Journal of Jilin University(Engineering and Technology Edition) ›› 2018, Vol. 48 ›› Issue (6): 1910-1916.doi: 10.13229/j.cnki.jdxbgxb20170681

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Smooth tracking with a kalman filter algorithm for capacitive touch panels

LI Ju-peng1(),ZHANG Zu-cheng1,LI Mo-yu1,MIAO De-fang2   

  1. 1. School of Electronic Information Engineering, Beijing Jiaotong University, Beijing 100044,China
    2. Chipone Technology (Beijing) Co.,Ltd., Beijing 100088,China
  • Received:2017-06-30 Online:2018-11-20 Published:2018-12-11

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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

CLC Number: 

  • TP319

Fig.1

Signal acquisition system of the capacitive"

Fig.2

Touch tracking including noise of three circles"

Fig.3

Noise characteristics analysis of tracking"

Fig.4

Comparison of results for the three kinds of noises between filtering methods"

Fig.5

Comparison of filtering results"

Table 1

Comparison of performances between different algorithms"

Savg 原轨迹 MAF算法 Wavelet算法 本文算法
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

Table 2

Comparison of performances between algorithms"

轨迹平滑算法 平均平滑度Savg 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
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