• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

实时软件无线电对抗干扰 GPS/WAAS 传感器的设计与实现。

Design and implementation of real-time software radio for anti-interference GPS/WAAS sensors.

机构信息

Department of Aeronautics and Astronautics, Stanford University, 496 Lomita Mall, Stanford, CA 94305, USA.

出版信息

Sensors (Basel). 2012 Oct 1;12(10):13417-40. doi: 10.3390/s121013417.

DOI:10.3390/s121013417
PMID:23202002
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3545573/
Abstract

Adaptive antenna array processing is widely known to provide significant anti-interference capabilities within a Global Navigation Satellite Systems (GNSS) receiver. A main challenge in the quest for such receiver architecture has always been the computational/processing requirements. Even more demanding would be to try and incorporate the flexibility of the Software-Defined Radio (SDR) design philosophy in such an implementation. This paper documents a feasible approach to a real-time SDR implementation of a beam-steered GNSS receiver and validates its performance. This research implements a real-time software receiver on a widely-available x86-based multi-core microprocessor to process four-element antenna array data streams sampled with 16-bit resolution. The software receiver is capable of 12 channels all-in-view Controlled Reception Pattern Antenna (CRPA) array processing capable of rejecting multiple interferers. Single Instruction Multiple Data (SIMD) instructions assembly coding and multithreaded programming, the key to such an implementation to reduce computational complexity, are fully documented within the paper. In conventional antenna array systems, receivers use the geometry of antennas and cable lengths known in advance. The documented CRPA implementation is architected to operate without extensive set-up and pre-calibration and leverages Space-Time Adaptive Processing (STAP) to provide adaptation in both the frequency and space domains. The validation component of the paper demonstrates that the developed software receiver operates in real time with live Global Positioning System (GPS) and Wide Area Augmentation System (WAAS) L1 C/A code signal. Further, interference rejection capabilities of the implementation are also demonstrated using multiple synthetic interferers which are added to the live data stream.

摘要

自适应天线阵处理在全球导航卫星系统 (GNSS) 接收机中被广泛认为具有很强的抗干扰能力。在寻求这种接收机架构的过程中，一个主要的挑战一直是计算/处理要求。更具挑战性的是，试图在这种实现中纳入软件定义无线电 (SDR) 设计理念的灵活性。本文记录了一种可行的方法，即将波束导向 GNSS 接收机实时实现到 SDR 中，并验证其性能。该研究在广泛使用的基于 x86 的多核微处理器上实现了一个实时软件接收机，以处理用 16 位分辨率采样的四元天线阵数据流。该软件接收机能够处理 12 个全视场可控接收模式天线 (CRPA) 阵列处理通道，能够拒绝多个干扰源。单指令多数据 (SIMD) 指令集编码和多线程编程是实现这种降低计算复杂度的关键，本文对此进行了全面记录。在传统的天线阵系统中，接收器使用预先知道的天线几何形状和电缆长度。本文记录的 CRPA 实现旨在无需大量设置和预校准的情况下运行，并利用空时自适应处理 (STAP) 在频率和空间域提供自适应。本文的验证部分证明，所开发的软件接收机能够实时处理实时全球定位系统 (GPS) 和广域增强系统 (WAAS) L1 C/A 码信号。此外，还通过向实时数据流中添加多个合成干扰源来演示实现的干扰抑制能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/a4b5e6b85bfd/sensors-12-13417f16.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/ec2f243a3bc5/sensors-12-13417f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/fbcc8f7d5f19/sensors-12-13417f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/d9e51da00da6/sensors-12-13417f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/f7beccea6600/sensors-12-13417f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/f4c34f5071b8/sensors-12-13417f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/8d800abc4e9f/sensors-12-13417f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/3d9059d59e22/sensors-12-13417f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/2063a604378d/sensors-12-13417f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/885681f7e2b8/sensors-12-13417f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/1ac2507e3dbc/sensors-12-13417f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/07c89c83fc72/sensors-12-13417f11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/3f8dd8fdc0b8/sensors-12-13417f12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/c9cd0b06d36f/sensors-12-13417f13.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/74920684185c/sensors-12-13417f14.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/0371bd5b9015/sensors-12-13417f15.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/a4b5e6b85bfd/sensors-12-13417f16.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/ec2f243a3bc5/sensors-12-13417f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/fbcc8f7d5f19/sensors-12-13417f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/d9e51da00da6/sensors-12-13417f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/f7beccea6600/sensors-12-13417f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/f4c34f5071b8/sensors-12-13417f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/8d800abc4e9f/sensors-12-13417f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/3d9059d59e22/sensors-12-13417f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/2063a604378d/sensors-12-13417f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/885681f7e2b8/sensors-12-13417f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/1ac2507e3dbc/sensors-12-13417f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/07c89c83fc72/sensors-12-13417f11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/3f8dd8fdc0b8/sensors-12-13417f12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/c9cd0b06d36f/sensors-12-13417f13.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/74920684185c/sensors-12-13417f14.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/0371bd5b9015/sensors-12-13417f15.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c92/3545573/a4b5e6b85bfd/sensors-12-13417f16.jpg

相似文献

1
Design and implementation of real-time software radio for anti-interference GPS/WAAS sensors.实时软件无线电对抗干扰 GPS/WAAS 传感器的设计与实现。
Sensors (Basel). 2012 Oct 1;12(10):13417-40. doi: 10.3390/s121013417.
2
A real-time capable software-defined receiver using GPU for adaptive anti-jam GPS sensors.使用 GPU 的实时自适应抗干扰 GPS 传感器的软件定义接收器。
Sensors (Basel). 2011;11(9):8966-91. doi: 10.3390/s110908966. Epub 2011 Sep 19.
3
An SDR-Based Real-Time Testbed for GNSS Adaptive Array Anti-Jamming Algorithms Accelerated by GPU.一种基于软件定义无线电的实时测试平台，用于由GPU加速的全球导航卫星系统自适应阵列抗干扰算法
Sensors (Basel). 2016 Mar 11;16(3):356. doi: 10.3390/s16030356.
4
Implementation of a High-Sensitivity Global Navigation Satellite System Receiver on a System-on-Chip Field-Programmable Gate Array Platform.在片上系统现场可编程门阵列平台上实现高灵敏度全球导航卫星系统接收机
Sensors (Basel). 2024 Feb 22;24(5):1416. doi: 10.3390/s24051416.
5
GNSS-ISE: Instruction Set Extension for GNSS Baseband Processing.GNSS-ISE：全球导航卫星系统基带处理的指令集扩展。
Sensors (Basel). 2020 Jan 14;20(2):465. doi: 10.3390/s20020465.
6
NaviSoC: High-Accuracy Low-Power GNSS SoC with an Integrated Application Processor.导航片上系统：集成应用处理器的高精度低功耗全球导航卫星系统片上系统
Sensors (Basel). 2020 Feb 16;20(4):1069. doi: 10.3390/s20041069.
7
GNSS space-time interference mitigation and attitude determination in the presence of interference signals.存在干扰信号时的全球导航卫星系统时空干扰缓解与姿态确定
Sensors (Basel). 2015 May 26;15(6):12180-204. doi: 10.3390/s150612180.
8
Design and Installed Performance Analysis of a Miniaturized All-GNSS Bands Antenna Array for Robust Navigation on UAV Platforms.一种用于无人机平台稳健导航的小型全 GNSS 波段天线阵列的设计和安装性能分析。
Sensors (Basel). 2022 Dec 9;22(24):9645. doi: 10.3390/s22249645.
9
An Enhanced FGI-GSRx Software-Defined Receiver for the Execution of Long Datasets.一种用于执行长数据集的增强型FGI-GSRx软件定义接收机。
Sensors (Basel). 2024 Jun 20;24(12):4015. doi: 10.3390/s24124015.
10
Vertical guidance performance analysis of the L1-L5 dual-frequency GPS/WAAS user avionics sensor.L1-L5 双频 GPS/WAAS 用户航空电子传感器的垂直引导性能分析。
Sensors (Basel). 2010;10(4):2609-25. doi: 10.3390/s100402609. Epub 2010 Mar 25.

引用本文的文献

1
A Joint Method Based on Time-Frequency Distribution to Detect Time-Varying Interferences for GNSS Receivers with a Single Antenna.一种基于时频分布的联合方法，用于检测单天线GNSS接收机的时变干扰。
Sensors (Basel). 2019 Apr 25;19(8):1946. doi: 10.3390/s19081946.
2
Low-Cost Curb Detection and Localization System Using Multiple Ultrasonic Sensors.基于多个超声波传感器的低成本路缘检测与定位系统。
Sensors (Basel). 2019 Mar 21;19(6):1389. doi: 10.3390/s19061389.
3
SFOL Pulse: A High Accuracy DME Pulse for Alternative Aircraft Position and Navigation.

本文引用的文献

1
A real-time capable software-defined receiver using GPU for adaptive anti-jam GPS sensors.使用 GPU 的实时自适应抗干扰 GPS 传感器的软件定义接收器。
Sensors (Basel). 2011;11(9):8966-91. doi: 10.3390/s110908966. Epub 2011 Sep 19.
SFOL脉冲：一种用于替代飞机定位和导航的高精度测距设备脉冲
Sensors (Basel). 2017 Sep 22;17(10):2183. doi: 10.3390/s17102183.
4
An SDR-Based Real-Time Testbed for GNSS Adaptive Array Anti-Jamming Algorithms Accelerated by GPU.一种基于软件定义无线电的实时测试平台，用于由GPU加速的全球导航卫星系统自适应阵列抗干扰算法
Sensors (Basel). 2016 Mar 11;16(3):356. doi: 10.3390/s16030356.
5
GNSS space-time interference mitigation and attitude determination in the presence of interference signals.存在干扰信号时的全球导航卫星系统时空干扰缓解与姿态确定
Sensors (Basel). 2015 May 26;15(6):12180-204. doi: 10.3390/s150612180.
6
Precise calibration of a GNSS antenna array for adaptive beamforming applications.用于自适应波束形成应用的全球导航卫星系统（GNSS）天线阵列的精确校准。
Sensors (Basel). 2014 May 30;14(6):9669-91. doi: 10.3390/s140609669.