Satellite Receiver Position Estimation via Weighted Pseudorange Matrix
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Solution Overview
Problem
Current satellite navigation systems face challenges in accurately estimating receiver position due to errors and noise in pseudorange measurements, requiring computationally intensive methods and external corrections, which are not efficient in multipath environments.
Innovation Solution
A method to compute a weight matrix based on signal degradations from multipath interference, using statistical processing and distribution fitting to assign weights to pseudoranges, enhancing receiver position estimation accuracy by differentiating signal reliability from various satellites.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional position estimation methods are used, then the system can compute receiver position, but the accuracy is degraded by errors and noise in pseudorange measurements
Solution Approach 1:
The patent applies local quality by assigning different weights to different pseudorange measurements based on their individual reliability. The weight matrix W contains diagonal elements that reflect the local quality (reliability) of each satellite signal, allowing the least squares solution to give more importance to high-quality measurements and less to degraded ones. This resolves the contradiction by maintaining position computation capability while improving accuracy through selective weighting of reliable signals.
Solution Approach 2:
The patent changes the parameter of signal reliability assessment by introducing a degradation indicator based on multipath error models. Instead of treating all pseudoranges equally, the system computes a weight for each measurement that reflects its degradation level. This parameter change enables the system to adapt to multipath environments by dynamically adjusting the influence of each measurement on the final position estimate.
2Measurement precision
If computationally intensive methods are used to correct pseudorange errors, then position accuracy may improve, but computational complexity and processing time increase
Solution Approach 1:
The patent applies preliminary action by pre-computing or quickly determining the weight matrix W based on satellite geometry and signal quality indicators. Rather than performing complex iterative corrections during position estimation, the system prepares the weighting factors in advance or computes them efficiently using closed-form expressions. This reduces the computational burden during the actual position solution while maintaining accuracy improvements.
Solution Approach 2:
The patent uses a simplified model or approximation (copy) of the complex error correction process. Instead of implementing full-fledged differential GPS or complex multipath mitigation algorithms, the system creates a weighted least squares formulation that copies the essential benefit of error correction through weighting, while avoiding the computational intensity of more sophisticated methods. This provides a computationally efficient alternative that achieves similar accuracy improvements.
3Productivity
If all pseudorange measurements are treated equally, then the computation is simpler, but the position estimation accuracy is reduced due to noisy measurements
Solution Approach 1:
The patent implements local quality by assigning distinct weights to different pseudorange measurements based on their individual quality characteristics. The weight matrix W reflects the local quality of each measurement, with higher weights given to more reliable signals and lower weights to noisy or degraded measurements. This approach maintains computational efficiency through a closed-form solution while improving accuracy by differentiating between high and low quality measurements.
Solution Approach 2:
The system applies self-service by automatically determining the weight matrix W based on the observed signal characteristics and satellite geometry. The receiver autonomously assesses the quality of each pseudorange measurement and adjusts the weighting accordingly, without requiring external assistance or complex manual configuration. This self-adjusting mechanism improves accuracy while maintaining computational simplicity.
Data Source
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AI summary
A method of estimating a position of a satellite receiver (2), comprising computing a weight matrix, and computing an estimated position of the satellite receiver based on the weight matrix, wherein computing the weight matrix includes computing quantities indicative of degradations experienced by satellite signals and of multipath interference, and computing the weight matrix based on the computed quantities.