Wireless Positioning via Cross-Correlation and CIR Analysis
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Solution Overview
Problem
Existing positioning methods in wireless telecommunications, such as OTDOA and UTDOA, face challenges in accurately determining the time-of-arrival (TOA) measurements due to multipath propagation, leading to errors in positioning calculations, especially in non-line-of-sight (NLOS) conditions where additional path information is not reliably reported.
Innovation Solution
A method that involves determining the cross-correlation between received and transmitted signals to identify and classify reflecting clusters/objects based on their temporal behavior, allowing for the reporting of additional path information to improve TOA estimation and reduce data reporting resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If TOA measurements are performed in multipath propagation conditions, then positioning can be achieved, but measurement accuracy deteriorates due to multipath components causing early false detection or late detection
Solution Approach 1:
The patent introduces an intermediary processing stage between signal reception and TOA measurement. A correlation function is computed between the received signal and a reference signal, and this correlation function serves as an intermediary representation that helps identify the direct path component more reliably in multipath conditions. The correlation peak detection in the intermediary domain provides more robust TOA estimation than direct signal analysis.
Solution Approach 2:
The patent transforms the TOA measurement problem from the time-domain signal analysis to the correlation-domain analysis. By computing the correlation function between received and reference signals, the measurement is performed in an additional dimension (correlation magnitude and phase), which provides more information for distinguishing the direct path from multipath components.
2Measurement precision
If additional path information is reported to correct TOA errors, then positioning accuracy improves, but data reporting resources increase
Solution Approach 1:
The patent extracts only the essential correction information from the full correlation function. Instead of reporting the entire correlation function or all multipath components, the method identifies and reports only the parameters of significant multipath components (relative time difference, relative power, and phase) that need correction. This selective extraction reduces data volume while maintaining positioning accuracy.
Solution Approach 2:
The patent changes the reporting parameters from raw signal data to processed correlation parameters. Instead of reporting full correlation functions or raw TOA measurements, the system reports derived parameters including relative time difference, relative power, and phase information of multipath components. This parameter transformation reduces data volume and focuses on the most relevant correction information.
3Reliability
If correlation function analysis is performed to identify multipath components, then TOA error correction capability improves, but computational complexity increases
Solution Approach 1:
The patent applies partial action by focusing computational resources on identifying only the most significant multipath components rather than analyzing all possible paths. The method identifies multipath components that exceed certain thresholds in terms of power or time difference, and processes only these significant components for correction. This selective processing reduces computational complexity while maintaining error correction capability for the dominant error sources.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the accuracy of position calculations by providing additional Channel Impulse Response (CIR) information beyond TOA, reducing data usage and improving positioning in challenging environments, while minimizing resource consumption.
Implementation Method 1
determining a cross-correlation between a received signal and a transmitted reference signal
Implementation Method 2
determining a Channel Impulse Response (CIR) of the cross-correlation related to a first lobe detected above a selected threshold in the CIR
Data Source
AI summary
The present disclosure relates to methods and apparatuses for improving positioning of a device in a wireless communications network. An example method, performed by a measuring device configured to communicate with a positioning device, includes determining a cross-correlation between a received signal and a transmitted reference signal; determining a channel impulse response (CIR) of the cross-correlation related to a first lobe detected above a selected threshold in the CIR; analyzing a temporal behavior of reflecting clusters/objects based on determined CIR instances of a time-of-arrival (TOA); classifying the reflecting clusters/objects based at least on their temporal behavior; and reporting at least one classified reflecting cluster/object to the positioning device.