Sensor Management Module for GNSS Dead Zone Positioning
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Solution Overview
Problem
Portable user devices face challenges in determining their position within GNSS dead zones, such as inside radio-opaque buildings, where traditional GNSS methods fail, and existing alternative techniques are not energy-efficient or effective in conserving battery resources.
Innovation Solution
The implementation of a sensor management module that determines when to activate a device movement sensor module for dead-reckoning and crowd-sourcing, using different probing techniques based on proximity to the GNSS dead zone, with energy-efficient strategies to conserve battery life and manage data collection quotas and battery levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If alternative techniques are used to determine position in GNSS dead zones, then position determination capability is improved, but energy consumption increases
Solution Approach 1:
The system performs preliminary probing using low-power techniques (WiFi scanning, cellular tower detection) before entering the dead zone to establish position context. This preliminary action allows the device to prepare position determination data in advance using energy-efficient methods, reducing the need for continuous high-power sensor activation once in the dead zone.
Solution Approach 2:
The system dynamically adjusts the activation state of the movement sensor module based on real-time conditions. The sensor management module continuously evaluates whether the device is in a GNSS dead zone and only activates the movement sensor when necessary, transitioning between active and inactive states to optimize energy consumption while maintaining position determination capability.
2Measurement precision
If continuous position tracking is performed in GNSS dead zones, then position accuracy is improved, but battery life decreases
Solution Approach 1:
Instead of continuous tracking, the system implements periodic position updates using movement sensor data. The movement sensor module is activated at intervals to capture position changes, and this periodic sampling maintains adequate position accuracy while significantly reducing battery consumption compared to continuous activation.
Solution Approach 2:
The system uses data from other sensors (accelerometer, gyroscope, magnetometer) that are already active for other purposes to contribute to position determination. By leveraging existing sensor data and only activating the movement sensor module when truly necessary, the system achieves position tracking with minimal additional energy expenditure.
3Reliability
If probing techniques are applied closer to the dead zone boundary, then position robustness is improved, but energy expenditure increases
Solution Approach 1:
The system applies different probing techniques at different locations relative to the dead zone boundary. Near the boundary, it uses more robust techniques (WiFi scanning, cellular detection), while farther away it relies on GNSS. This localized application of probing techniques ensures position robustness only where necessary, reducing overall energy expenditure.
Data Source
AI summary
The functionality described herein allows a user device to determine an appropriate juncture at which to initiate processing within a global navigation satellite system (GNSS) dead zone in an energy-efficient manner. In one implementation, the functionality employs a sensor management module for determining when to activate a device movement sensor module provided by a user device. When activated, the user device uses the device movement sensor module to perform any environment-specific processing, such as a dead-reckoning process for determining incremental positions within the venue. Further, in a crowd-sourcing application, the user device may report the incremental positions together with beacon information to remote processing functionality.