Error analysis and stochastic modeling of low-cost MEMS accelerometer

This paper presents the error analysis and stochastic modeling of commercial low-cost MEMS Accelerometer. Although Micro Electro Mechanical Systems (MEMS) based sensors have been utilized for the development of low-cost integrated navigation systems on the benefits of low inherent cost, small size, low power consumption, and solid reliability, it is significantly important to characterize the error behaviors of MEMS-based sensors and to construct more sophisticated mathematical modeling methods. The errors of MEMS-based accelerometer have been identified into deterministic and stochastic error sources and the stochastic error part was the focus to be discussed in this paper using discrete parameter models of stationary random process. Appropriate Autoregressive (AR) models have been analyzed which can be used to help the development of appropriate optimal algorithm for multiple sensor integration.