This paper presents the integration of inertial navigation system (INS) with electromagnetic-log (EM-log) as an underwater navigation system using H-infinity filter for robustness from the uncertainty of the sea current model. In underwater environments, the electromagnetic signals are attenuated rapidly, so that the global navigation satellite system is not available in general. Thus, INS is usually chosen for underwater navigation, and other aiding sensors are also used to complement its accumulative errors, one of which is EM-log. Since an EM-log provides the relative velocity to seawater, the integrated navigation cannot be performed accurately unless the sea current speed is compensated properly. Generally, the INS and EM-log can be integrated using extended Kalman filter (EKF). However, EKF guarantees its performance when the stochastic properties of the system’s process and measurement noises are perfectly known. In other words, in the presence of sea current modelling errors, the integration using the EKF is not expected to show good performance. On the other hand, H-infinity filter is a robust filter which can tolerate such uncertainties. In this paper, the integration of INS and EM-log using H-infinity filter is studied. The performance is compared with that of the EKF case by proper computer simulation.
An approach to improve the performance of SDINS and GPS integrated system for bank-to-turn flight vehicles is described. Then, it is shown through the simulation that a specific gyro misalignment error results in an increased heading error of SDINS. A new modelling method is presented herein for identifying of sensor and attitude error.The main advantage of the proposed method is that it not only estimates the gyro misalignment error of SDINS, but also improves estimate performance of heading error of SDINS in the presence of the gyro misalignments.
LINS (Laser Inertial Navigation System) consists of RLG (Ring Laser Gyroscopes)/accelerometers and provides real-time navigation information to the target system. Therefore it is very important to make a decision in the real time whether LINS is in the normal operation or not. That is called a fault detection method. In this paper, we propose the fault detection method of LINS based on the overlapping model. We also show that the fault detection probability is increased through overlapping the hardware model and the software model. It is verified through the long-term operation and RAM (Reliability Availability Maintainability) analysis of LINS that the fault detection method proposed in this paper is able to detect about 97% of probable system failures.
This paper addresses the performance comparisons of the GPS pseudorange and pseudorange rate measurements in the tightly coupled INS/GPS Navigation systems. Even though the two measurements have the same ability in estimating level attitude errors, pseudorange rate has an advantage in improving estimating heading attitude error performance. The performance of pseudorange and pseudorange rate measurements is compared in numerical simulations and van test.
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