Node Positioning Using Aged Reference Data
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Solution Overview
Problem
In communication networks, determining the position of a node is challenging when current position measurement information is unavailable from one or more reference nodes, due to issues like interference, packet loss, or asynchronous data collection, leading to inaccurate or failed position calculations.
Innovation Solution
The method involves receiving position data from reference nodes, storing it with timestamps, and generating 'aged' data when updates are missing, adjusting precision indicators based on age, and using this aged data in conjunction with updated information to compute the node's position, accounting for mobility if necessary, to maintain accurate positioning even in hostile environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current position measurement information is required from all reference nodes, then position calculation accuracy is improved, but system reliability deteriorates when data is unavailable due to interference or packet loss
Solution Approach 1:
The system performs preliminary actions by collecting and storing position measurement information from reference nodes in advance, maintaining a history of position data with timestamps. When current data is unavailable, the system can utilize previously collected aged position data to compute the node's position, thereby maintaining system reliability without sacrificing accuracy
Solution Approach 2:
The system dynamically adjusts parameters by evaluating the age of position data and selectively applying aging factors to precision indicators based on timestamp differences. This parameter adjustment allows the system to adaptively weight historical data against current data, maintaining accurate position calculations even when current reference node data is unavailable
2Adaptability or versatility
If position data from multiple reference nodes is collected asynchronously, then data collection flexibility is improved, but measurement precision deteriorates due to timing differences
Solution Approach 1:
The system implements dynamic handling of asynchronous data by continuously monitoring timestamps and calculating age differences for each reference node's position data. The precision indicator is dynamically adjusted based on how aged each data point is relative to the most recent data, allowing the system to maintain measurement precision while accepting asynchronous data collection from multiple reference nodes
3Productivity
If aged position data is used when current data is unavailable, then system productivity is improved by maintaining continuous positioning, but measurement precision deteriorates due to data staleness
Solution Approach 1:
The system prepares for potential data unavailability by maintaining a cushion of historical position data with associated timestamps. When current data becomes unavailable, pre-computed aged position data serves as a buffer, allowing continuous positioning to be maintained. The precision indicator is adjusted beforehand based on the age of the data, providing a controlled degradation of accuracy rather than complete positioning failure
Data Source
AI summary
Techniques are provided for determining a position of a node. For example, the node receives first position data from a first reference node and second position data from a second reference node. The second position data includes second position measurement information and a precision indicator which indicates accuracy of the second position measurement information. The node generates a timestamp which indicates when the second position data was received by node, and storing the second position data and associated timestamp. Upon receiving updated first position data at the node from the first reference node, the node determines whether updated second position data has been received from the second reference node, and if not, generates aged second position data based on the stored second position data and the associated timestamp. The node can then determine its position based on the aged second position data and the updated first position data.