Acceleration Filter is an open source code example and working Android application intended to allow users to explore the use of digital low-pass filters and mean filters on the devices acceleration sensor. A low-pass filter is a filter that passes low-frequency signals and attenuates signals with frequencies higher than the cutoff frequency. The low-pass filter can be used to reduce the noise on sensor signals, or can be used in alternative methods such as estimating linear acceleration.
Acceleration Filter allows the user to view the outputs from multiple low-pass filters in real-time. This makes it easy to compare the performance of different low-pass filters. Along with the low-pass filters, a mean averaging method is also available to compare the relative performance of the low-pass filters to simple mean averaging filters. The user can select if the low-pass filter scaling factor, alpha, is determine dynamically based on a time constant and the update frequency of the sensor... or the user can set alpha to a static value. This allows user to explore a large number of filter settings to quickly determine what is best for their application. Perfect for visualizing the effect of low-pass filters on digital signals. You can even log the output to an external .csv file.
Acceleration Filter allows you to visulize acceleration measurements. Plot acceleration data from all three axis in real-time. This data can be written to an external .CSV file, saved and then viewed on your favorite spreadsheet application at a later time.
Apply low-pass and averaging filters to the acceleration measurements to optimize response and noise for your application. Save the measurements to an external .CSV file to easily compare the performance of the two filters. Visualize the noise of each filter in real-time.