Vehicular Positioning Using 3GPP Multipath Virtual Transmitters
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Solution Overview
Problem
Current positioning systems, such as GNSS, face challenges in urban areas and tunnels due to multipath propagation, resulting in insufficient accuracy for many applications, especially in intelligent transportation systems, where positioning errors of around 18 meters are unacceptable.
Innovation Solution
A computer-implemented positioning method that utilizes multipath components by processing RF signals from base stations within the 3GPP infrastructure to calculate the vehicle's position, assuming a linear path between the RF module and the origin of each multipath component, and employing a SLAM algorithm to estimate the positions of both physical and virtual transmitters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multipath components are exploited for positioning, then positioning accuracy is improved, but positioning error remains too high (18m RMSE) for practical ITS applications
Solution Approach 1:
The patent converts the harmful multipath propagation effect into a beneficial positioning resource by treating reflected signals as if they originated from virtual transmitters. Instead of discarding multipath components as noise, the system models them as additional signal sources and uses their geometric relationships to calculate vehicle position, thereby transforming a previously harmful interference into a useful positioning aid.
Solution Approach 2:
The patent introduces virtual transmitters as intermediary entities that mediate between the physical transmitter and the receiver. These virtual transmitters represent the apparent source locations of multipath signals, allowing the system to process reflected signals through standard LOS positioning algorithms while accounting for the complex propagation paths indirectly.
2Loss of information
If SLAM algorithm is used to estimate positions of virtual and physical transmitters, then positioning information is obtained, but computational complexity increases
Solution Approach 1:
The patent segments the positioning problem into two distinct parts: (1) estimating the positions of virtual transmitters using SLAM algorithms, and (2) calculating the vehicle position using standard LOS positioning with the estimated virtual transmitter locations. This segmentation allows the complex SLAM computation to be performed only for the static virtual transmitter positions, while vehicle position calculation remains computationally efficient.
Solution Approach 2:
The patent performs preliminary estimation of virtual transmitter positions using SLAM algorithms before using these estimates for actual vehicle positioning. By pre-computing the virtual transmitter locations and treating them as known entities in subsequent positioning calculations, the system reduces the computational burden during real-time vehicle position updates.
3Ease of manufacture
If existing 3GPP infrastructure is leveraged for positioning, then cost is reduced, but positioning accuracy in urban canyons and tunnels is insufficient
Solution Approach 1:
The patent specifically addresses urban canyon and tunnel environments by converting the harmful multipath effects predominant in these areas into beneficial positioning information. In urban canyons where signals reflect off buildings and in tunnels where signals bounce off walls, the system models these reflected paths as virtual transmitters, allowing accurate positioning despite the challenging propagation conditions that would normally degrade GNSS and cellular positioning.
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 significantly improves positioning accuracy and reduces costs by leveraging existing 3GPP infrastructure, providing a reliable and precise vehicle positioning system even in challenging environments.
Implementation Method 1
multipath propagation and blocking of signals
Implementation Method 2
receive a reference signal from at least one base station
Data Source
AI summary
A method for vehicular self-positioning is executed by a positioning device in a vehicle. The positioning device computes a current estimated position of the vehicle as a function of local motion data obtained from a motion sensor in the vehicle, and operates an RF module in the vehicle to receive a reference signal from one or more base stations in an environment of the vehicle, the respective base station being configured for telecommunication and being part of a 3GPP infrastructure. The positioning device further processes the reference signal to determine measured values of at least one path parameter for a selected set of multipath components, and operates a positioning algorithm, e.g. SLAM, on at least the current estimated position and the measured values to calculate a current output position of the vehicle and position information for an origin of each of the multipath components.