چكيده به لاتين
The integration of two GPS global positioning systems and the INS inertial navigation system is one of the practical methods for more accurate, robust and continuous navigation than any of the systems alone. This dissertation aims to improve the accuracy of the integrated GPS/INS system with the low-cost INS sensors with MEMS technology to achieve an accurate and low-cost positioning solution even at long-term GPS outages. Challenging conditions in this study are low-cost inertial sensors, vehicle speeds of 120 km / h, a high percentage of random noise due to real data, system real-time, and several long-term GPS interruptions during the flight process. Since the positioning error of the integrated system depends on the quality of the inertial sensors, the length of the GPS outage, the speed of the flight test and the effectiveness of the algorithm used to predict the positioning error, two approaches have been designed and used in this study. Initially, to reduce the destructive effect of high uncertainties and noise in the raw measurements of low-cost inertial sensors in the integrated navigation system and as a result of better training of the intelligent system, new algorithms with unique features are introduced as preprocessing steps. Then, in the first approach, at GPS outages, artificial intelligence (AI)-based algorithms are designed to predict INS error, which is highly efficient in modeling the complex uncertainties of existing conditions. In these algorithms, a compromise between speed and accuracy is considered to be suitable for real-time applications. In the second approach, a step has been taken and in both GPS outages and the presence of GPS signals, the accuracy and performance of the integrated system have been improved. Thus, in the presence of GPS, by designing a new Indirect Centralized Correntropy Kalman filter, optimized by using AI-based methods, in addition to eliminating the shortcomings of Kalman filtering methods, it has added unique features to the integrated system. It also provides continuous and accurate navigation in the GPS blockages with the design of appropriate intelligent algorithms. High performance and accuracy, especially against non-Gaussian GPS measurement noises, dynamic maneuvers of the in-flight vehicle, noises of inertial sensors and long-term GPS blockages are among the distinctive features of the proposed algorithm. The proposed algorithms have succeeded in improving the results by at least 20% compared to the latest achievements in this field.
