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Optimizing Signal Processing Kernels for GNSS Software Receivers

机译:优化GNSS软件接收器的信号处理内核

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The Software Defined Radio (SDR) paradigm as applied to GNSS has blossomed in the last twenty years. This approach involves performing all the high rate processing from Intermediate Frequency (IF) to baseband, including acquisition, tracking and observation generation, in software. In this time interval the capabilities of modern processors have evolved significantly, enabling more interesting processing, of more signals with wider bandwidths. Equally, low cost or embedded platforms today have processing capabilities surpassing those of the desktop computers used in the first experiments in GNSS SDR. In this work we investigate the possibilities for optimizing the software implementation of high rate GNSS signal processing tasks. In contrast to some earlier work in this field, rather than considering the optimization of a specific operation for a specific platform, we consider the general problem of maintaining a software code base that is capable of performing across a range of target machines, with a range of performance requirements, both in terms of processing efficiency (the number of channels that can be processed in real time, for example) and the processing accuracy (certain approximations can reduce the computational complexity at the cost of a loss in Signal-to-Noise Ratio (SNR) or ranging performance).
机译:在最近的20年中,应用于GNSS的软件定义无线电(SDR)范式蓬勃发展。这种方法涉及在软件中执行从中频(IF)到基带的所有高速率处理,包括采集,跟踪和观察生成。在此时间间隔内,现代处理器的功能得到了显着发展,可以对带宽更大的更多信号进行更有趣的处理。同样,当今的低成本或嵌入式平台具有的处理能力已经超过了GNSS SDR首次实验中使用的台式计算机的处理能力。在这项工作中,我们研究了优化高速率GNSS信号处理任务的软件实现的可能性。与该领域的一些早期工作相比,我们没有考虑针对特定平台优化特定操作的问题,而是考虑了维护软件代码库的一般问题,该软件代码库可以跨一定范围的目标计算机执行性能要求,包括处理效率(例如可以实时处理的通道数)和处理精度(某些近似值都可以降低计算复杂度,但会损失信噪比)比率(SNR)或测距性能)。

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