Capacitive Proximity Sensing With Dual LPF Switching
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Solution Overview
Problem
Existing proximity detection methods for capacitive sensing in wireless devices face challenges such as poor signal-to-noise ratio (SNR), large parasitic capacitance, and temperature fluctuations, leading to inaccurate proximity distance detection, particularly in the presence of a human body.
Innovation Solution
Employing an advanced low-pass filter (ALP) with two parallel low-pass filters (LPFs) of different filtering rates, coupled with logic to dynamically switch between them based on proximity distance changes, and using a recurrent neural network (RNN) to optimize SNR during stable proximity conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single low-pass filter is used for capacitive sensing, then the filtering of noise is achieved, but the response speed to proximity changes is slow and precision is reduced
Solution Approach 1:
The patent divides the single filtering function into two separate parallel low-pass filters with different filtering rates. The first LPF uses a higher filtering rate for stable conditions, while the second LPF uses a lower filtering rate for changing conditions. This segmentation allows the system to simultaneously achieve good noise filtering and fast response by selecting the appropriate filter based on the current state.
Solution Approach 2:
The patent implements dynamic switching between two different filtering rates based on the detected proximity changes. When proximity distance changes exceed a threshold, the system switches to the second LPF with lower filtering rate for faster response. When changes are within threshold, it uses the first LPF with higher filtering rate for better noise filtering. This dynamic adaptation resolves the contradiction between filtering performance and response speed.
2Measurement precision
If filtering rate is increased to improve noise filtering, then SNR is improved, but the ability to detect rapid proximity changes is reduced
Solution Approach 1:
The system dynamically adjusts the filtering rate based on the detected proximity changes. The controller monitors proximity distance changes and switches between two LPFs with different filtering rates. This dynamic adjustment allows the system to optimize SNR when conditions are stable while maintaining the ability to detect rapid changes when needed.
Solution Approach 2:
The patent changes the filtering rate parameter based on the operational conditions. By having two LPFs with different filtering rates and switching between them, the system can change the filtering parameter to match the current situation - using higher filtering rate for better SNR during stable periods and lower filtering rate for faster response during changing periods.
3Volume of moving object
If antenna size is reduced for device miniaturization, then device form factor is improved, but capacitive sensing capability and SNR deteriorate
Solution Approach 1:
The patent changes the filtering parameters (filtering rates) to optimize the performance of small antennas. By using dual LPFs with different filtering rates and switching between them, the system compensates for the reduced capacitive sensing capability of miniaturized antennas, maintaining measurement precision despite the smaller antenna size.
Solution Approach 2:
The patent replaces hardware improvements (larger antennas) with signal processing solutions (dual LPF system). Instead of increasing antenna size to improve sensing capability, the system uses advanced filtering algorithms to enhance the weak signals from small antennas, substituting mechanical/s物理 improvements with electronic/software solutions.
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
Improves the precision and responsiveness of proximity detection by quickly adapting to changes in proximity distance, enhancing SNR in noisy environments and reducing the impact of temperature fluctuations.
Implementation Method 1
an antenna itself is used as a capacitive sensor and a proximity detection algorithm is employed to detect proximity of an object
Implementation Method 2
the RF electromagnetic fields can be reduced to meet emission regulations criteria and SAR standards
Implementation Method 3
Employing an advanced low-pass filter (ALP) with two parallel low-pass filters (LPFs) of different filtering rates
Implementation Method 4
significant temperature changes that cause unpredictability in being able to precisely detect the presence of an object
Data Source
AI summary
An integrated circuit includes a capacitive sensing circuit to receive signal values associated with a proximity distance to an object. A pair of low pass filters (LPFs) are coupled in parallel to the capacitive sensing circuit and include a first LPF configured with a low filtering rate and a second LPF configured with high filtering rate that is higher than that of the low filtering rate. Control logic is coupled to the pair of LPFs and estimates the proximity distance based on one or more filtered signal values received from the pair of LPFs. The logic causes the second LPF to filter the signal values while the proximity distance remains unchanged. The logic detects a change in the proximity distance beyond a threshold value. The logic causes the first LPF to filter a subsequent signal value received from the capacitive sensing circuit based on detecting the change.