20240012163. GNSS MEASUREMENT PROCESSING TO IDENTIFY MODES simplified abstract (u-blox AG)

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GNSS MEASUREMENT PROCESSING TO IDENTIFY MODES

Organization Name

u-blox AG

Inventor(s)

Ian Sheret of Hitchin (GB)

Olivier Julien of Oberrieden (CH)

Christopher David Hide of Reigate (GB)

Hayden Dorahy of Leatherhead (GB)

Roderick Bryant of Conder (AU)

GNSS MEASUREMENT PROCESSING TO IDENTIFY MODES - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240012163 titled 'GNSS MEASUREMENT PROCESSING TO IDENTIFY MODES

Simplified Explanation

The patent application describes a method and apparatus for processing GNSS (Global Navigation Satellite System) measurements, specifically carrier phase measurements. The method involves defining a state vector with state variables and obtaining a posterior probability density for the state vector. This probability density is based on non-Gaussian residual error models for the GNSS measurements. A systematic search is then performed on the posterior probability density to identify a set of modes of the probability density.

  • The patent application proposes a method for processing GNSS measurements using carrier phase measurements.
  • The method involves defining a state vector with state variables.
  • A posterior probability density for the state vector is obtained based on non-Gaussian residual error models for the GNSS measurements.
  • A systematic search is performed on the posterior probability density to identify a set of modes of the probability density.

Potential applications of this technology:

  • Precise positioning and navigation systems that rely on GNSS measurements.
  • Autonomous vehicles that require accurate and reliable GNSS data for navigation.
  • Surveying and mapping applications that require high-precision GNSS measurements.

Problems solved by this technology:

  • Overcoming the limitations of Gaussian error models for GNSS measurements, which may not accurately represent the true error distribution.
  • Improving the accuracy and reliability of GNSS measurements by incorporating non-Gaussian residual error models.
  • Enhancing the performance of GNSS-based positioning and navigation systems in challenging environments with multipath and signal interference.

Benefits of this technology:

  • Improved accuracy and reliability of GNSS measurements, leading to more precise positioning and navigation.
  • Enhanced performance of GNSS-based systems in challenging environments, resulting in better overall system performance.
  • Increased confidence in the integrity of GNSS measurements, reducing the risk of errors and potential safety hazards.


Original Abstract Submitted

a method and apparatus are disclosed for processing gnss measurements. the gnss measurements comprise carrier phase measurements. a state vector is defined, comprising state variables. a posterior probability density for the state vector is obtained, which is based on non-gaussian residual error models for the gnss measurements. a systematic search of the posterior probability density is performed, to identify a set of modes of the probability density.

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