Position error forecasting method for GPS (Global Position System)/MEMS-INS (Micro-Electricomechanical Systems-Inertial Navigation System) integrated navigation system based on SET2FNN

Abstract

The invention discloses a position error forecasting method for a GPS (Global Position System) / MEMS-INS (Micro-Electricomechanical Systems-Inertial Navigation System) integrated navigation system based on SET2FNN, . comprising the following steps that: (1) when the GPS / MEMS-INS integrated navigation system begins to work and the signal of the GPS is in a good condition, a UKF (Unscented Kalman Filter) includes two parallel operating modes: a forecasting mode and an updating mode, self-evolving real-time regulating and updating are carried out on the structure and the parameter of an SET2FNN model by taking the triaxial angular speed output by the gyro of the MEMS and the signal lost time of the GPS as the input of the SET2FNN and taking the diffidence of position errors output under the two modes of the UKF as an expected output of the SET2FNN; and (2) when the signal of the GPS is lost, the SET2FNN model and the UKF are both in the forecasting mode, the position error is forecasted and corrected by taking the triaxial angular speed output by the gyro of the MEMS and the signal lost time of the GPS as the input and using a method for dynamically combining the long-period forecasting of the SET2FNN model with the short-period forecasting of the UKF, and then a position result of the corrected integrated navigation system is output.

Description

technical field [0001] The invention relates to the field of positioning error prediction of a GPS / MEMS-INS (Micro Electro Mechanical System-Inertial Navigation System, an inertial navigation system based on a micro-electromechanical system, referred to as a micro inertial navigation system) integrated navigation system, and in particular to a SET2FNN (Self-Evolving Interval Type-2 Fuzzy Neural Network, self-evolving interval type-2 Fuzzy Neural Network) GPS / MEMS-INS integrated navigation system positioning error prediction method when GPS signal is lost. Background technique [0002] In recent years, with the development of MEMS technology, MEMS inertial sensors have become more and more widely used in the field of navigation and positioning. Its characteristics of small size, light weight and low cost meet the basic requirements for navigation systems in most commercial application fields. Due to the complementary characteristics of MEMS-INS and GPS, GPS / MEMS-INS integrat...

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Problems solved by technology

[0010] The object of the invention is to: overcome the deficiencies in the prior art, provide a kind of GPS / MEMS-INS integrated navigation system positioning error prediction method based on SET2FNN, this method SET2FNN adopts type-2 fuzzy logic system, than based on type-1 fuzzy logic The system's ANFIS is more suitable for dealing with uncertainties, and can better solve the problem that the output noise of MEMS inertial devices greatly affects the positioning error modeling and prediction accuracy, and SET2FNN conducts self-evolutionary adjustment of structure and parameters online, which overcomes the problem of ANFIS due to Adopting a fixed structure leads to poor model adaptive ability and poor dynamic performance when applied to time-varying systems such as integrated navigation systems

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