A smoothing and filtering method for capacitive touch track noise signal

Abstract

The invention discloses a smoothing filtering method of noise signals of a capacitive touch track. The smoothing filtering method comprises the first step of conducing a first linear touch on a side parallel to the capacitive touch screen, conducting multiple scanning on the capacitive touch screen to obtain data of the capacitive touch track, and adopting a centroid algorithm method to determine position coordinates of various touch points of the capacitive touch track to obtain the capacitive touch track; the second step of adopting a signal decomposition method to solve a noise track, and calculating variance of the noise track according to a mathematical statistics method of noise signals; the third step of adopting an extended Kalman filter method to conduct smoothing filtering on the capacitive touch track. According to the smoothing filtering method of the noise signals of the capacitive touch track, effective smoothing filtering treatment is conducted on the capacitive touch track, thus accuracy and noise processing property of the capacitive touch are improved, and a better touch user experience is obtained.

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

However, the moving average filter algorithm cannot handle the high noise interference touch trajectory data and balance the relationship between the filtering effect and the processing speed; the linear Kalman filter does not consider the nonlinear process of the touch process, and the filtering effect is limited to a certain extent.

Images