Research on Direct Spread Spectrum Signal Monitoring Technology Based on Combined Partitioned Matched Filter–Fast Fourier Transform and Partitioned Matched Filter–Fractional Fourier Transform Algorithms
Huaiyi Guan, Jun Fu, Bao Li, Hongwei Wei, Pengfei Jiang, Shiyao Zhao, Yi Huang · Applied Sciences · 2025
To address the challenge of monitoring BeiDou RDSS signals under low signal-to-noise ratio (SNR) and high-dynamic conditions, this paper introduces a hierarchical joint processing algorithm combining PMF-FFT and PMF-FRFT. The method counters the energy dispersion issue in conventional FFT-based techniques by employing a two-stage “coarse–fine” strategy. A computationally efficient PMF-FFT performs a rapid coarse search, followed by an intelligent trigger, based on a correlation peak morphology, that initiates a localized PMF-FRFT fine search for high-dynamic signals, to precisely estimate the code phase, center frequency, and Doppler rate. Experimental results demonstrated that the algorithm’s acquisition performance was comparable to a global PMF-FRFT search and superior to the conventional PMF-FFT, achieving a 4.91% correlation peak improvement at −10 dB SNR and a gain of nearly 30% in extreme conditions (−20 dB SNR, 1000 Hz offset). Crucially, its average processing time (∼0.088 s) was on the same order of magnitude as PMF-FFT (∼0.0568 s) and significantly faster than global PMF-FRFT (∼0.3317 s). The proposed algorithm effectively balances detection performance with computational efficiency, offering a viable solution for the real-time monitoring of high-dynamic DSSS signals.