MATLAB Program for Simulating DDS Spurious Characteristics

In the field of digital signal processing, Direct Digital Synthesis (DDS) technology is widely used in communication and radar systems due to its advantages of high resolution, fast switching capability, and low power consumption. However, spurious components present in DDS output signals can significantly impact system performance, making the analysis of DDS spurious characteristics crucial.

Through MATLAB simulation programs, we can efficiently model DDS spurious characteristics. The simulation primarily focuses on how phase truncation errors and amplitude quantization errors affect the output spectrum. Phase truncation results from the finite word length of the phase accumulator, while amplitude quantization arises from limited precision in waveform data stored in lookup tables (LUTs). In MATLAB implementation, this typically involves configuring parameters like phase_accumulator_bits and lut_resolution, then generating sinusoidal waveforms using trigonometric approximations or precomputed LUTs.

During simulation, parameters such as the number of phase accumulator bits and lookup table precision are typically set. The output signal spectrum is analyzed using FFT (Fast Fourier Transform) functions like fft() and pwelch(), allowing observation of spurious component distribution and amplitude levels. This simulation approach not only helps engineers understand DDS spurious characteristics but also provides references for practical system design, enabling optimization of parameter selection to reduce spurious effects. Key MATLAB functions would include phase accumulation algorithms using modulo arithmetic and spectrum analysis with windowing techniques.

By adjusting the phase accumulator bit width and lookup table size, improvements in spurious performance can be visually observed through spectral plots. Furthermore, the simulation can be extended to include other non-ideal factors such as clock jitter (modeled using random phase modulation) and DAC nonlinearity (implemented with quantization error models), thereby providing a more comprehensive evaluation of DDS system performance. The code structure would typically involve main simulation loops, error injection modules, and spectral visualization using MATLAB's plotting capabilities.