All-Phase FFT Implementation: Algorithm Overview and Code Integration

All-phase FFT is a specialized Fast Fourier Transform algorithm designed for signal processing, originally proposed and rigorously demonstrated by Professors Wang Zhaohua and Hou Zhengxin from Tianjin University. This algorithm offers two significant advantages in spectral analysis: initial phase invariance and effective prevention of spectral leakage.

The initial phase invariance characteristic ensures the preservation of the signal's original phase information, which is particularly crucial for applications requiring precise phase measurements. The spectral leakage suppression capability significantly enhances spectral analysis accuracy when processing non-integer periodic sampled signals.

In practical implementation, all-phase FFT achieves these advantages through specialized data preprocessing methods and window function design. The core algorithmic concept involves specific segmentation and overlap processing of the original signal, resulting in more stable and reliable transformation outcomes. Key implementation aspects include careful window function selection (typically using symmetric windows) and proper data overlap handling through array manipulation techniques. The algorithm is particularly suitable for applications demanding high spectral precision, such as power system harmonic analysis and vibration signal analysis.

Although the original literature provides MATLAB implementations, the core algorithm can be adapted to other programming platforms. Critical implementation considerations include window function optimization (using functions like hanning or hamming) and proper data framing with overlap-add techniques. The processing pipeline typically involves signal segmentation, window application, FFT computation, and phase correction - all essential for maintaining algorithm performance.