Satellite Integrity Checking via Kalman Filter Segmentation
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Solution Overview
Problem
Current navigation systems face challenges in efficiently detecting and excluding multiple simultaneous satellite failures, particularly with the increasing number of satellites, which requires a large number of Kalman filters, leading to high computational costs and complexity.
Innovation Solution
A method that uses a predetermined number of Kalman filters to define secondary sets of measurements, ensuring each measurement is included in at least one secondary set, and each p-tuple of measurements is excluded from at least one secondary set, allowing for the detection of up to p faulty measurements with reduced computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a bank of Kalman filters is used to detect and exclude satellite failures, then the reliability of navigation measurements is improved, but the device complexity increases significantly when multiple simultaneous failures must be detected
Solution Approach 1:
The patent segments the set of all possible satellite failure combinations into p-tuples (groups of p satellites). Instead of creating a filter for every possible failure scenario, the method divides the problem into manageable segments by focusing on excluding specific p-tuples of measurements from secondary sets. This segmentation allows detection of up to p simultaneous failures without requiring an exponentially large number of filters.
Solution Approach 2:
The patent applies partial action by not requiring every possible failure combination to be explicitly handled. Instead of creating a dedicated filter for each possible satellite failure scenario (which would be excessive), the method uses a predetermined number of filters that partially cover the failure space by excluding p-tuples, achieving sufficient detection capability with reduced complexity.
2Measurement precision
If the number of satellites in the navigation system is increased, then the availability and precision of navigation solutions is improved, but the number of required Kalman filters for integrity checking increases combinatorially
Solution Approach 1:
The patent makes the predetermined number of Kalman filters universal by designing them to handle multiple failure scenarios simultaneously. Each filter is configured to exclude specific p-tuples of measurements, allowing a single filter to detect multiple different failure combinations. This multi-functionality enables the system to maintain high measurement precision from multiple satellites while avoiding combinatorial growth in filter numbers.
Solution Approach 2:
The patent changes the parameter of filter configuration from dedicated one-to-one mapping with failure scenarios to a many-to-one relationship where multiple failure scenarios are handled by the same filter through selective exclusion of p-tuples. This parameter change in how filters are structured and assigned enables scaling to more satellites without proportional increase in filter count.
3Reliability
If a large number of Kalman filters are implemented to detect multiple simultaneous satellite failures, then the integrity control capability is improved, but the productivity and computational efficiency deteriorates
Solution Approach 1:
The patent segments the computational task across a predetermined number of filters, where each filter handles specific p-tuple exclusions. This segmentation distributes the computational load efficiently, allowing the system to maintain high integrity detection capability while avoiding the computational burden of implementing a filter for every possible failure scenario.
Data Source
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AI summary
The invention relates to a method for verifying the integrity of a primary set of measurements obtained from navigation signals emitted by satellites and supplied to an integrity control device comprising a plurality of Kalman filters. The method comprises the steps of defining, for each Kalman filter, a secondary set of measurements contained within the primary set, and calculating, by each Kalman filter, a navigation solution from its respective secondary set of measurements. The method is characterized in that the definition of the secondary sets complies with the following principles: each measurement contained in the primary set is present in at least one of the secondary sets; for each p-tuple of measurements in the primary set, where p is a predetermined integer greater than 1, at least one of the secondary sets does not contain said p-tuple of measurements; and for each secondary set,at least one of the p-tuples is excluded from said secondary set, and in that it further includes the steps of: detecting, for each navigation solution, at most p faulty measures not present in the secondary set from which the navigation solution is developed, and reporting at most p faulty satellites in the primary set from the respective results of the detections.