A smoothing and filtering method for capacitive touch track noise signal

Abstract

The invention discloses a capacitive touch control trajectory noise signal smoothing filtering method comprising the following steps that S1: primary linear touch control is performed in a way of being parallel to one side of a capacitive screen, the capacitive screen is scanned for multiple times so that capacitive touch control trajectory data are obtained, and the position coordinates of each touch control point in the capacitive touch control trajectories are determined by a centroid method so that the capacitive touch control trajectories are obtained; S2: noise trajectories are solved by using a signal decomposition method, and the variance of the noise trajectories is calculated according to the mathematical statistic method of noise signals; and S3: smoothing filtering is performed on the capacitive touch control trajectories by using the Kalman filtering method. Effective smoothing filtering processing can be performed on the touch control trajectory noise of the capacitive screen so that the touch control accuracy and the noise processing performance of the capacitive screen can be enhanced and the better touch control user experience can be acquired.

Description

technical field [0001] The present invention relates to the field of capacitive touch screen signal processing, and more specifically, to a method for smoothing and filtering capacitive touch track noise signals. Background technique [0002] At present, capacitive touch screen has become the mainstream choice of human-computer interaction interface. Capacitive touch screen has won the recognition of users for its good touch experience, but capacitive touch screen is easy to be affected by the internal noise of the device and produce false and wrong responses. , which is typically manifested in the inaccurate prediction of the touch point in the touch track and the output of the zigzag track during the touch operation process, thereby affecting the user experience level. In the face of the influence of noise from the DC converter, display driver, antenna or other sources inside the system, the touch driver must achieve the same level of user experience, then take necessary a...

AI Technical Summary

Problems solved by technology

[0003] With the continuous development of signal processing technology, it has become one of the research hotspots in domestic and foreign academic circles to use hardware processing or software processing methods to perform feature analysis and filter processing on the noise existing in touch signals, and to output stable and reliable touch traces. First, for the filtering processing of the touch track signal, the existing research mostly adopts methods such as moving average filtering for noise processing. Since the effect of the moving average filtering algorithm depends on the selection of the length of the data window, the longer the data window can obtain more noise. Good filtering effect, the filtering effect is unstable, and it also brings the problem of touch delay

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