Low-computation GNSS post-correlation signal parameter estimation method based on the complex signal phase in a high-dynamic environment

To estimate global navigation satellite system (GNSS) post-correlation signal parameters in a highly dynamic environment with low complexity, we propose a GNSS acquisition method based on the complex signal phase (CSP). The proposed method is based on the idea that compared with the fast Fourier transform (FFT)-based method, the single-frequency signal estimation method based on CSP can achieve high-precision frequency estimation with a small number of signal points at a high signal-to-noise ratio (SNR). Compared to the FFT-based method, which uses a search process to estimate frequency parameters, the proposed method directly uses the CSP of the received signal to estimate frequency parameters. However, there are some problems for the method based on this idea. In detail, due to the influence of bit signs and noise on peak detection, adjacent differential processing, coherent integration and coarse initial frequency search processing procedures are adopted to address the detection peak reduction problem. Moreover, the detection performance of the proposed method is analyzed. The simulation results show that the proposed method can achieve the same estimation accuracy with low complexity at a moderate signal-to-noise ratio (SNR) compared with block accumulating semicoherent integration of correlations (BASIC). In particular, when the post-correlation signal SNR is higher than 8 dB, the proposed method can achieve the same chirping rate and initial frequency estimation accuracy as BASIC.