The development of a micro-electromechanical systems (MEMS) inertial navigation system for the navigation of underwater vehicles, both autonomous underwater vehicles (AUVs) and remotely-operated vehicles (ROVs), is extremely challenging. The navigation estimation of underwater vehicles is easily influenced by error noise arising in the MEMS-based inertial sensors. Therefore, this paper presents a integrated calibration method to overcome the challenges of MEMS-based inertial sensors for underwater navigation. The MEMS-based inertial sensors module is composed of a micro-accelerometer, a micro-gyroscope, and signal processing circuits. In general, the sources of error noise can be categorized into two groups, deterministic and stochastic: the former primarily include bias errors, misalignment and nonlinearity; the latter include temperature effects and signal drifting. Linearity calibration is used to modify deterministic errors and wavelet analysis can suppress stochastic noise. The integrated calibration method therefore includes bias compensation, linearity calibration and wavelet signal processing to enhance the accuracy and performance of the MEMS-based inertial navigation system. The experimental results demonstrate that the output signal can be corrected suitably by means of the proposed method. Overall, the results confirm the strong potential of MEMS-based inertial sensors for use in underwater vehicle navigation applications.
|Number of pages||12|
|Journal||Journal of Taiwan Society of Naval Architects and Marine Engineers|
|Publication status||Published - 2012 Aug 1|
All Science Journal Classification (ASJC) codes
- Ocean Engineering
- Mechanical Engineering