GNSS Positioning Without Integer Ambiguity Resolution
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Solution Overview
Problem
Existing GNSS positioning systems face complexity and inefficiency due to the need to resolve integer ambiguities in carrier-phase measurements, which can lead to loss-of-lock and increased computational complexity, especially in urban environments and long distances, making it difficult to achieve high-resolution positioning.
Innovation Solution
A method and system that resolves ambiguities by treating them as float values, using a weighted combination of integers, and employing probabilistic state estimators like Kalman filters, selecting a subset of measurements based on informational value to reduce computational complexity and improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If integer ambiguity resolution is performed in traditional GNSS positioning, then positioning accuracy is improved, but computational complexity and processing time increase significantly
Solution Approach 1:
The patent extracts and removes the integer ambiguity resolution step from the traditional two-step GNSS positioning process. By formulating a direct continuous optimization approach that bypasses integer resolution, the method eliminates the computationally intensive ambiguity resolution phase while maintaining positioning accuracy through direct minimization of the cost function involving carrier phase and pseudorange measurements.
Solution Approach 2:
Instead of following the conventional approach of first resolving integer ambiguities and then determining position, the patent inverts the sequence by directly estimating position and ambiguities simultaneously through continuous optimization. This inversion allows the use of standard nonlinear optimization algorithms without requiring discrete integer search procedures.
2Measurement precision
If integer ambiguity resolution is performed, then high-resolution positioning is achieved, but loss-of-lock occurs more frequently in urban environments and long distances
Solution Approach 1:
The patent applies dynamic estimation techniques where the ambiguity parameters are treated as continuous floating-point values that can adapt continuously to changing signal conditions. This dynamic approach allows the estimator to track ambiguities smoothly through signal interruptions and multipath environments, reducing loss-of-lock events compared to static integer resolution methods.
Solution Approach 2:
The method changes the parameter representation of carrier phase ambiguities from discrete integers to continuous floating-point values. This parameter transformation enables the use of gradient-based optimization methods that are more robust to signal quality variations, atmospheric changes, and receiver motion, thereby reducing loss-of-lock frequency in challenging environments.
3Measurement precision
If all carrier phase measurements are used for positioning, then measurement precision improves, but computational load increases due to processing all measurements
Solution Approach 1:
The patent implements a selective measurement utilization strategy where only a subset of carrier phase measurements that provide the most useful information are used in the optimization process. By identifying and using only the necessary measurements rather than processing all available measurements, the method reduces computational load while maintaining positioning accuracy through the contribution of the most informative measurement subset.
Data Source
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AI summary
A system for tracking a state of a GNSS receiver uses a subset of the measurements of satellite signals selected to avoid the need for intermediate integers ambiguity estimate. The system selects the subset of measurements for the state tracking such that each measurement in the selected subset of measurements is formed by a weighted combination of multiple different measurements from the set of measurements. The system uses a probabilistic state estimator that tracks the state of the GNSS receiver using a probabilistic motion model subject to noise and a probabilistic measurement model relating the selected subset of the measurements of satellite signals to the current state of the receiver.