Recursive Satellite Subset Selection for Navigation Accuracy
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Solution Overview
Problem
Satellite navigation system receivers are limited by their processing capabilities, which restrict them to calculating a location based on a maximum number of visible satellites, often resulting in sub-optimal geometry and increased computational demands when selecting a subset of satellites for navigation solutions.
Innovation Solution
A method for recursively evaluating subsets of satellites based on predefined criteria to select the optimal subset for navigation solution calculation, reducing the number of satellites processed and minimizing computational demands while ensuring desired accuracy and integrity thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the receiver processes all visible satellites to improve navigation accuracy, then the precision of location calculation increases, but the computational load and processing requirements exceed the receiver's capabilities
Solution Approach 1:
The patent extracts and removes satellites from the visible set that do not contribute to improving navigation accuracy. By evaluating each satellite's contribution to geometric dilution of precision (GDOP) and removing those with negative or zero contribution, the system reduces the satellite subset to only those that provide meaningful accuracy improvement, thereby reducing computational load while maintaining precision.
Solution Approach 2:
The patent changes the parameter of satellite selection from a fixed maximum number to a dynamic subset determined by accuracy contribution thresholds. By introducing criteria such as minimum accuracy improvement threshold and maximum satellite subset size, the system adapts the processing load to match receiver capabilities while ensuring navigation accuracy requirements are met.
2Productivity
If the receiver selects a subset of satellites to reduce computational load, then the processing requirements decrease, but the geometry of satellite configuration may become sub-optimal
Solution Approach 1:
The patent implements feedback by evaluating the geometric contribution of each satellite to the navigation solution accuracy before selection. The system calculates how each satellite affects dilution of precision metrics and uses this feedback to make informed selection decisions, ensuring that the reduced subset maintains optimal or near-optimal geometry for accurate navigation solutions.
Solution Approach 2:
The patent performs preliminary evaluation of all visible satellites to identify and rank them by their contribution to navigation accuracy before the actual selection process. By pre-calculating accuracy contribution metrics and sorting satellites accordingly, the system ensures that the most geometrically beneficial satellites are selected first, maintaining optimal configuration in the reduced subset.
3Measurement precision
If the receiver evaluates all possible satellite groupings to find the optimal subset, then the navigation accuracy is maximized, but the computational time and complexity increase significantly
Solution Approach 1:
The patent extracts and eliminates satellite combinations that cannot possibly improve navigation accuracy. By identifying and removing satellites that contribute negatively or neutrally to geometric precision, the system reduces the combinatorial search space from all possible subsets to only those containing potentially beneficial satellites, dramatically reducing computation time while preserving accuracy optimization.
Solution Approach 2:
The patent changes the evaluation parameter from exhaustive enumeration of all subsets to a threshold-based filtering approach. By introducing parameters such as minimum accuracy contribution threshold and maximum subset size, the system transforms the problem from evaluating 2^N possible combinations to evaluating only those subsets that meet the threshold criteria, reducing computational complexity from exponential to linear or polynomial time.
Data Source
AI summary
In one embodiment, a method for selecting a sub-set of satellites from a set of N satellites is provided. The method includes recursively evaluating each sub-set of N−P satellites of a set of N satellites. If only one sub-set satisfies one or more first criterion, then the one sub-set that satisfies the one or more first criterions is selected. If, however, more than one sub-set satisfies the one or more first criterion, then the sub-sets that satisfy the one or more first criterion are evaluated with respect to one or more second criterion and the one sub-set that optimizes the one or more second criterion is selected. Once the selected set of N satellites is equal to the number of satellites from which a receiver is configured to calculate a navigation solution, then that selected set of N satellites is used to calculate a navigation solution.