Mobile Device Recalibration From Multi-Landmark 3D Geolocation
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Solution Overview
Problem
Existing methods for geolocating mobile devices are limited to two-dimensional positioning and do not effectively utilize angular survey measurements for three-dimensional geolocation and attitude determination without additional equipment like inertial measurement units.
Innovation Solution
A recalibration method using angular survey measurements from multiple landmarks, employing a combination of simulated annealing and Gauss-Newton algorithms to determine three-dimensional position and attitude of a mobile device, along with optional Levenberg-Marquardt algorithm for refinement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If bearing methods are used for geolocation, then two-dimensional positioning is achieved, but three-dimensional geolocation and attitude determination cannot be performed
Solution Approach 1:
The patent extends traditional two-dimensional bearing methods into three-dimensional space by incorporating elevation angles and performing calculations in a 3D coordinate system. The method uses spherical coordinate transformations and 3D geometric relationships to determine both position (x, y, z) and attitude (pitch, roll, yaw) of the mobile device, thereby adding the vertical dimension and rotational degrees of freedom to the geolocation capability.
2Adaptability or versatility
If additional equipment like inertial measurement units is used, then three-dimensional geolocation is possible, but device complexity increases
Solution Approach 1:
The patent enables the mobile device to determine its own three-dimensional position and attitude using only its existing sensors (camera, GPS, accelerometer) and computational algorithms. The device processes images of landmarks, extracts bearing and elevation information, and performs iterative optimization calculations internally without requiring external inertial measurement units or other additional specialized equipment.
3Device complexity
If angular survey measurements alone are used, then device simplicity is maintained, but measurement precision for three-dimensional positioning is insufficient
Solution Approach 1:
The patent employs iterative optimization algorithms (such as Gauss-Newton or Levenberg-Marquardt) that use feedback from measurement residuals to continuously refine the estimated position and attitude. The system calculates the difference between observed angular measurements and those predicted from current position estimates, then uses this feedback to update and improve the estimates until convergence is achieved, thereby achieving high precision without additional hardware.
Solution Approach 2:
The patent transforms the measurement problem by changing the mathematical parameters and coordinate systems used for calculation. It converts image bearing measurements into 3D spatial coordinates through spherical coordinate transformations and applies non-linear optimization techniques that adjust position and attitude parameters iteratively, thereby extracting maximum precision from the available angular survey data.
Data Source
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AI summary
The present invention relates to a method of recalibrating a mobile device to a plurality of landmarks during geolocation, comprising the following steps: - acquisition (110) of bearing and elevation measurements of at least four landmarks in a reference frame of the mobile device; - determination (120) of an angular deviation for each of at least three pairs of said landmarks; - determination (130) of an initial approximation of the position of the mobile device from said angular deviations; - determination (140) of an improved approximation of the position of the mobile device from the initial approximation and said angular deviations; - determination (150) of the distances between the mobile device and each of said landmarks; - determination (160) of a first approximation of the attitude of the mobile device from said distances.