Attitude estimation and sensor identification utilizing nonlinear filters based on a low-cost MEMS magnetometer and sun sensor

A combination of low-cost micro-electoro-mechanical sensors (MEMSs) and nonlinear attitude estimation algorithm techniques can provide an inexpensive and accurate system for navigation and attitude determination. The features of MEMSs are their light weight and small size; hence, the MEMSs have found significant attention in low-cost navigation and control systems. A common disadvantage of these sensors is the significant errors that accompany the corresponding measurements. The accuracy obtained using MEMSs depends on a number of factors, such as scale factor, bias, and random noise corrections. However, these low-cost sensors suffer from large noise and errors, making calibration and error identification of critical importance.