Collaborative PNT Processing for Distributed Nodes
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Solution Overview
Problem
Existing navigation and positioning systems, such as GPS, face limitations in accuracy due to intrinsic characteristics, visibility, signal strength, and other factors, which affect the precision of positioning, navigation, and timing (PNT) solutions for nodes in distributed sensing systems.
Innovation Solution
A method utilizing a collaborative PNT processing module that receives carrier phase and pseudorange measurements from multiple nodes, models error characteristics using independent and joint error probabilities, and applies a statistical model-based estimator like the extended Kalman filter to improve PNT solutions, along with the Two-Way Time Transfer technique to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If satellite navigation systems such as GPS are utilized to provide PNT information for each node, then PNT information can be obtained for multiple nodes, but the accuracy of such PNT information is limited due to intrinsic accuracy characteristics, visibility, and signal strength factors
Solution Approach 1:
The patent combines PNT information from multiple satellite navigation systems (GPS, GLONASS, Galileo, BeiDou) into a unified collaborative processing framework. By merging measurements from multiple sources and nodes, the system achieves higher accuracy and reliability than individual systems can provide alone, directly resolving the contradiction between obtaining PNT information and maintaining high accuracy.
Solution Approach 2:
The patent implements feedback mechanisms where each node's PNT solution is continuously refined based on collaborative information from other nodes. The system uses observed discrepancies between nodes to adjust and improve individual PNT solutions, creating a self-correcting feedback loop that enhances both accuracy and reliability simultaneously.
2Adaptability or versatility
If distributed sensing is utilized with multiple disparate nodes moving independently, then various sensing applications can be enabled, but the complexity of coordinating and processing data from multiple nodes increases
Solution Approach 1:
The patent creates a universal collaborative PNT processing framework that can serve multiple sensing applications simultaneously. The same core processing architecture supports navigation, positioning, timing, and various sensing functions, allowing the system to maintain high adaptability while reducing overall system complexity through multi-functionality.
Solution Approach 2:
The patent segments the complex data processing task into modular components: individual node measurements, collaborative processing module, and application-specific output. This segmentation allows each component to be optimized independently and simplifies the overall system architecture while maintaining the ability to handle multiple sensing applications.
3Measurement precision
If collaborative PNT processing is implemented to improve accuracy, then PNT solution accuracy is enhanced, but the computational requirements and processing time increase
Solution Approach 1:
The patent performs preliminary actions by pre-establishing error covariance models and processing parameters for each node before actual PNT calculation. These pre-computed models are then used during collaborative processing to quickly refine PNT solutions without performing complex calculations from scratch, significantly reducing processing time while maintaining high accuracy.
Solution Approach 2:
The patent applies partial action by selectively incorporating collaborative information based on node characteristics and measurement quality. Rather than uniformly processing all nodes equally, the system adjusts the degree of collaboration based on individual node performance, using only the necessary computational resources required for each specific PNT solution refinement.
Data Source
AI summary
A method for providing collaborative PNT for a plurality of nodes in a distributed sensing system is disclosed. The method may include receiving carrier phase and pseudorange measurements from a first node and a second node of the plurality of nodes; providing a process model for each node, where the process model for each node is configured for modeling error characteristics associated with that node; determining an error covariance between the first node and the second node; and estimating a PNT solution for the first node and a PNT solution for the second node based on: the carrier phase and pseudorange measurements received from the first node, the carrier phase and pseudorange measurements received from the second node, the process model for the first node, the process model for the second node, and the error covariance between the first node and the second node.