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FFT Splitting for Improved FPGA-Based Acquisition of GNSS Signals

机译：FFT分割可改善基于FPGA的GNSS信号采集

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摘要

With modern global navigation satellite system (GNSS) signals, the FFT-based parallel code search acquisition must handle the frequent sign transitions due to the data or the secondary code. There is a straightforward solution to this problem, which consists in doubling the length of the FFTs, leading to a significant increase of the complexity. The authors already proposed a method to reduce the complexity without impairing the probability of detection. In particular, this led to a 50% memory reduction for an FPGA implementation. In this paper, the authors propose another approach, namely, the splitting of a large FFT into three or five smaller FFTs, providing better performances and higher flexibility. For an FPGA implementation, compared to the previously proposed approach, at the expense of a slight increase of the logic and multiplier resources, the splitting into three and five allows, respectively, a reduction of 40% and 64% of the memory, and of 25% and 37.5% of the processing time. Moreover, with the splitting into three FFTs, the algorithm is applicable for sampling frequencies up to 24.576 MHz for L5 band signals, against 21.846 MHz with the previously proposed algorithm. The algorithm is applied here to the GPS L5 and Galileo E5a, E5b, and El signals.
机译：对于现代全球导航卫星系统（GNSS）信号，基于FFT的并行代码搜索获取必须处理由于数据或辅助代码而引起的频繁符号转换。对于这个问题有一个直接的解决方案，其中包括使FFT的长度加倍，从而导致复杂性的显着增加。作者已经提出了一种在不损害检测概率的情况下降低复杂度的方法。特别是，这导致FPGA实现的内存减少了50％。在本文中，作者提出了另一种方法，即将大型FFT分为三个或五个较小的FFT，以提供更好的性能和更高的灵活性。对于FPGA实施，与先前提出的方法相比，以逻辑和乘法器资源的略微增加为代价，分为三部分和五部分分别减少了40％和64％的内存，以及处理时间的25％和37.5％。此外，通过分成三个FFT，该算法适用于L5频段信号的最高采样频率为24.576 MHz，而先前提出的算法为21.846 MHz。该算法在此处应用于GPS L5和Galileo E5a，E5b和El信号。

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  • 来源
    《International journal of navigation and observation》 |2015年第2015期|765898.1-765898.12|共12页
  • 作者

    Jerome Leclere; Cyril Botteron; Rene Jr. Landry; Pierre-Andre Farine;

  • 作者单位

    Electronics and Signal Processing Laboratory (ESPLAB), Ecole Polytechnique Federate de Lausanne (EPFL), 2000 Neuchatel, Switzerland,Laboratory of Space Technologies, Embedded Systems, Navigation and Avionic (LASSENA), Ecole de Technologie Superieure (ETS), Montreal, QC, Canada H3C 1K3;

    Electronics and Signal Processing Laboratory (ESPLAB), Ecole Polytechnique Federate de Lausanne (EPFL), 2000 Neuchatel, Switzerland;

    Laboratory of Space Technologies, Embedded Systems, Navigation and Avionic (LASSENA), Ecole de Technologie Superieure (ETS), Montreal, QC, Canada H3C 1K3;

    Electronics and Signal Processing Laboratory (ESPLAB), Ecole Polytechnique Federate de Lausanne (EPFL), 2000 Neuchatel, Switzerland;

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