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Global Positioning System (GPS) technology has revolutionized navigation and positioning, but its accuracy is often compromised by various errors. These errors, stemming from environmental, satellite, and receiver-related factors, require careful mitigation to ensure reliable performance across applications.Atmospheric ErrorsGPS signals travel through the Earth’s ionosphere and troposphere, introducing delays which affect accuracy. The ionosphere is strongly influenced by charged particles,...
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An SDR-Based Real-Time Testbed for GNSS Adaptive Array Anti-Jamming Algorithms Accelerated by GPU.

Hailong Xu1, Xiaowei Cui2, Mingquan Lu3

  • 1Department of Electronic Engineering, Tsinghua University, Weiqing Building, Tsinghua, Beijing 100084, China. xuhl07@163.com.

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|March 16, 2016
PubMed
Summary
This summary is machine-generated.

A new GPU-accelerated software-defined radio testbed enhances Global Navigation Satellite System (GNSS) adaptive array anti-jamming research. This flexible platform offers high performance for real-time processing of complex adaptive algorithms.

Keywords:
Global Navigation Satellite System (GNSS) anti-jammingSpace-Frequency Adaptive Processing (SFAP)Space-Time Adaptive Processing (STAP)adaptive arraybeamformingnullingsoftware-define radio (SDR)

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Area of Science:

  • Electrical Engineering
  • Computer Science
  • Signal Processing

Background:

  • Software-defined radio (SDR) is crucial for evaluating new algorithms.
  • GNSS adaptive array anti-jamming faces limitations due to high computational demands, inflexibility, and lack of configurability in prior research.

Purpose of the Study:

  • To design and implement a flexible, high-performance SDR-based real-time testbed for GNSS adaptive array anti-jamming.
  • To accelerate adaptive algorithms using Graphics Processing Units (GPUs) and explore Space-Time Adaptive Processing (STAP) and Space-Frequency Adaptive Processing (SFAP).

Main Methods:

  • Developed an SDR testbed leveraging GPU acceleration for real-time GNSS anti-jamming.
  • Implemented STAP and SFAP algorithms with extensive parameterization.
  • Utilized a batched programming method to maximize GPU parallelism.
  • Processed real-time data from up to eight antenna elements in adaptive nulling or beamforming modes.

Main Results:

  • The testbed provides a feature-rich, extendible platform with high computational performance.
  • Demonstrated real-time processing capabilities for complex adaptive algorithms.
  • Evaluated both computational efficiency and anti-jamming performance through rigorous testing.

Conclusions:

  • The GPU-accelerated SDR testbed significantly advances GNSS adaptive array anti-jamming research.
  • The platform offers a flexible and configurable solution for research, prototyping, and potential product applications.