Indoor Localization Using Adaptive Inaudible Acoustic Signals
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Solution Overview
Problem
Current indoor localization techniques face challenges in achieving high accuracy due to variations in ambient conditions such as spatial structure, device configuration, and temperature, leading to inconsistent localization results.
Innovation Solution
An electronic device equipped with a speaker to output inaudible acoustic signals and microphones to receive reflected waves, utilizing a waveform optimization model and machine learning to adaptively generate optimized signals for spatial structures, update parameters based on signal changes, and determine object location information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional localization techniques are used, then the system is simple to implement, but localization accuracy deteriorates due to variations in ambient conditions
Solution Approach 1:
The patent implements dynamic adaptation by continuously monitoring signal characteristics and adjusting localization parameters in real-time based on ambient conditions. The system transitions from static localization parameters to dynamic ones that adapt to changing environmental factors such as temperature, spatial structure variations, and device configuration changes, thereby maintaining high accuracy without requiring complete system redesign.
Solution Approach 2:
The patent employs parameter optimization by identifying and adjusting key localization parameters (such as signal frequency, amplitude, and correlation thresholds) based on detected ambient conditions. This allows the system to compensate for environmental variations by modifying operational parameters rather than changing the fundamental system architecture, balancing accuracy improvement with acceptable complexity.
2Measurement precision
If adaptive signal optimization is implemented, then localization accuracy improves, but computational complexity increases
Solution Approach 1:
The patent applies preliminary optimization by pre-calculating and storing optimal signal parameters and correlation thresholds for different ambient conditions. During actual localization operations, the system retrieves pre-computed values rather than performing complex real-time optimization, significantly reducing computational burden while maintaining high accuracy through condition-based parameter selection.
Solution Approach 2:
The patent implements feedback mechanisms where localization results and signal quality metrics are continuously monitored and used to adjust optimization parameters. This closed-loop approach allows the system to learn from past performance and refine its signal optimization strategy over time, improving accuracy while computational complexity increases only marginally due to the iterative nature of the feedback process.
3Adaptability or versatility
If waveform optimization model is used to update parameters, then adaptability to spatial structure changes improves, but processing time increases
Solution Approach 1:
The patent merges the waveform optimization model with the signal processing pipeline by integrating parameter update operations into the existing localization workflow. Instead of running optimization as a separate post-processing step, the system combines parameter estimation and optimization into a unified process that shares computational resources and data structures, reducing overall processing time while maintaining adaptability to spatial structure changes.
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
The solution enhances localization accuracy by iteratively optimizing signal parameters and updating models based on ambient conditions, improving the precision of object and spatial structure changes detection.
Implementation Method 1
a speaker configured to output an inaudible acoustic signal
Implementation Method 2
one or more microphones configured to receive a first reflected wave signal which is the output inaudible acoustic signal reflected by a spatial structure
Implementation Method 3
one or more microphones configured to receive a first reflected wave signal
Implementation Method 4
obtain a signal change amount based on a correlation between a reference signal corresponding to the inaudible acoustic signal and the received first reflected wave signal
Data Source
AI summary
An electronic device includes a speaker configured to output an inaudible acoustic signal, one or more microphones configured to receive a first reflected wave signal, a memory storing one or more instructions, and one or more processors configured to execute the one or more instructions to obtain a signal change amount based on a correlation between a reference signal corresponding to the inaudible acoustic signal and the received first reflected wave signal, based on the signal change amount exceeding a first threshold value corresponding to a movement of an object, obtain object location information corresponding to a location of the object in a spatial structure based on the signal change amount, and based on the signal change amount exceeding a second threshold value corresponding to a change in the spatial structure, update a final parameter set corresponding to the inaudible acoustic signal by using a waveform optimization model.