New self-calibration schemes for accelerometers of platform

To guarantee success of precision navigation, it is necessary to carry out in-field calibration for the accelerometers of platform inertial navigation system (INS) before a mission is launched. Traditional continuous self-calibration methods are not fit for accelerometers' fast calibration because the platform misalignments have to be estimated precisely and the nonlinear coupling terms will affect accuracy. Focusing on this field, the present paper proposes new fast self-calibration methods for the accelerometers of platform INS. Continuous calibration schemes are designed and optimized by the genetic algorithm (GA) to improve the observability of parameters. Simulations are conducted to analyze the performance and the sensitivity of the proposed methods. It is proved that the proposed methods can estimate the accelerometer parameter more precisely and more practical to deal with urgent situations than traditional methods.