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干扰环境下基于盲自适应波束形成方法的毫米级精度全球导航卫星系统定位

Millimetre Level Accuracy GNSS Positioning with the Blind Adaptive Beamforming Method in Interference Environments.

作者信息

Daneshmand Saeed, Marathe Thyagaraja, Lachapelle Gérard

机构信息

Department of Geomatics Engineering, University of Calgary, PLAN Group Schulich School of Engineering, 2500 University Drive, N.W., Calgary, AB T2N 1N4, Canada.

出版信息

Sensors (Basel). 2016 Oct 31;16(11):1824. doi: 10.3390/s16111824.

DOI:10.3390/s16111824
PMID:27809252
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5134483/
Abstract

The use of antenna arrays in Global Navigation Satellite System (GNSS) applications is gaining significant attention due to its superior capability to suppress both narrowband and wideband interference. However, the phase distortions resulting from array processing may limit the applicability of these methods for high precision applications using carrier phase based positioning techniques. This paper studies the phase distortions occurring with the adaptive blind beamforming method in which satellite angle of arrival (AoA) information is not employed in the optimization problem. To cater to non-stationary interference scenarios, the array weights of the adaptive beamformer are continuously updated. The effects of these continuous updates on the tracking parameters of a GNSS receiver are analyzed. The second part of this paper focuses on reducing the phase distortions during the blind beamforming process in order to allow the receiver to perform carrier phase based positioning by applying a constraint on the structure of the array configuration and by compensating the array uncertainties. Limitations of the previous methods are studied and a new method is proposed that keeps the simplicity of the blind beamformer structure and, at the same time, reduces tracking degradations while achieving millimetre level positioning accuracy in interference environments. To verify the applicability of the proposed method and analyze the degradations, array signals corresponding to the GPS L1 band are generated using a combination of hardware and software simulators. Furthermore, the amount of degradation and performance of the proposed method under different conditions are evaluated based on Monte Carlo simulations.

摘要

由于全球导航卫星系统(GNSS)应用中的天线阵列具有抑制窄带和宽带干扰的卓越能力,其使用正受到广泛关注。然而,阵列处理产生的相位失真可能会限制这些方法在基于载波相位定位技术的高精度应用中的适用性。本文研究了自适应盲波束形成方法中出现的相位失真,该方法在优化问题中未采用卫星到达角(AoA)信息。为了适应非平稳干扰场景,自适应波束形成器的阵列权重会持续更新。分析了这些持续更新对GNSS接收机跟踪参数的影响。本文的第二部分重点在于减少盲波束形成过程中的相位失真,以便通过对阵列配置结构施加约束并补偿阵列不确定性,使接收机能够进行基于载波相位的定位。研究了先前方法的局限性,并提出了一种新方法,该方法保持了盲波束形成器结构的简单性,同时在干扰环境中实现毫米级定位精度的同时减少跟踪性能下降。为了验证所提方法的适用性并分析性能下降情况,使用硬件和软件模拟器相结合的方式生成了与GPS L1频段对应的阵列信号。此外,基于蒙特卡罗模拟评估了所提方法在不同条件下的性能下降量和性能表现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f303/5134483/56175023ce26/sensors-16-01824-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f303/5134483/9e850dc79bbc/sensors-16-01824-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f303/5134483/8178534e7f5e/sensors-16-01824-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f303/5134483/d8476312f2e2/sensors-16-01824-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f303/5134483/aa7c124a5f01/sensors-16-01824-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f303/5134483/b315bedd0423/sensors-16-01824-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f303/5134483/499b733d24e6/sensors-16-01824-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f303/5134483/0812f210a879/sensors-16-01824-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f303/5134483/56175023ce26/sensors-16-01824-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f303/5134483/9e850dc79bbc/sensors-16-01824-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f303/5134483/8178534e7f5e/sensors-16-01824-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f303/5134483/d8476312f2e2/sensors-16-01824-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f303/5134483/aa7c124a5f01/sensors-16-01824-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f303/5134483/b315bedd0423/sensors-16-01824-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f303/5134483/499b733d24e6/sensors-16-01824-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f303/5134483/0812f210a879/sensors-16-01824-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f303/5134483/56175023ce26/sensors-16-01824-g008.jpg

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本文引用的文献

1
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2
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Sensors (Basel). 2014 May 30;14(6):9669-91. doi: 10.3390/s140609669.