Miniaturized Wireless Inertial Sensing System with Frequency Agile RF
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Solution Overview
Problem
Existing orientation and position sensing systems lack improved capabilities for data processing, communication, and accuracy, particularly in dynamic environments and applications requiring precise tracking of moving objects.
Innovation Solution
A system comprising a movable body with a device equipped with an orientation sensor, inertial position sensor, frequency agile RF transceiver, processor, and memory, allowing for data logging and wireless communication, along with a complementary filtering method to combine inertial and external position data for enhanced accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous wireless communication is used for position tracking, then real-time orientation and position data can be transmitted, but power consumption increases
Solution Approach 1:
The system implements periodic communication by logging inertial position data locally and transmitting only at intervals or when thresholds are exceeded, rather than continuously streaming data. This periodic action maintains tracking reliability while significantly reducing power consumption from the RF transceiver.
Solution Approach 2:
The system performs preliminary data processing and filtering locally before transmission, preparing data in advance for efficient wireless communication. This preliminary action reduces the frequency and volume of transmissions needed, thereby lowering power consumption while maintaining real-time tracking capability.
2Measurement precision
If high-precision inertial sensors are used for position tracking, then measurement accuracy improves, but device complexity and cost increase
Solution Approach 1:
The system merges data from multiple lower-cost sensor types (accelerometers, gyroscopes, magnetometers) to achieve high-precision position tracking that would otherwise require expensive single-solution inertial sensors. This combination approach maintains measurement precision while reducing device complexity and cost.
Solution Approach 2:
The system introduces complementary filtering and data fusion algorithms as intermediaries between raw sensor data and final position calculations. These intermediary processing steps enhance measurement precision from modest sensors without requiring complex hardware, thereby reducing overall device complexity.
3Loss of information
If data is continuously transmitted wirelessly for real-time monitoring, then orientation and position information is immediately available, but power consumption and communication interference increase
Solution Approach 1:
The system transmits data periodically rather than continuously, maintaining data availability for real-time monitoring while dramatically reducing energy consumption from the transceiver. Logged data between transmission intervals ensures information remains accessible without constant power expenditure.
Solution Approach 2:
The system performs preliminary data filtering, processing, and prioritization before transmission, preparing only essential or changed data for wireless communication. This preliminary action reduces transmission frequency and volume, lowering energy consumption while maintaining adequate data availability for monitoring applications.
Data Source
AI summary
A system includes a moveable body and a first device for mounting on the movable body. The first device includes an orientation sensor, an inertial position sensor, a first processor, a frequency agile RF transceiver, and a memory device.