Mobile Carrier Positioning Using CIR Multipath Association
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Solution Overview
Problem
Existing UWB localization systems face challenges in accurately determining the position of a mobile carrier due to significant background noise and geometric dilution of accuracy, especially when using omnidirectional antennas and moving targets, which complicates the processing of channel impulse responses (CIR) and reduces positional accuracy.
Innovation Solution
A method that involves predicting the position of a mobile carrier, acquiring channel impulse responses, determining multipath components, associating predicted distances with these components, and updating the position based on these associations, using techniques like extended Kalman filters or particle filtering to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If omnidirectional antennas are used for UWB localization, then the ability to receive echoes from all directions is improved, but background noise increases significantly
Solution Approach 1:
The system performs preliminary identification of multipath components in the channel impulse response before using them for localization. By pre-processing the CIR to identify and separate multipath components from direct paths and noise, the system prepares clean distance measurements in advance, reducing the impact of background noise that omnidirectional antennas inevitably capture.
Solution Approach 2:
The invention converts the harmful multipath effects and background noise into useful information by identifying and utilizing multipath components for distance measurement. Instead of treating multipath reflections as mere noise to be filtered out, the system actively detects and uses these reflected signals to improve localization accuracy, especially in indoor environments where multipath is prevalent.
2Adaptability or versatility
If CIR measurements are processed for moving targets, then radar functionality is achieved, but processing complexity increases due to target motion
Solution Approach 1:
The system performs preliminary identification of multipath components in the channel impulse response before using them for localization. By pre-processing the CIR to identify and separate multipath components from direct paths and noise, the system prepares clean distance measurements in advance, reducing the impact of background noise that omnidirectional antennas inevitably capture.
Solution Approach 2:
The invention converts the harmful multipath effects and background noise into useful information by identifying and utilizing multipath components for distance measurement. Instead of treating multipath reflections as mere noise to be filtered out, the system actively detects and uses these reflected signals to improve localization accuracy, especially in indoor environments where multipath is prevalent.
3Ease of manufacture
If anchors are deployed at ground level for drone localization, then installation simplicity is improved, but geometric dilution of accuracy increases
Solution Approach 1:
The invention introduces multipath components as intermediaries between the ground-level anchors and the drone. By using reflected signals from walls, ceilings, and other surfaces as intermediate propagation paths, the system effectively extends the geometric coverage of ground-level anchors, allowing accurate 3D positioning even when anchors are confined to the ground plane.
Solution Approach 2:
The system transitions from 2D anchor deployment to 3D signal propagation by utilizing multipath reflections. Although anchors are physically deployed only at ground level (2D), the multipath components introduce virtual anchor positions in three-dimensional space through reflections off walls, ceilings, and other surfaces, thereby achieving 3D positioning accuracy without elevating physical anchors.
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
Improves the accuracy of mobile carrier positioning by effectively processing CIR measurements with moving antennas, reducing noise interference and geometric errors, and enabling precise distance measurements between the carrier and obstacles, even in complex environments.
Implementation Method 1
The use of a very wide spectrum gives this technology the ability to very accurately measure the time of arrival of the radio signal (or TOA for Time of Arrival), or the time differences of arrival (TDOA for 'Time Difference of Arrival'), which subsequently allows the calculation of a flight time and therefore a very precise distance.
Implementation Method 2
determination of a set of multipath components from the channel impulse response; association of at least one predicted distance with at least one corresponding multipath component
Data Source
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AI summary
The invention relates to a method for improving the accuracy of the position of a mobile carrier, comprising the steps of: S1) predicting a position of the mobile carrier (1), and determining a set of predicted distances (dk,Jrad^j=1:Nobs) between the mobile carrier (1) and a set of obstacles (2, 3, Oj) in the environment of the mobile carrier (1); S2) acquiring a channel impulse response (CIR) between a first node (T1) and a second node (T0), at least one of the two nodes (T1, T0) being carried on the mobile carrier (1); S3) determining a set of multipath components (dk,iradi=1:NMPC) from the channel impulse response (CIR); S4) association of at least one predicted distance (dk,Jrad^j=1:Nobs) to at least one corresponding multipath component (dk,iradi=1:NMPC) so as to obtain a set of updated distances (dk,irad,Oj) between the moving carrier (1) and the set of obstacles (2, 3, Oj).