ADC SNR and ENOB Calculator
Calculate analog-to-digital converter signal-to-noise ratio, effective number of bits (ENOB), and SFDR including aperture jitter effects
Formula
SNR_ideal = 6.02·N + 1.76 dB; SNR_jitter = −20·log₁₀(2π·f_in·t_j)
How It Works
An Analog-to-Digital Converter (ADC) is a critical component in electronic systems that converts continuous analog signals into discrete digital representations. Signal-to-Noise Ratio (SNR) and Effective Number of Bits (ENOB) are key performance metrics that describe the quality and precision of an ADC. SNR measures the ratio of the desired signal power to the noise power, while ENOB quantifies the actual resolution of the converter by accounting for non-ideal characteristics like distortion and noise.
Worked Example
Consider an 8-bit ADC with a full-scale range of 5V. If the input signal is a 1 kHz sine wave with an amplitude of 2V peak-to-peak, and the measured total harmonic distortion (THD) is -50 dB, the calculation would proceed as follows: First, calculate the theoretical SNR (ideal case) as 6.02N + 1.76 dB (where N is the number of bits). For an 8-bit ADC, this would be 6.02 * 8 + 1.76 = 50.92 dB. Then, use the measured THD to determine the actual ENOB by comparing the ideal and actual SNR performance.
Practical Tips
- ✓Always consider the full measurement bandwidth when calculating SNR
- ✓Use calibrated test equipment for accurate ADC performance characterization
- ✓Account for input signal frequency and amplitude variations
- ✓Consider temperature and environmental factors affecting ADC performance
Common Mistakes
- ✗Assuming ideal performance without accounting for real-world noise
- ✗Neglecting sampling rate and Nyquist criteria
- ✗Overlooking quantization errors in precision calculations
Frequently Asked Questions
What is the difference between SNR and SINAD?
SNR typically measures signal power to noise power, while SINAD (Signal-to-Noise and Distortion) includes harmonic distortion in the noise measurement
How does bit depth affect ADC performance?
Higher bit depth increases resolution and dynamic range, reducing quantization noise and improving signal representation
What factors impact ADC signal-to-noise ratio?
Key factors include sampling rate, input signal frequency, reference voltage, circuit design, and environmental conditions
Shop Components
Affiliate links — we may earn a commission at no cost to you.
Related Calculators
Signal
Nyquist Sampling
Calculate Nyquist sampling rate, oversampling ratio, aliasing frequency, ADC dynamic range, SNR, and data rate. Verify that your sampling rate satisfies the Nyquist criterion and avoid aliasing in your system.
Signal
SNR
Calculate SNR, noise floor, sensitivity, and dynamic range for RF receivers and signal chains
Signal
Johnson-Nyquist Noise
Calculate thermal noise voltage, noise power, and noise spectral density for resistors using the Johnson-Nyquist noise formula
Signal
Filter Designer
Design passive RC and LC Butterworth low-pass, high-pass, and band-pass filters. Calculates component values (C, L), time constant, and attenuation for filter orders 1 through 4.
Signal
FFT Resolution
Calculate FFT frequency bin resolution, Nyquist range, time record length, noise floor processing gain, and window scalloping loss
Signal
AM Modulation Index
Calculate amplitude modulation index, sidebands, bandwidth, and power efficiency for AM radio signals