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GPS surveying methods vary in application, accuracy, and data collection techniques, catering to diverse surveying and mapping needs. Static GPS, kinematic GPS, and real-time kinematic (RTK) surveying are widely used. Each technique offers distinct advantages.Static GPS involves placing one receiver at a known reference point and another at the target point. It collects exact positional data by observing multiple satellite ranges over an extended period, achieving centimeter-level accuracy for...
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Introduction to Global Positioning System01:30

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The Global Positioning System (GPS) revolutionized positioning on Earth, providing precise location data through satellite ranging. The GPS system was developed in 1978 by the U.S. Department of Defense  for military use, and it became available for civilian applications in 1983, transforming fields including navigation, fleet management, and time synchronization for telecommunications systems.GPS consists of satellites in medium Earth orbit, about 20,200 kilometers above the surface,...
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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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Field Application of Global Positioning System01:28

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The Global Positioning System (GPS) has become an indispensable tool in fieldwork, offering unparalleled precision and efficiency for surveying, navigation, and infrastructure development. By harnessing signals from a constellation of satellites, GPS receivers determine the location of objects with remarkable speed and accuracy, often completing calculations within a second.Advantages of Modern GPS TechnologyContemporary GPS receivers are designed to meet the practical demands of field...
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Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

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Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...
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Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
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Related Experiment Video

Updated: Nov 15, 2025

Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements
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Low Complexity Robust Data Demodulation for GNSS.

Lorenzo Ortega1, Charly Poulliat2, Marie Laure Boucheret2

  • 1Telecommunications for Space and Aeronautics Lab (TéSA), 31500 Toulouse, France.

Sensors (Basel, Switzerland)
|March 6, 2021
PubMed
Summary
This summary is machine-generated.

This study offers new approximations for log-likelihood ratio (LLR) values in direct sequence spread spectrum (DS-SS) systems, improving performance in Global Navigation Satellite System (GNSS) environments. These methods enhance decoding accuracy by accounting for noise uncertainty, leading to significant frame error rate (FER) improvements.

Keywords:
GNSSSNR mismatchbayesian inferenceinterference countermeasurelow complexitynoise estimationrobust LLR

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Area of Science:

  • Signal Processing
  • Communications Engineering
  • Satellite Navigation Systems

Background:

  • Direct sequence spread spectrum (DS-SS) systems are crucial for Global Navigation Satellite System (GNSS) applications.
  • Accurate log-likelihood ratio (LLR) estimation is vital for reliable data decoding, especially under varying noise conditions.
  • Traditional methods often assume known noise variance, potentially causing demodulation errors in GNSS receivers.

Purpose of the Study:

  • To develop closed-form approximations for LLR values in DS-SS systems within GNSS environments.
  • To address the challenge of noise uncertainty in LLR estimation for improved demodulation.
  • To enhance the performance of decoding clock and ephemeris data (CED) encoded with low-density parity-check (LDPC) codes.

Main Methods:

  • Derivation of closed-form LLR expressions for additive white Gaussian and Laplacian noise channels under noise uncertainty.
  • Development of LLR approximations for noise variance following an inverse log-normal distribution.
  • Application and simulation of these LLR expressions in the context of GPS L1C signal decoding using the belief propagation (BP) algorithm.

Main Results:

  • The study provides novel closed-form approximations for LLR values applicable to common GNSS scenarios.
  • The proposed methods effectively handle noise uncertainty, unlike classical approaches.
  • Simulations demonstrate significant frame error rate (FER) improvements when decoding GPS L1C CED with LDPC codes.

Conclusions:

  • The derived closed-form LLR approximations offer a robust solution for DS-SS systems in GNSS, particularly under noise uncertainty.
  • Accounting for noise variance uncertainty leads to enhanced decoding performance and reduced FER.
  • These findings are relevant for improving the reliability and accuracy of satellite navigation systems.