Joint Probability Density Function for Wireless Target Localization
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Solution Overview
Problem
Existing geo-location methods in Low-Power Wide-Area Networks (LPWANs, such as LoRaWAN, rely on point estimators that provide a single location estimate, lacking the comprehensive statistical information needed for accurate tracking and region probability calculations, especially in IoT applications where GPS chips are costly and power-intensive.
Innovation Solution
A method that generates a joint probability density function (PDF) based on time-of-arrival measurements from multiple receivers, allowing for the computation of the probability that a target device is within a specified region, incorporating a priori information and measurement errors, and enabling the generation of contour lines for efficient search operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If point estimators are used for location calculation, then the method is simple and fast, but the statistical information completeness and tracking accuracy are insufficient
Solution Approach 1:
The patent changes the parameter representation from a single point estimate to a joint probability density function characterized by multiple parameters (mean location, covariance matrix, etc.). This allows capturing both location and uncertainty statistics, resolving the contradiction between measurement precision and calculation complexity by transforming the problem into a statistical parameter estimation framework.
Solution Approach 2:
The patent introduces the joint probability density function as an intermediary that bridges the raw time-of-arrival measurements and the final location probability calculations. This intermediary structure enables comprehensive statistical information to be derived systematically, improving location accuracy without requiring overly complex direct calculations.
2Measurement precision
If GPS chips are used for location tracking, then location accuracy is high, but device cost and power consumption increase significantly
Solution Approach 1:
The patent replaces the mechanical/GPS-based location system with a wireless communication-based time-of-arrival measurement system. By using the existing LPWAN infrastructure and computing location statistically from multiple receivers, the system achieves comparable or superior location accuracy without the power consumption and cost of GPS chips, directly addressing the energy consumption contradiction.
Solution Approach 2:
The patent creates a virtual location system that copies the functionality of expensive GPS hardware through software-based statistical processing. Instead of relying on physical GPS receivers, the system uses time-of-arrival measurements from multiple inexpensive receivers and computes location probabilities through joint PDF calculations, effectively copying GPS functionality at lower cost and power consumption.
3Loss of information
If time-of-arrival measurements from multiple receivers are used, then location statistical information is improved, but measurement and calculation complexity increases
Solution Approach 1:
The patent merges the location estimation and uncertainty quantification into a single joint probability density function framework. By combining multiple time-of-arrival measurements and their statistical characteristics into one unified representation, the system achieves complete statistical information without proportionally increasing measurement system complexity, as the complexity is managed through mathematical integration rather than additional hardware.
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 provides more accurate and reliable location information, enabling efficient tracking and region probability calculations, improving the accuracy of target device localization in IoT applications without the need for expensive GPS chips.
Implementation Method 1
obtaining time of arrival measurements associated with reception, at a plurality of receiver devices at known or measured locations, of one or more wireless transmissions made by a target device
Data Source
AI summary
A method is provided for geo-location of a wireless target device. The method is able to generate complete statistical information about the target device in the form of a joint probability density function of the target's location. The method includes obtaining time of arrival measurements associated with reception, at a plurality of receiver devices at known or measured locations, of one or more wireless transmissions made by a target device at a location that is unknown. Based on the time of arrival measurements, the method includes computing a joint probability density function that is descriptive of a probability that the target device is within any specified region. The method then involves applying the joint probability density function to a particular specified region to compute the probability that the location of the target device is within the particular specified region.