Adaptive Sampling Rate Control for MEMS Sensor Power Optimization
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Solution Overview
Problem
MEMS sensors in consumer devices face a tradeoff between sampling rate and power consumption, particularly in battery-powered devices, where reducing power consumption without degrading performance is crucial, especially in satellite-based navigation systems where signal degradation occurs.
Innovation Solution
Adaptive control of MEMS sensor sampling rates based on user dynamics, using dynamics estimation logic to determine low or high user dynamics and adjust sampling rates accordingly, with a system comprising sensors like accelerometers, magnetometers, and gyroscopes, and a sampling rate engine to generate and control these rates, allowing for different sampling rates for each sensor and the ability to switch between high and low power modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the MEMS sensor sampling rate is increased to maintain navigation performance, then measurement precision is improved, but power consumption increases
Solution Approach 1:
The patent implements dynamic adjustment of sampling rates based on detected motion characteristics. The system transitions from static sampling rate configuration to dynamic sampling rate adaptation, where the sampling rate automatically increases during high-motion periods and decreases during low-motion periods, resolving the contradiction between maintaining measurement precision and reducing power consumption
Solution Approach 2:
The system changes the sampling rate parameter adaptively based on motion detection results. By monitoring motion characteristics and adjusting the sampling rate parameter accordingly, the system optimizes the balance between navigation accuracy and power consumption, using higher sampling rates only when necessary for accurate measurement
2Duration of action of moving object
If the sampling rate is reduced to extend battery life, then power consumption decreases, but navigation system performance degrades
Solution Approach 1:
The system employs periodic motion analysis where motion characteristics are evaluated over time intervals. By detecting periodic or sustained motion patterns, the system can confidently reduce sampling rates during stable low-motion periods while maintaining high sampling rates during transient or significant motion events, thus extending battery life without compromising navigation reliability
Solution Approach 2:
The system uses feedback from motion detection algorithms to dynamically control sampling rate adjustments. The motion characteristics detected by the sensor are fed back to the sampling rate control logic, which adjusts the sampling rate accordingly, ensuring that navigation performance is maintained when needed while allowing power savings during stable conditions
Data Source
AI summary
A system comprises a plurality of sensors, a sensor processor, and a sampling rate engine. The sensor processor is coupled to an output of each sensor of the plurality of sensors. The sensor processor estimates user dynamics in response to a first output signal of a first sensor of the plurality of sensors. The sampling rate engine is coupled to an output of the sensor processor. The sampling rate engine determines a sampling rate value of a second sensor of the plurality of sensors in response to a user dynamics value from the sensor processor. The second sensor comprises a selectable sampling rate. The selectable sampling rate is configured in response to the sampling rate value determined by the sampling rate engine.