SOOP Feature Models for Low-Bandwidth PNT Determination
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing PNT determination methods using signals of opportunity require high bandwidth communication channels, leading to latency and infrastructure complexity, limiting mobility and efficiency, especially when GPS/GNSS signals are unavailable or jammed.
Innovation Solution
A system that generates a model at a reference station based on SOOP characteristics, providing pre-loaded or transmitted parameters to mobile stations for PNT calculations, reducing the need for real-time high-bandwidth data transfer and enabling accurate positioning and timing determinations using machine learning and artificial intelligence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If raw recordings of SOOP are compared between reference and mobile stations, then positioning precision is improved, but communication bandwidth requirements increase significantly
Solution Approach 1:
The patent extracts only the essential features and parameters from the raw SOOP recordings at the reference station, rather than transmitting the complete raw data. This selective extraction of critical information maintains positioning precision while dramatically reducing the communication bandwidth required between reference and mobile stations.
Solution Approach 2:
Instead of the mobile station receiving and processing large amounts of raw reference station data, the approach is inverted: the reference station processes the raw recordings locally and transmits only the processed results (features and parameters) to the mobile station. This reverses the data flow direction and processing burden, reducing communication requirements.
2Measurement precision
If large data sets are transferred between reference and mobile stations, then positioning accuracy is improved, but calculation time increases
Solution Approach 1:
The reference station performs the computationally intensive signal processing and feature extraction in advance, before the mobile station needs the data. By pre-processing the SOOP recordings and preparing the essential parameters beforehand, the system maintains high positioning accuracy while minimizing the real-time calculation burden at the mobile station.
Solution Approach 2:
Rather than transferring and processing complete raw recordings, the system creates and transmits a simplified copy or representation of the essential signal characteristics. This copied form contains the necessary information for accurate positioning but requires significantly less computational resources to process.
3Measurement precision
If high bandwidth communication channels are used for SOOP comparison, then PNT determination accuracy is improved, but system complexity and infrastructure requirements increase
Solution Approach 1:
The patent extracts only the essential features and parameters from the raw SOOP recordings at the reference station, rather than transmitting the complete raw data. This selective extraction of critical information maintains positioning precision while dramatically reducing the communication bandwidth required between reference and mobile stations.
Solution Approach 2:
The reference station acts as an intermediary that processes raw SOOP recordings locally and extracts essential parameters before transmission. This intermediary processing step eliminates the need for complex real-time communication infrastructure between mobile and reference stations, as only processed parameter data needs to be transmitted.
Data Source
AI summary
Methods and apparatus to reduce communications for position, navigation and timing (PNT) determinations are disclosed. A disclosed example apparatus to enable PNT determination for a mobile station includes at least one memory, machine readable instructions, and processor circuitry to at least one of instantiate or execute the machine readable instructions to identify features of signals of opportunity (SOOP) measured at a reference station, generate a model based on the identified features of the SOOP in conjunction with a position and a timing of the reference station, and provide at least one of the model or parameters associated with the model to the mobile station for the PNT determination.


