing systems.