Distributed Sensor Network for Precise Positioning
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Solution Overview
Problem
Precise positioning of underground infrastructure and linear utility conveyances is challenging, especially in dense urban environments, due to signal distortion and obstructions, which existing methods fail to address effectively.
Innovation Solution
A method involving a distributed sensor network that measures complex electromagnetic field strength and phase values to determine the location and orientation of transmitter objects using a controller and receivers with orthogonal coil detectors, allowing for real-time geo-referencing and compensation for field distortions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional single-point or limited sensor location methods are used, then equipment deployment is simpler, but positioning precision and ability to handle signal distortion deteriorate
Solution Approach 1:
The system divides the monitoring space into multiple zones with distributed sensors instead of using a single centralized sensor. Each sensor node independently measures electromagnetic field parameters, and the controller aggregates data from all nodes to compute precise transmitter location, thereby improving positioning accuracy through spatial distribution.
Solution Approach 2:
The system combines measurements from multiple distributed sensors with electromagnetic field modeling and optimization algorithms to achieve precise positioning. The controller merges data from all sensor nodes, integrates it with expected field models, and uses optimization to determine the most accurate transmitter location despite signal distortion.
2Measurement precision
If distributed sensor networks are deployed to improve positioning accuracy, then measurement precision improves, but device complexity increases
Solution Approach 1:
Each sensor node in the distributed network is designed as a universal unit that can perform multiple functions: measuring electromagnetic field parameters, determining its own location, and communicating with the controller. This multi-functionality reduces overall system complexity despite the distributed architecture.
Solution Approach 2:
The system implements feedback through the controller that receives measurements from all sensor nodes, compares them with expected electromagnetic field models, and uses optimization algorithms to refine location estimates. This feedback loop continuously improves positioning accuracy while managing network complexity through centralized coordination.
3Ease of operation
If electromagnetic field measurements are used to locate underground utilities, then non-intrusive detection is achieved, but signal distortion from obstructions worsens measurement reliability
Solution Approach 1:
The system measures electromagnetic field parameters in multiple spatial dimensions using distributed sensors positioned at different locations and orientations. By capturing field data across multiple dimensions (x, y, z coordinates and field vector components), the system can triangulate transmitter location more accurately and compensate for signal distortion from obstructions.
Solution Approach 2:
The system performs preliminary electromagnetic field modeling to establish expected field patterns before actual measurement. By comparing actual measurements with pre-computed models, the system can identify and compensate for distortions caused by obstructions, thereby maintaining reliable detection despite signal interference.
4Length of stationary object
If low frequency RF signals are used for underground localization, then detection range is extended, but path loss increases
Solution Approach 1:
The system uses electromagnetic field modeling to create a virtual representation of the expected field pattern from the transmitter. By comparing actual sensor measurements with this modeled copy of the field, the system can accurately determine transmitter location even when the physical signal has undergone path loss or distortion, effectively extending detection capability.
Solution Approach 2:
The system measures multiple electromagnetic field parameters (magnitude, phase, and vector components) rather than relying on a single parameter. By analyzing changes in these parameters across the distributed sensor network, the system can compensate for path loss effects and extend effective detection range for low frequency signals.
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
Enables accurate and precise location of underground utilities without the need for equipment to be brought to specific points, providing confidence bounds and overcoming signal distortion issues, even in complex environments.
Implementation Method 1
measuring a set of complex electromagnetic field strength magnitude and phase values within a space using one or more receivers
Implementation Method 2
measuring a set of complex electromagnetic field strength magnitude and phase values within a space
Data Source
AI summary
A method for determining the location and orientation of a transmitter object by measuring a set of complex electromagnetic field magnitude and phase strengths within a space using one or more receivers is provided. The method includes modeling a set of expected complex electromagnetic strengths to estimated position and orientation of the transmitter object. And estimating parameters related to the transmitter object position based on the residual error between the measured set of complex electromagnetic field values and a set of expected electromagnetic field values. Further embodiments include a method as above including a plurality of receivers with known positions within a limited space including the transmitter object. A sensor network including a plurality of receivers to perform the above method is also provided. The receivers may communicate using a wireless channel.