NLoS Vehicle Positioning via Multi-Path Signal Analysis
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Solution Overview
Problem
Existing autonomous vehicle sensing technologies, such as Radar, LiDAR, and GPS, face limitations in accurately detecting hidden or non-line-of-sight vehicles, particularly under poor weather conditions, leading to reduced accuracy and reliability in autonomous driving scenarios.
Innovation Solution
A method utilizing multi-path wireless signals to estimate the position, direction, and trajectory of hidden vehicles by receiving and measuring signals from multiple paths, employing multiple antennas and time of arrival, angle of arrival, and angle of departure measurements, to determine the position and geometry of vehicles without direct line-of-sight communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing autonomous vehicle sensing technologies (Radar, LiDAR, GPS) are used, then positioning can be achieved, but accuracy deteriorates under poor weather conditions and for hidden vehicles
Solution Approach 1:
The patent uses wireless communication signals as an intermediary to enable positioning of hidden vehicles. Instead of relying on direct line-of-sight sensing technologies like Radar and LiDAR, the system utilizes existing wireless signals that can penetrate obstacles and travel along multi-path routes, allowing the receiving vehicle to determine the position of transmitting vehicles even when they are not directly visible or when weather conditions are poor.
Solution Approach 2:
The patent transitions from traditional spatial sensing dimensions to utilizing signal propagation dimensions. By measuring time of arrival, angle of arrival, and angle of departure of wireless signals, the system extracts positioning information from temporal and angular dimensions, enabling accurate localization of hidden vehicles that cannot be detected by conventional spatial sensing methods.
2Measurement precision
If multi-path wireless signals are used for positioning, then positioning accuracy for hidden vehicles improves, but system complexity increases
Solution Approach 1:
The patent leverages the multi-functionality of wireless communication signals, which simultaneously serve both communication and positioning purposes. The same wireless signals used for data transmission also provide timing and angular information for positioning, eliminating the need for separate dedicated positioning hardware and reducing overall system complexity while maintaining high positioning accuracy.
Solution Approach 2:
The system uses the transmitting vehicle's own wireless communication signals for positioning purposes. The transmitting vehicle generates signals that inherently contain timing and spatial information, which the receiving vehicle processes to determine position. This self-service approach eliminates the need for external positioning infrastructure or additional active sensors on the transmitting vehicle.
3Reliability
If direct line-of-sight communication is required, then signal quality is maintained, but positioning of hidden vehicles becomes impossible
Solution Approach 1:
The patent converts the harmful effect of obstacles blocking direct line-of-sight into a beneficial multi-path propagation scenario. Instead of treating signal reflections and indirect paths as interference to be eliminated, the system utilizes these multi-path signals as the primary means for detecting and positioning hidden vehicles, transforming the limitation into a capability.
Solution Approach 2:
The patent inverts the traditional approach by not requiring direct line-of-sight communication. Instead of seeking to establish a direct signal path, the system deliberately utilizes indirect multi-path routes to detect and position vehicles that are hidden from direct view, completely reversing the conventional line-of-sight requirement paradigm.
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 enables fast and accurate positioning of hidden vehicles, enhancing the reliability and efficiency of autonomous driving systems and overcoming the limitations of existing technologies, particularly in challenging weather conditions.
Implementation Method 1
a method utilizing multi-path wireless signals to estimate the position, direction, and trajectory of hidden vehicles by receiving and measuring signals from multiple paths
Implementation Method 2
employing multiple antennas and time of arrival, angle of arrival, and angle of departure measurements, to determine the position and geometry of vehicles
Implementation Method 3
employing multiple antennas and time of arrival, angle of arrival, and angle of departure measurements, to determine the position and geometry of vehicles
Implementation Method 4
employing multiple antennas and time of arrival, angle of arrival, and angle of departure measurements, to determine the position and geometry of vehicles
Data Source
AI summary
One embodiment is a method including: receiving signals of at least 4 paths from the Tx UE; measuring a ToA, an AoA, an AoD of each of the signals of 4 paths, determining each distance between the Rx UE and each scatter of each 4 paths, each distance between the Rx UE and the Tx UE and a driving direction of the Tx UE, based on the ToA, AoA and AoD; determining a position of the Tx UE based on results of measurement and results of the determination, wherein an assumption that each of x-axis distance and y-axis distance between the Tx UE and Rx UE based on the AoA, AoD and the driving direction of the Tx UE are identical in signal path 1 and signal path p (p=2, 3, 4) is used for determination of the position.