Low-Computation GNSS Acquisition Method for Sparse Doppler Frequency Hypotheses in High-Dynamic Environment

To acquire Global Navigation Satellite System (GNSS) signal in high-dynamic and long integration applications, the high dimensional search of this detection needs a high computational cost. To reduce the computations of parameters estimation, this paper proposes a low-computation GNSS acquisition method (LGAM) in the high-dynamic environment. Firstly, sparse Doppler frequency (SDF) process is performed for SDF hypotheses, and post-correlation signal model is derived based on SDF structure. Then, double-FFT based detection is proposed based on the post-correlation signal model for parameters estimation. The results demonstrate that due to the reduction of complex multiplications, the computational cost of LGAM is lower than that of the FFT based methods under the moderate signal to noise ratio.