Research on the Application of Parallel FFT Algorithms in Matched Filtering Techniques

The ever-increasing demands for signal processing speed and accuracy in modern communication or radar systems underscore the pivotal role of Matched Filtering (MF) as a critical signal processing technique in target detection. Parallel Fast Fourier Transform (PFFT) technology has demonstrated significant advantages in efficiently implementing matched filtering, notably reducing computational latency and optimizing resource utilization, thereby providing robust support for realtime signal processing tasks. This paper aims to enhance the computational efficiency and performance of matched filtering by leveraging PFFT processing techniques, employing multi-channel processing algorithms, and utilizing radix- 2² algorithms for twiddle factor computation. These approaches significantly improve the computational speed and efficiency of matched filtering operations.