| Nowdays,all kinds of tiny weapons and equipments are put into use in military area,so that they can meet requirements in the circumstance of high strength.Besides,the tiny weapons are also applied in investigation field.In the field of civil use,they are also widely used.MEMS/GPS integrated navigation system not only has the advantages of low cost,small size and environmental adaptability,but also combines the merits of each single navigation system,so that navigation accuracy has been greatly improved.By analyzing the problems which exist in the current MEMS/GPS integrated navigation system,this subject aims to improve and make the system innovative.As a result,it can achieve the goal of high precision designed by the project.This article will mainly from the sensor error analysis and compensation aspects,the aspects of integrated navigation system error modeling and the establishment of filter model and the aspect of filter algorithm for integrated navigation system to improve.As a consequence of it,it can achieve the goal that is set by the project.The main contents of this paper are as follows:Firstly,this article introduces the background and significance of the research.And then it analyzes the development status of related fields at home and abroad.The field refers to the development of MEMS inertial device,the evolution of satellite navigation and the development of integrated navigation algorithm.Then the existing problems of MEMS/GPS integrated navigation system are analyzed.The problems mainly refer to the sensor error compensation,integrated syetem error modeling,the establishment of filter model and integrated navigation system filter algorithm.At last,this article gives the overall design scheme of the integrated system.Secondly,by improving the error model of the sensor and improving the error compensation technique,the purpose of improving the precision of the sensor is achieved.Through the above method,the error compensation of MEMS device can be better.The zreo bias,scale factor,installation error and the error model of the sensor are estabilished.The calibration is completed by using the calibration method.Temperature compensation of MEMS is realized by neural network technology.Thirdly,the fourth chapter will optimize the model of MEMS /GPS integrated navigation system.This topic in the error model of integrated navigation syetem is no longer using the fiber optical error equations of strapdown inertial navigation syetem,but considering the characteristics of the MEMS sensor itself to establish the error equation for MEMS SINS.In the process of establishing the filtering model of the integrated navigation system,thegeomagnetic sensor is introduced as the measuring equipment,and the filtering model of attitude+velocity+position is established innovatively.Finally,we design the filtering algorithm of the MEMS/GPS/geomagnetic integrated navigation system.This paper is improved to increase the stability of the strong tracking Kalman filter,and then for the MEMS/GPS/magnetic navigation system will encounter the time-varying measuration noise and GPS outliers,so we design MEMS/GPS filter algorithm.At first we modified strong tracking filtering algorithm,so that it can improve its accuracy.And then we combine adaptive Kalman filter with strong tracking Kalman filter.So we design the adptive strong tracking Kalman filter algorithm. |
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