Research On On-line Performance Detection Technology Of Intelligent Individual Soldier Navigation Module

The intelligent soldier navigation module is a wearable device that uses Micro Electro Mechanical System(MEMS)inertial sensors to access accurate positioning information of personnel,and has been widely used in the industry.However,the sensors have errors such as random noise and zero offset.The traditional detection method relies heavily on high-precision turntable equipment to detect the single navigation module,which directly leads to the problem of low detection efficiency and time-consuming.Therefore,this thesis aims to improve the traditional detection method and break through the technical barriers of online detection only in high-precision turntable scenarios,and design an online detection scheme for multiple intelligent individual soldier navigation modules so that it can complete online detection under various conditions such as turntable and manned state.This thesis uses the intelligent soldier navigation module with built-in MEMS gyroscope and MEMS accelerometer as the hardware platform for online detection.At the same time,the online detection system designed based on the platform provides the basis of hardware platform for the subsequent multi-channel data acquisition and online detection of intelligent soldier navigation module.Secondly,it analyzes and initializes several common errors in MEMS sensors.This thesis focuses on the three types of errors,which are random error,zero offset error and installation error.Firstly,this thesis proposes the regular particle filter algorithm to calibrate the random error,and use the improved twelve position method to initially calibrate the drift error,so that the measured value of the MEMS accelerometer is closer to the theoretical gravity acceleration value,and the measured value error is reduced from the original 0.3385m/s2 to 0.0415m/s2.In addition,for the installation error of the gyroscope,the high precision turntable is also used for its initial calibration,so that its measurement value error is reduced from the original 4.616°/s to 0.187°/s..An adaptive online calibration algorithm is designed for MEMS gyroscope to solve the accumulated error of attitude angle after long use of manned intelligent soldier navigation module.At the same time,the MEMS inertial sensor is difficult to capture the zero position in the human-carried motion environment,so this thesis innovatively proposes an online calibration algorithm for dynamic zero position based on the Long Short-Term Memory networks(LSTMs)model for the intelligent soldier navigation module.Experiments verify that the attitude angle delay is less than 0.2s,and the resolution error of the attitude angle is reduced by about 3 times.Finally,through the turntable and manned experiment verification,the entire online detection process greatly improve the efficiency of individual navigation module for multiple intelligence,and ensure that the positioning accuracy of a batch of modules can reach the qualified standard(horizontal accuracy <= 5% of the total distance,vertical accuracy <= 1.5 meters),to achieve the purpose of online detection of the performance of the intelligent individual soldier navigation module.