Accelerometers are used in numerous industries including aircrafts and missile navigations systems, rotary machines, and electronic devices such as tablets, cell phones, and cameras. Accelerometers of different purposes and specifications are being produced in large quantities. The large demand for accelerometers forces the need for accelerometer testing methodology that is more convenient and accurate. Inertial Micro-Electromechanical Systems Accelerometer (MEMS) require a series of tests that include physical stimuli. One of the key challenges is the cost associated with testing. Therefore, the accurate prediction of the sensor functions not only reduces the testing time but also more importantly contributes to reducing testing cost. The accelerometer error model must be constructed, and the coefficients in the error equations must be determined. Therefore, Kalman filter in the analysis of visual iii motion has been documented frequently. The filter is constructed as a mean squared error minimizer. The purpose of filtering is to extract the required information from a signal, ignoring everything else.iv Acknowledgements
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