一种基于频域采样的序列快速捕获算法
doi: 10.3724/SP.J.1146.2011.01383
A Fast Sequential Acquisition Method Based on Frequency Sampling
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摘要: 该文针对长周期序列捕获中存在的运算开销大、接收序列有限条件下捕获效果差等问题,提出一种基于频域采样的序列快速捕获算法。依据序列时频关系,建立部分频域捕获模型,通过采样构造本地序列部分频域集,利用最优采样频域集与接收序列相关实现捕获。序列频域采样等效为时域内引入相位权值后分段叠加,降低运算开销的同时改变了非峰值项概率分布,有利于抑制背景噪声。仿真结果表明,当本地序列周期217时,该文算法可降低运算开销27倍,较扩展重叠算法平均捕获成功率提高约50%。Abstract: 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.
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Key words:
- Signal processing /
- Sequential acquisition /
- Sample /
- m sequence /
- Discrete Fourier Transform (DFT)
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