Aerospace and Electronic Systems Magazine August 2017 - 57

Leclère, Botteron, and Farine
is to have as many zeros as possible in s′. Note that there are also
some variants of this method providing better performance but not
applicable to every code [35], [36].

[6]

CONCLUSION
In this article, we have performed a comparison of the possible
hardware implementations of the parallel code search acquisition
for GNSS signals having a secondary code. Since applying directly
the FFT over the entire tiered code is not possible or at least extremely consuming in hardware, a better solution already suggested in the literature is to perform FFT-based circular correlations
over the primary code and to combine the results. Focusing on this
solution, we have compared different hardware implementations,
including the cases when the combinations are performed before or
after the FFT-based correlations, when they are performed sequentially or in parallel, and when the output is provided in different
orders. Moreover, we also analyzed the memory requirements and
the processing time of each implementation.
From these comparisons, it has been shown that some implementations are not interesting (such as the one using a second FFTbased circular correlation for the secondary code), since they consume more memory and provide a longer processing time than other
implementations. It has also been shown that the direct correlation
that applies the FFT over the entire tiered code would not be interesting, because some proposed parallel implementations provides
slightly longer processing times, but require much less memory.
Generally, the choice of the most suitable implementation is a
compromise between the memory used and the processing time.
However, if the various parameters are specified (such as the quantization of the signals, the sampling frequency, the number of coherent or noncoherent accumulation, the number of frequency bins
to test), it will be easy to evaluate both the memory and the processing time using our results since all the formulas are provided.
In addition, we also have proposed a new method that approximately halves the number of operations related to the secondary
code correlation, and slightly reduces the total processing time
(12.6%) for a hardware implementation. The idea of this method
(which is not an approximation) is to add or subtract 1 to the binary secondary code to obtain a code with at least half of zeros to
perform the correlation.

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