Virtual Base Station for Mobile Location Estimation
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Solution Overview
Problem
Existing mobile location estimation methods, such as the two-step least square algorithm, face significant accuracy decreases in harsh Non-Line of Sight (NLOS) environments, particularly at the boundaries of measurement error regions, leading to inaccurate location determination of mobile stations.
Innovation Solution
The method involves analyzing the geometric distribution of base stations to create a list of conditional equations and allocate a virtual base station, which helps in deriving a constraint equation to refine the location estimation by smoothing out measurement errors through a two-step least square algorithm, using virtual coefficients and geometric dilution of precision (GDOP) contours to prevent false solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the two-step least square algorithm is used for location estimation, then the algorithm is efficient and highly accurate for gentle NLOS environments, but the accuracy significantly decreases when the confined region grows due to increased NLOS error
Solution Approach 1:
A virtual base station is introduced as an intermediary element to provide additional geometric constraints. The virtual base station has coordinates (xv, yv) and virtual distance γ that are calculated based on the geometric distribution of actual base stations and GDOP analysis. This intermediary entity helps to better confine the mobile station location within the confined region by adding an extra constraint equation to the two-step least square algorithm, thereby improving reliability in harsh NLOS environments without sacrificing the efficiency and accuracy benefits of the original algorithm.
2Measurement precision
If more base stations are added to reduce measurement error impact, then the location estimation accuracy improves, but the device complexity and computational load increase
Solution Approach 1:
Instead of adding more physical base stations, the invention creates a virtual copy or representation of a base station. The virtual base station is a computational construct with coordinates (xv, yv) and virtual distance γ that mimics the geometric effect of an additional physical base station. This copying approach provides the benefits of increased geometric diversity and improved location estimation accuracy without the physical complexity and cost of deploying additional base stations.
Solution Approach 2:
The invention changes the parameters of the system by introducing virtual coordinates (xv, yv) and virtual distance γ as new variables. These parameters are derived from the geometric distribution analysis and GDOP contours of the existing base stations. By transforming the problem into a parameter space that includes virtual base station characteristics, the system achieves improved measurement precision through mathematical transformation rather than physical expansion.
3Reliability
If the confined region is used to define the MS location range, then the location estimation provides a reasonable range, but the region becomes too large to provide precise location when NLOS error increases
Solution Approach 1:
The invention dynamically adjusts the confinement of the mobile station location by introducing a virtual base station whose parameters (coordinates xv, yv and virtual distance γ) are adaptively calculated based on the geometric distribution of actual base stations and GDOP analysis. This dynamic approach allows the system to maintain an appropriately sized confined region even when NLOS errors increase, as the virtual base station parameters are recalculated to optimize the geometric constraints. The confined region remains sufficiently restrictive for precise location estimation while still accounting for increased error conditions.
Data Source
AI summary
A location estimation method is provided. The method locates coordinates of a mobile station (MS) by referencing a plurality of base stations (BS). A geometric distribution of the BS is analyzed to provide a list of conditional equations. A virtual BS is allocated, having a virtual distance to the MS to provide a constraint equation. The MS location is derived from the conditional equations and the constraint equation.