GNSS Signal Classification Using Hemispherical Imaging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing Global Navigation Satellite Systems (GNSS) face challenges in accurately processing signals due to obstructions like buildings and tree canopies, which cause signal attenuation and multipath reception, making it difficult to identify affected or unaffected satellite signals effectively.
Innovation Solution
Employing a hemispherical or fisheye lens with an imaging device to determine the line-of-sight view of GNSS satellites, classifying signals based on obstruction levels, and using satellite usability classification data to prioritize signal processing in GNSS receivers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If traditional multipath mitigation techniques (choke rings, circularly polarized antenna elements, software algorithms) are used, then multipath signals from typical reflectors are attenuated, but these methods cannot identify specific GNSS satellite signals affected by passing obstructions like canopy
Solution Approach 1:
An imaging device is introduced as an intermediary between the antenna and the processing system. The imaging device captures visual information about the sky and obstructions, providing a mediator that enables identification of which satellites are affected by passing obstructions. This visual intermediary allows the system to distinguish between satellites with clear line-of-sight and those blocked by canopy or other objects.
Solution Approach 2:
The patent replaces traditional mechanical multipath mitigation techniques (choke rings, circularly polarized antenna elements) with an optical imaging system. Instead of using physical structures to block multipath signals, the system uses an imaging device to visually identify and classify satellite signals based on their spatial relationship with obstructions, substituting mechanical filtering with optical detection and software classification.
2Quantity of substance
If all available GNSS satellite signals are processed without classification, then signal availability is maximized, but accuracy of GNSS fixes degrades due to attenuated and distorted signals from obstructed satellites
Solution Approach 1:
The patent applies local quality by classifying individual satellite signals based on their specific line-of-sight conditions. Instead of treating all signals uniformly, the system evaluates each satellite's individual obstruction status using the imaging device and assigns different quality levels (e.g., clear view, partially obstructed, completely blocked). This allows the processing system to weight or exclude specific signals based on their local quality characteristics.
Solution Approach 2:
The patent segments the set of all available GNSS satellite signals into distinct categories based on obstruction status. The imaging device divides the sky field of view into regions corresponding to different satellites, and the processing system segments signals into groups such as unobstructed, partially obstructed, and completely blocked. This segmentation enables selective processing of signals based on their quality characteristics.
3Difficulty of detecting and measuring
If imaging device and signal classification system are added to GNSS receiver, then identification of line-of-sight satellites is improved, but device complexity increases
Solution Approach 1:
The imaging device serves multiple functions: it captures visual information about the sky, identifies obstructions, determines line-of-sight conditions for specific satellites, and provides data for signal classification. By making the imaging device multi-functional, the system reduces the need for separate dedicated components for each function, thereby limiting the increase in overall device complexity while achieving improved line-of-sight detection capability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for more accurate GNSS fixes by distinguishing between usable, suspect, and non-usable satellite signals, improving the reliability and quality of positioning data, especially in obstructed environments.
Implementation Method 1
Employing a hemispherical or fisheye lens with an imaging device to determine the line-of-sight view of GNSS satellites
Implementation Method 2
focus rays onto a detector
Data Source
AI summary
In accordance with embodiments of the invention, a skyward-looking sensor enables classification of points in its hemispherical field of view as either sky, partial sky or not sky, which in turn enables determination from data supplied by the GNSS receiver of whether each satellite in the GNSS antenna's field of view is in a region of sky, partial sky or not sky. Pseudrange and phase data from GNSS satellites determined to be in a region of sky can be considered reliable and used with confidence in a positioning solution. Pseudrange and phase data from GNSS satellites determined to be in a region of partial sky can be considered suspect and can therefore only contribute to a position solution with limited confidence and decreased accuracy. Pseudorange and phase data from GNSS satellites determined to be in a region of no sky can be considered unreliable and excluded from use in a positioning solution.