Self-adaptive robust estimation method and system for parameters of unmanned surface ship

The invention discloses a self-adaptive robust estimation method and system for parameters of an unmanned surface ship, and belongs to the field of automatic control. The method comprises the following steps: firstly, constructing a water surface unmanned ship augmented state estimation problem considering external disturbance, wherein augmented state vectors comprise a water surface unmanned ship state vector, a parameter vector and an unknown input vector; then, relying on a system real-time input vector and a measurement vector, a designed adaptive robust unscented Kalman filtering method is adopted to obtain a water surface unmanned ship model parameter; specifically, a robust Kalman filtering method is designed based on a maximum cross entropy criterion and a minimum mean square error criterion in consideration that the state of a water surface unmanned ship system is possibly interfered by outlier noise; considering that the statistical characteristics of the process noise of the unmanned surface ship s