Probabilistic Ray-Tracing Positioning
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Solution Overview
Problem
Existing positioning methods relying on line-of-sight measurements are inadequate when signals are non-line-of-sight, and they do not fully utilize statistical properties of angle of arrival measurements, leading to suboptimal performance and resource-intensive ray launching processes.
Innovation Solution
A method that determines the position of a user equipment by obtaining a vector of angles of reception, computing N probability distributions from ray launching in a 3D environment, and calculating the probability of the user equipment's position based on these distributions, using a Gaussian mixture model to fit parametric distributions and reduce the number of rays needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional ray-tracing methods are used to determine position, then positioning can be performed in non-line-of-sight conditions, but the number of rays required is very large, leading to high resource consumption
Solution Approach 1:
The patent pre-computes and stores probability distribution functions during an offline phase, capturing the statistical characteristics of ray paths in the environment. During online positioning, instead of launching numerous rays, the system only needs to evaluate these pre-computed probability distributions at the measured AoA, dramatically reducing computational resources while maintaining positioning capability in NLOS conditions
Solution Approach 2:
The patent transforms the ray-tracing problem from deterministic geometric intersection to a probabilistic framework. By changing from tracking individual ray paths to evaluating probability distribution functions that capture the statistical behavior of multiple rays, the system achieves positioning with far fewer computational operations
2Use of energy by moving object
If the number of launched rays is reduced to save resources, then resource consumption decreases, but positioning accuracy deteriorates
Solution Approach 1:
The patent changes the fundamental parameter from individual ray trajectories to probability distribution functions that encapsulate the statistical behavior of ray paths. This transformation allows accurate positioning predictions with minimal computational effort, as the probability distributions capture the essential geometric and statistical characteristics of the environment
Solution Approach 2:
The patent creates a probabilistic model (copy) of the ray-tracing behavior that can be evaluated efficiently without performing actual ray launches. The pre-computed probability distribution functions serve as a simplified representation that reproduces the positioning information that would otherwise require numerous ray simulations
Data Source
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AI summary
The invention relates to a method and devices for determining a piece of data representing a position of a user equipment within an environment which comprises a set of base stations. According to the invention, the method comprises the following steps: - Obtaining (S01) a vector of N angles ([y1, ...,yN]) of reception of a signal emitted by said user equipment, each angle of said vector corresponding to an angle of reception of the signal at a given base station of the set of base stations, - Obtaining (S02) N probability distributions, each probability distribution being obtained from a result of a ray launching in a 3D representation of said environment, - Computing (S03) at least one probability of the position of the user equipment, and as a function of said N probability distributions and said vector of N angles.