Wireless Positioning Confidence Value Calculation
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Solution Overview
Problem
Current wireless positioning systems face challenges in determining the reliability of estimated parameters, such as angle-of-arrival (AoA) or angle-of-departure (AoD), especially under multipath signal propagation and non-line-of-sight conditions, which affects the accuracy of mobile device positioning.
Innovation Solution
A method is proposed that calculates a confidence value for estimated parameters by combining intermediate confidence values from multiple stages of signal processing, including pre-processing, pre-estimation, and final estimation, using algorithms like Propagator Direct Data Acquisition (PDDA) and post-processing, to enhance the reliability of position determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If AoA or AoD estimation is performed in multipath and non-LoS conditions, then position determination can be achieved in any case, but the reliability of the estimated position deteriorates
Solution Approach 1:
The confidence determination is segmented into multiple stages corresponding to different processing phases: first confidence value for pre-processed samples, second confidence value for pre-estimated parameter, and third confidence value for final estimated parameter. Each stage evaluates reliability independently, allowing the system to identify at which processing stage the signal quality degrades due to multipath effects.
Solution Approach 2:
The method implements feedback by using the multi-stage confidence values to adjust the final position determination. The confidence values feed back into the positioning algorithm to weight or discard estimates based on their reliability, thereby improving overall position accuracy in multipath conditions while maintaining the ability to operate in all environments.
2Device complexity
If basic confidence determination mechanisms are used for estimated parameters, then the implementation is simple, but the quality of position determination deteriorates
Solution Approach 1:
The confidence determination is divided into three distinct computational stages, each producing a confidence value for a specific processing output. This segmentation allows the system to maintain relatively simple individual confidence calculations while achieving high overall precision through the combination of multiple confidence assessments.
Solution Approach 2:
The method merges multiple confidence values from different processing stages into a comprehensive confidence assessment. By combining the first confidence value (pre-processed samples), second confidence value (pre-estimated parameter), and third confidence value (final estimated parameter), the system achieves high measurement precision without requiring each individual confidence calculation to be overly complex.
Data Source
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AI summary
In one embodiment a method for determining a confidence value (CV) to be used in determining a position of at least one mobile device for an estimated parameter in a wireless positioning system comprises the steps of receiving (S10) a signal comprising a number of signal samples, pre-processing (S11) each sample of the number of signal samples and therefrom providing a number of pre-processed samples, calculating (S12) a first confidence value (CV1), performing (S13) a pre-estimation of a parameter and providing a pre-estimated parameter, calculating (S14) a second confidence value (CV2) for the pre-estimated parameter, performing (S15) a final estimation of the parameter and providing the estimated parameter, calculating (S16) a third confidence value (CV3) for the estimated parameter, combining (S17) at least two of the first, second and third confidence value and providing (S18) the confidence value for the estimated parameter.