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方差触发式两步全球定位系统捕获

Variance-Triggered Two-Step GPS Acquisition.

作者信息

Costa Fabrício, Albuquerque Glauberto Leilson, Silveira Luiz Felipe, Valderrama Carlos, Xavier-de-Souza Samuel

机构信息

Departamento de Computação e Automação (DCA), Universidade Federal do Rio Grande do Norte, Natal 59078-970, Brazil.

Service d'électronique et de Microélectronique (SEMi), Universitè de Mons, 7000 Mons, Belgium.

出版信息

Sensors (Basel). 2019 Jul 19;19(14):3177. doi: 10.3390/s19143177.

DOI:10.3390/s19143177
PMID:31330949
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6679285/
Abstract

The acquisition is the most time-consuming step performed by a Global Navigation Satellite System (GNSS) receiver. The objective is to detect which satellites are transmitting and what are the phase and Doppler frequency shift of the signal. It is the step with the highest computational complexity, especially for signals subjected to large Doppler shifts. Improving acquisition performance has a large impact on the overall performance of the GNSS reception. In this paper, we present a two-step Global Positioning System (GPS) acquisition algorithm whose first step performs an incremental correlation to find a coarse pair of phase and frequency and the second step, triggered by the variance of the largest correlation values, refines the first step. The proposed strategy, based on the conventional time-domain serial algorithm, reduces the average execution time of the acquisition process to about 1/5 of the conventional acquisition while keeping the same modest logic hardware requirements and slightly better success and false-positive rates. Additionally, the new method reduces memory usage by a factor that is proportional to the signal's sampling frequency. All these advantages over conventional acquisition contribute together to significantly improve the overall performance and cost of GPS receivers.

摘要

捕获是全球导航卫星系统(GNSS)接收机执行的最耗时步骤。其目标是检测哪些卫星正在发射信号,以及信号的相位和多普勒频移是多少。这是计算复杂度最高的步骤,尤其是对于经历大多普勒频移的信号。提高捕获性能对GNSS接收的整体性能有很大影响。在本文中,我们提出了一种两步全球定位系统(GPS)捕获算法,其第一步执行增量相关以找到相位和频率的粗略对,第二步由最大相关值的方差触发,对第一步进行细化。所提出的策略基于传统的时域串行算法,在保持相同适度逻辑硬件要求以及略好的成功率和误报率的同时,将捕获过程的平均执行时间减少到传统捕获的约1/5。此外,新方法将内存使用量减少了与信号采样频率成比例的系数。相对于传统捕获的所有这些优势共同作用,显著提高了GPS接收机的整体性能和成本。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/27e4a366821b/sensors-19-03177-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/6e3df28b942b/sensors-19-03177-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/70f55b6ea6a1/sensors-19-03177-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/3b7f43871c83/sensors-19-03177-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/9249c6bfd06f/sensors-19-03177-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/430e65eb0a8f/sensors-19-03177-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/529ed6757fbb/sensors-19-03177-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/f0e69e930d29/sensors-19-03177-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/5f1bba1c4650/sensors-19-03177-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/04b0023ea6e0/sensors-19-03177-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/27e4a366821b/sensors-19-03177-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/6e3df28b942b/sensors-19-03177-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/70f55b6ea6a1/sensors-19-03177-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/3b7f43871c83/sensors-19-03177-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/9249c6bfd06f/sensors-19-03177-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/430e65eb0a8f/sensors-19-03177-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/529ed6757fbb/sensors-19-03177-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/f0e69e930d29/sensors-19-03177-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/5f1bba1c4650/sensors-19-03177-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/04b0023ea6e0/sensors-19-03177-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58be/6679285/27e4a366821b/sensors-19-03177-g010.jpg

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本文引用的文献

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A Double Dwell High Sensitivity GPS Acquisition Scheme Using Binarized Convolution Neural Network.基于二值化卷积神经网络的双驻留高灵敏度 GPS 捕获方案
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Low Computational Signal Acquisition for GNSS Receivers Using a Resampling Strategy and Variable Circular Correlation Time.使用重采样策略和可变循环相关时间的全球导航卫星系统(GNSS)接收机的低计算信号采集
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