A Fast Sequential Acquisition Method Based on Frequency Sampling

To solve sequential acquisition problems with long pseudo-noise code, such as large computation cost and poor capture performance in the environment of few received sequences, a fast sequential acquisition method based on frequency sampling is proposed. Firstly, the general sequential acquisition model based on frequency subset is designed according to the sequential relationship between frequency and time domain. And then the frequency subsets are composed by sampling the complete frequency set of entire local sequences. The optimal subsets are used to do cyclic correlation operation with received sequences to accomplish capture at the end. In the perspective of time domain, frequency sampling is equal to sequences folding, and some phase weighting factors are imported simultaneously, which can improve the probability distribution of nonpeak values. Therefore, the acquisition computation cost is reduced in higher degree and the background noise is compressed at the same time. The simulation results show that frequency sampling method can reduce computation cost by 27 times, and its average capture success rate is probably 50% larger than XFAST, when the period of local sequences is 217.