Navigation Protection Radius Estimation for Bounded GNSS Errors
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Solution Overview
Problem
Existing methods for determining protection radii associated with navigation parameters, such as position, speed, and heading, fail to optimally account for bounded errors whose distribution model is unknown, leading to suboptimal error estimation and increased risk of navigation parameter errors exceeding predefined bounds.
Innovation Solution
A method that calculates a protection radius by determining transfer matrices and summing unit contributions from known error bounds, using a Kalman filter to integrate GNSS and inertial measurements, effectively bounding errors and minimizing the risk of navigation parameter errors exceeding the protection radius without significant computational load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing methods are used to determine protection radii, then the determination process is simple, but the error estimation is suboptimal and the risk of navigation parameter errors exceeding bounds increases
Solution Approach 1:
The protection radius determination is segmented into multiple unit contributions, each corresponding to a specific time instant and error source. This allows the complex error estimation to be broken down into manageable components that can be computed and summed systematically, improving accuracy without overwhelming computational complexity.
Solution Approach 2:
The method pre-computes transfer matrices and error propagation characteristics at each time instant before final protection radius determination. By preparing these components in advance and storing them, the system enables rapid and accurate protection radius calculation when needed, without requiring complex real-time computations.
2Measurement precision
If complex error modeling is applied to account for bounded errors, then error bounding accuracy improves, but computational load increases significantly
Solution Approach 1:
The method extracts and processes only the essential error bound information from complex error models, separating the critical protection radius determination from unnecessary computational details. This extraction approach maintains error bounding accuracy while significantly reducing the computational load by focusing only on the most relevant error characteristics.
Solution Approach 2:
The method transforms complex error distribution models into simplified parameter representations (error bounds at specific instants). By changing the representation from complex continuous distributions to discrete bounded parameters, the system achieves accurate error bounding with much lower computational requirements.
3Measurement precision
If real-time protection radius determination is performed, then navigation accuracy is maintained, but processing time increases
Solution Approach 1:
Transfer matrices and error propagation characteristics are pre-computed and stored at each time instant before final protection radius determination. This preliminary preparation enables rapid real-time calculation of protection radii without compromising navigation accuracy, as the computationally intensive parts are already completed in advance.
Solution Approach 2:
The method dynamically updates protection radii by combining pre-computed transfer matrices with current measurement information. This dynamic approach maintains real-time navigation accuracy while minimizing processing time by leveraging previously computed components and only calculating what is necessary for the current state.
Data Source
AI summary
A method for determining at least one protection radius associated with at least one navigation parameter of a wearer. The method includes receiving a measurement from a sensor, an error bound, and an inertial measurement. The method further includes, for each successive reception instant, determining an estimated state vector on the basis of the measurement from the sensor and the inertial measurement. The method further includes computing an estimate error propagation matrix and a bounded error influence matrix, and computing transfer matrices on the basis of the calculated matrices. The method further includes determining navigation parameters from the estimated state vector and the associated protection radius on the basis of the calculated transfer matrices.