State Parameter Adjustment Filtering Method of Airborne POS Based on Instantaneous Observable Degree Model

The position and orientation system is integrated measurement equipment for the airborne remote sensing system, and the measurement precision plays a vital role in imaging compensation. Because of the observable degree of state variable changes in real time with movement, the existing filtering method with constant state parameters reduces the attitude precision. In order to solve the problem, a state parameter adjustment filtering method based on instantaneous observable degree model is proposed. An instantaneous observable degree model is established to analyze the impact mechanism of movement on observable degree. On the basis of the model, an observable adjustment factor is constructed to adjust the state parameter. Flight experiment is carried out, which verifies that the proposed method is effective in improving the attitude precision.

[1]  Chingiz Hajiyev,et al.  Gyro-free attitude and rate estimation for a small satellite using SVD and EKF , 2016 .

[2]  Ronan Arraes Jardim Chagas,et al.  Observability analysis of inertial navigation errors from optical flow subspace constraint , 2016, Inf. Sci..

[3]  Wei Wang,et al.  Decoupled Observability Analyses of Error States in INS/GPS Integration , 2014 .

[4]  Shengying Zhu,et al.  Observability-Based Beacon Configuration Optimization for Mars Entry Navigation , 2015 .

[5]  M. Mostafa,et al.  DIRECT POSITIONING AND ORIENTATION SYSTEMS HOW DO THEY WORK? WHAT IS THE ATTAINABLE ACCURACY? , 2001 .

[6]  Walter Fichter,et al.  Observability Criteria and Unobservable Maneuvers for In-Orbit Bearings-Only Navigation , 2014 .

[7]  Roee Diamant,et al.  Observability Analysis of DVL/PS Aided INS for a Maneuvering AUV , 2015, Sensors.

[8]  Shesheng Gao,et al.  Rapid alignment method based on local observability analysis for strapdown inertial navigation system , 2014 .

[9]  Bing Luo,et al.  Observability Analysis of a MEMS INS/GPS Integration System with Gyroscope G-Sensitivity Errors , 2014, Sensors.

[10]  Jiancheng Fang,et al.  Integrated Calibration Method for Dithered RLG POS Using a Hybrid Analytic/Kalman Filter Approach , 2013, IEEE Transactions on Instrumentation and Measurement.

[11]  Yanqiang Yang,et al.  Local Observability Analysis of Star Sensor Installation Errors in a SINS/CNS Integration System for Near-Earth Flight Vehicles , 2017, Sensors.

[12]  Maiying Zhong,et al.  On Analytical Error Analysis of POS for Ground Alignment and Constant-Velocity Flight , 2016, IEEE Transactions on Instrumentation and Measurement.

[13]  Young Min Yoo,et al.  A theoretical approach to observability analysis of the SDINS/GPS in maneuvering with horizontal constant velocity , 2012 .

[14]  Hongguang Ma,et al.  Improving Accuracy of the Vehicle Attitude Estimation for Low-Cost INS/GPS Integration Aided by the GPS-Measured Course Angle , 2013, IEEE Transactions on Intelligent Transportation Systems.

[15]  Yiannos Manoli,et al.  Observing Relative Motion With Three Accelerometer Triads , 2014, IEEE Transactions on Instrumentation and Measurement.

[16]  I. Bar-Itzhack,et al.  Observability analysis of piece-wise constant systems. I. Theory , 1992 .

[17]  Jiancheng Fang,et al.  In-Flight Alignment of POS Based on State-Transition Matrix , 2015, IEEE Sensors Journal.

[18]  Zhang Yuan Analysis on Observability of INS Transfer Alignment Based on SVD Method , 2005 .

[19]  Xiaolin Gong,et al.  An innovative transfer alignment method based on federated filter for airborne distributed POS , 2016 .

[20]  Huapeng Yu,et al.  Stochastic observability-based analytic optimization of SINS multiposition alignment , 2015, IEEE Transactions on Aerospace and Electronic Systems.