Wearable Sensor Assembly for GPS-Denied Path Mapping
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems fail to effectively track and route mobile objects in environments lacking GPS signals, wireless networks, and other localization infrastructure, such as indoor or hazardous settings where visibility is limited.
Innovation Solution
A wearable sensor assembly combining an inertial measurement unit (IMU) and a radio-frequency (RF) radar unit, which collects data on radar velocities, angular velocities, and linear accelerations to determine translation and orientation information, and a processor that combines this data to create path-based maps and provide routing within these environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS-based localization systems are used, then positioning accuracy is improved, but the system becomes unavailable in environments without GPS signals (indoor, hazardous areas)
Solution Approach 1:
The patent introduces an inertial measurement unit (IMU) as an intermediary system that operates independently of GPS infrastructure. The IMU uses accelerometers and gyroscopes to measure motion and orientation, providing positioning capability in environments where GPS signals are unavailable, thus resolving the contradiction between positioning accuracy and environmental adaptability
Solution Approach 2:
The patent replaces the satellite-based electromagnetic signal system (GPS) with a mechanical inertial sensing system (IMU). This substitution enables the system to function in GPS-denied environments by using mechanical sensors to detect motion and compute position through integration of acceleration and orientation data
2Reliability
If traditional localization infrastructure (WiFi, radio beacons) is deployed, then tracking capability is improved, but the system complexity and infrastructure requirements increase
Solution Approach 1:
The patent enables the mobile object to self-track using onboard IMU sensors without requiring external localization infrastructure. The system performs self-contained motion tracking by processing data from its own accelerometers and gyroscopes, eliminating the need for deployed WiFi networks or radio beacon systems
Solution Approach 2:
The patent extracts the localization function from external infrastructure and relocates it to the mobile object itself. By placing IMU sensors on the mobile object, the system removes the dependency on external tracking infrastructure, thereby reducing overall system complexity while maintaining tracking capability
3Reliability
If sensor fusion algorithms are implemented, then positioning reliability in GPS-denied environments is improved, but computational requirements and processing complexity increase
Solution Approach 1:
The patent merges data from multiple IMU sensors (accelerometers, gyroscopes) and integrates them through sensor fusion algorithms to improve positioning reliability. By combining information from different sensor types and fusing their data streams, the system achieves more accurate and reliable tracking in GPS-denied environments despite increased processing requirements
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 effective tracking and mapping of mobile objects in environments without GPS or other infrastructure, providing accurate path generation and routing, even in hazardous conditions where traditional localization methods are unavailable.
Implementation Method 1
one or more angular velocities of the mobile object from the IMU, and (iii) one or more linear accelerations from the IMU
Implementation Method 2
one or more radar velocities from the RF radar unit
Data Source
AI summary
Systems and methods of path-based mapping and routing are provided. Translation information and absolute information of mobile objects in environments are determined based on a fusion of sensing data from a radar and an inertial measurement unit (IMU) including a gyroscope and an accelerometer, from which path-based maps and optimal routes can be generated.