Analog-to-Digital Conversion (ADC) is the process of transforming continuous analog signals into discrete digital data, enabling electronic systems to process real-world analog information using digital techniques. This conversion is essential in various applications, including audio recording, telecommunications, and sensor data acquisition.
Key Steps in ADC:
- Sampling: The continuous analog signal is sampled at discrete intervals to capture its instantaneous values. The sampling rate must be at least twice the highest frequency present in the signal to avoid aliasing, as per the Nyquist-Shannon Sampling Theorem.
- Quantization: Each sampled value is approximated to the nearest value within a finite set of discrete levels, introducing quantization error. The number of levels is determined by the ADC’s resolution, typically expressed in bits.
- Encoding: The quantized values are converted into binary code, representing the digital form of the analog signal.
Types of ADCs:
- Successive Approximation ADC: Utilizes a comparator and a digital-to-analog converter to iteratively approximate the input signal.
- Sigma-Delta ADC: Employs oversampling and noise shaping to achieve high-resolution conversion, often used in audio applications.
- Flash ADC: Uses a bank of comparators to simultaneously compare the input signal to reference voltages, providing very high-speed conversion but with lower resolution.
- Pipelined ADC: Processes multiple bits in stages, balancing speed and resolution, commonly used in communication systems.