Recently integrated navigation systems are developed to use the advantages of both inertial navigation and global positioning system. In such integrated navigation systems when the GPS signal is missed, the system works based on inertial navigation data. In this condition the navigation error increases progressive, especially when the INS sensors have low accuracy. To overcome this problem in most of the previous researches neural networks or support vector machines are applied to learn the navigation errors when the auxiliary navigation signal exists. As soon as the auxiliary navigation signal is lost the output of trained NN’s are summed with the output of inertial navigation system to remove the navigation errors directly. In this paper a method is proposed to decrease the navigation error rate in presence of process and measurement noise. Actually here multilayer perceptron neural networks are trained to learn the navigation errors when the auxiliary navigation signal is received, then the output of neural networks are applied to a Kalman filter which estimates the navigation errors. Simulation is carried out on three different 6Dof paths. The results show that the proposed method is independent of flight path and has more effective performance in compare with mentioned methods.
Elhami, M., Sadat, M. “Simulation and Optimization of Guidance and Integrated Navigation System in Small Planes”, J. Mech. and Aerospace, Vol. 12, No. 1, 1395.##
Mousavi, M. and Zandi, M. “Improvement of Navigation System Accuracy Based on GPS/GLONASS Using Kalman Filter”, J. Sea Techniques, Vol. 2, No. 2, 1394.##
Khodaparast, A., Golshani, S. and Sadeghi, V. “Accuracy Increment of Position Estimation based on Integration of Inertial Navigation System and GPS for a Flight Vehicle”, Proc. Second Conf. Applicable Researchs in Electronic and Mechatronic, Tehran, Iran, 1993.##
Nasrollahi, S. and Ghahremani, N. “ Accuracy Increment of Navigation System Base on Integration of Inertial Navigationm Vehicle”, Proc. Electrical Eng. Conf., Tehran, Iran, 1389.##
Ahmadpour, A., Alavi, M. and Rahimi, R. “Improvement of GPS and INS Navigation Systems based on Extended Kalman Filter”, Proc. Int. Conf. Applicable Research on Electrical, Mechanical and Mechatronic Engineering, Tehran, Iran, 1394.##
Gorgi, M. and Farrokhi, M. “Integration of Iertial Navigation and GPS using Artificial Neural Networks”, Proc. Conf. Iranian Aerospace Society, Tehran, IRAN, 1386.##
Sadeghi, M. and Ebadollahi, S. “Error Modelling and Correction of INS System by GPS Signal Using MLP Neural Network”, Proc. 2nd Conf. Avionic, Tehran, IRAN, 1393.##
Bin, W., Jian, W., Jianping, W. and Baigen, C. “Study on Adaptive GPS/INS Integrated Navigation System”, Intelligent Transportation Systems, Vol. 2, pp. 1016-1021, 2003.##
Kaygisiz, B.H., Erkmen, A.M. and Erkmen, I. “GPS /INS Enhancement Using Neural Networks for Autonomous Ground Vehicle Applications”, International Conference on Intelligent Robots and Systems, Vol. 3, pp. 3763-3768, 2003.##
Hiliuta, A., Landry, R., and Gagnon, F. “Fuzzy Corrections in a GPS/INS Hybrid Navigation System”, IEEE Transactions on Aerospace and Electronic Systems, Vol. 40, No. 2, pp. 591-600, 2004.##
Sharaf, R. and Noureldin, A. “Sensor Integration for Satellite-Based Vehicular Navigation Using Neural Networks”, IEEE Transactions on Neural Networks, Vol. 18, No. 2, pp. 589-594, 2007.##
Chiang, K.W., and Huang, Y.W. “An Intelligent Navigator for Seamless INS/ GPS Integrated Land Vehicle Navigation Applications”, Applied Soft Computing, Vol. 8, No. 1, pp. 722-733, 2008.##
Bhatt, D., Aggarwal, P., Devabhaktuni, V. and Bhattacharya, P. “A Source Difference Artificial Neural Network for Enhanced Positioning Accuracy”, Measurment Science and Technology Journal, Vol. 23, No. 10, pp. 491-502, 2012.
Adusumilli, S., Bhatt, D. and Wong, H. “A Low-Cost INS/ GPS Integration Methodology Based on Random Forest Regression”, Expert System with Application, Vol. 40, No. 11, pp. 4653-4659, 2013.##
Bhatt, D., Aggarwal, P., Devabhaktuni, V. and Bhattacharya, P. “A Novel Hybrid Fusion Algorithm to Bridge the Period of GPS Outages Using Low Cost INS”, Expert System with Application, Vol. 41, No. 5, pp. 2166-2173, 2014.
Titterton, D.H. and Weston, J.L. “Strapdown Inertial Navigation Technology”, 2nd Edition, The Institution of Electrical Engineers, 2004.
Noureldin, A., Karamat, T.B. and Georgy, J. “Fundamentals of Inertial Navigation, Satellite-Based Positioning and Their Integration”, Springer, United States, 2013.
Wikipedia, “Great-circle Distance”, https://en.wikipedia.org/wiki/Great-circle_distance, last modified on 11 June 2015.
Simon, D. “Optimal State Estimation Kalman, H∞, and Nonlinear Approaches”, Wiley, New Jersey, United States, 2006.
mohammad hoseini, S., & seifi, M. (2019). Error Rate Reduction of a Low-Cost Integrated Navigation System Using Neural Networks. Aerospace Mechanics, 15(3), 17-32.
MLA
saeed mohammad hoseini; morteza seifi. "Error Rate Reduction of a Low-Cost Integrated Navigation System Using Neural Networks". Aerospace Mechanics, 15, 3, 2019, 17-32.
HARVARD
mohammad hoseini, S., seifi, M. (2019). 'Error Rate Reduction of a Low-Cost Integrated Navigation System Using Neural Networks', Aerospace Mechanics, 15(3), pp. 17-32.
VANCOUVER
mohammad hoseini, S., seifi, M. Error Rate Reduction of a Low-Cost Integrated Navigation System Using Neural Networks. Aerospace Mechanics, 2019; 15(3): 17-32.
)
