Improved Angular Velocity Estimation Using MEMS Sensors with Applications in Miniature Inertially Stabilized Platforms

Abstract

The performance of any inertially stabilized platform (ISP) is strongly related to the bandwidth and accuracy of the angular velocity signals. This paper discusses the development of an optimal state estimator for sensing inertial velocity using low-cost micro-electro-mechanical systems (MEMS) sensors. A low-bandwidth gyroscope is used alone with two low-performance accelerometers to obtain the estimation. The gyroscope has its own limited dynamics and mainly contributes to the low-frequency components of the estimation. The accelerometers have inherent biases and mainly contribute to the high-frequency components of the estimation. Extensive experimental results show that the state estimator can achieve high-performance signals over a wide range of velocities without drifts in both the t- and s-domains. Furthermore, with applications in miniature inertially stabilized platforms, the control characteristic presents a significantly improvement over the existing methods. The method can be also applied to robotics, attitude estimation, and friction compensation.