基于Kalman滤波的电容屏触控轨迹平滑算法

doi:10.13229/j.cnki.jdxbgxb20170681

摘要/Abstract

摘要：

针对触控信号易受多种噪声影响而出现触控失真问题,提出了基于Kalman滤波的电容屏触控轨迹平滑算法。通过搭建电容屏触控信号采集和测试平台,获取原始触控电容数据并分析触控轨迹噪声特征,以此建立触控轨迹平滑系统的状态模型和观测模型,经Kalman算法的时域迭代处理实现电容屏触控轨迹的噪声抑制。试验测试结果证明:本文触控轨迹平滑滤波算法对比于传统平滑滤波算法,在不增加计算量的同时获得了更好的轨迹平均平滑度,可用于电容式触摸屏应用系统。

关键词: 信息处理技术, 电容式触摸屏, 触控轨迹噪声, Kalman滤波, 轨迹质量评价

Abstract:

Capacitive touch panels (CTPs) have been more popular owing to their excellent interactive performance. However, electronic magnetic interference, display noise and process variation negatively influence the accuracy of predictions of touch positions. A smooth tracking algorithm for capacitance touch panels based on Kalman filter was proposed. The original touch capacitance data and touch noise characteristic were detected using a micro-controller unit and a sensor integrated circuit. Additionally, the noise of touch trajectory was suppressed by Kalman algorithm timely through process model and measurement model of touch trajectory smooth system. Experimental results indicate that the proposed touch trajectory smooth algorithm has better performance compared to the traditional filtering algorithms, and the algorithm can be used to CTP systems.

Key words: information procession technology, capacitive touch panels(CTPs), touch tracking noise, Kalman filter, tracking quality evaluation

中图分类号:

TP319

李居朋,张祖成,李墨羽,缪德芳. 基于Kalman滤波的电容屏触控轨迹平滑算法[J]. 吉林大学学报(工学版), 2018, 48(6): 1910-1916.

LI Ju-peng,ZHANG Zu-cheng,LI Mo-yu,MIAO De-fang. Smooth tracking with a kalman filter algorithm for capacitive touch panels[J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1910-1916.

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参考文献 16

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S_avg	原轨迹	MAF算法		Wavelet算法		本文算法
S_avg	原轨迹	轨迹平滑度	计算时间/ms	轨迹平滑度	计算时间/ms	轨迹平滑度	计算时间/ms
T₁	2.8211	1.1513	0.0028	4.2714	0.1185	0.3159	0.0049
T₂	1.6202	0.4837	0.0096	2.4252	0.2911	0.1322	0.0114
T₃	2.0209	0.6081	0.0048	2.6716	0.2173	0.2036	0.0071
T₄	1.5286	0.4659	0.0102	2.2643	0.3823	0.1440	0.0145
T₅	1.5667	0.5557	0.0059	2.5727	0.2003	0.1768	0.0084
T₆	2.9968	1.0294	0.0029	4.8427	0.1147	0.3816	0.0046
T₇	1.2842	0.4190	0.0049	2.9810	0.1826	0.1368	0.0066
T₈	1.1489	0.3905	0.0059	2.7265	0.1991	0.1290	0.0071
T₉	1.2371	0.4342	0.0049	3.1694	0.2223	0.1374	0.0071
T₁₀	1.9440	0.7652	0.0064	4.1793	0.1384	0.2242	0.0103

轨迹平滑算法	平均平滑度S_avg	平均消耗时间/ms
MAF算法	0.6303	0.0059
Wavelet算法	3.2104	0.2067
本文算法	0.1982	0.0082