NIORAIM Non-Uniform Weighting for Integrity Limits
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Solution Overview
Problem
The existing Receiver Autonomous Integrity Monitoring (RAIM) Fault Detection and Exclusion (FDE) system often lacks availability, as its integrity level cannot be smaller than the required alert limit for certain flight operations, limiting its effectiveness in detecting and excluding measurement faults.
Innovation Solution
The Novel Integrity Optimized RAIM (NIORAIM) method determines non-uniform weights through a least squares approximation of a linearized measurement equation and applies them in the RAIM system to reduce the horizontal integrity limit, improving system availability by balancing position accuracy with integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional RAIM FDE algorithms are used, then the system can detect and exclude single measurement faults, but the integrity level cannot be smaller than the required alert limit for certain flight operations, resulting in limited system availability
Solution Approach 1:
The patent changes the weighting parameters from uniform to non-uniform weights derived from least squares approximation. This parameter change optimizes the balance between position accuracy and integrity level, enabling the system to achieve smaller integrity limits (improved reliability) while maintaining acceptable position accuracy for certain flight operations.
Solution Approach 2:
The patent applies different weights to different satellite measurements based on their individual quality characteristics. By assigning non-uniform weights according to the least squares approximation of the linearized measurement equation, the system optimizes the contribution of each measurement to the overall solution, improving integrity level while maintaining position accuracy.
2Reliability
If non-uniform weights are applied through least squares approximation, then the horizontal integrity limit is reduced and system availability is improved, but there is some loss in solution accuracy
Solution Approach 1:
The patent deliberately changes the weighting parameters to non-uniform values that optimize integrity level. The least squares approximation provides a systematic method to determine these weights, accepting some loss in position accuracy as a trade-off to achieve significantly improved integrity levels and system availability.
Solution Approach 2:
The patent optimizes the weighting parameters by deriving non-uniform weights from the least squares approximation of the linearized measurement equation. This parameter optimization achieves the best possible balance between position accuracy and integrity level, reducing the horizontal integrity limit while maintaining acceptable position accuracy for certain flight operations.
Data Source
AI summary
An integrity monitoring method for an aircraft is disclosed. The integrity monitoring method includes determining a set of non-uniform weights. The non-uniform weights are based on a least squares approximation of a linearized measurement equation. The integrity monitoring method also includes applying the non-uniform weights in a receiver autonomous integrity monitoring (RAIM) system. Further, the integrity monitoring method includes determining a reduced integrity limit based on the output of the RAIM system.