In this paper, a calibration method for gyro bias that changes depending on the position of the IMU (inertial measurement unit) is proposed to improve the navigation performance of RLG-based RINS (ring-laser-gyro-based rotational inertial navigation system). RINS is a navigation device that compensates for the inertial sensor errors by utilizing the rotation of the IMU. In previous studies, the rotation scheme of the IMU is designed assuming that inertial sensor errors are not affected by position of the IMU. However, changes in temperature distribution, direction of gravity, and dithering according to the rotation of the IMU affect the inertial sensor errors, such as gyro bias. These errors could degrade the long-term navigation performance of RLG-based RINS. To deal with this problem, this paper proposed a compensation method of the gyro bias that changes depending on the position of the IMU. First, RINS is reviewed using a dual-axis 16-position rotation scheme and RLG. Next, the attitude error of RLG-based RINS is derived utilizing navigation equations. The effect of the gyro bias change caused by the change in the IMU attitude for the navigation performance of RINS is analyzed based on navigation equations and simulations. Finally, system-level indirect calibrations for the Z–axis up position and Z–axis down position are performed to calculate the gyro bias change caused by the IMU attitude. The accuracy of the proposed calibration method is verified by long-term navigation test. The test results show that the proposed calibration method improves the navigation performance of RINS compared with the conventional calibration method.
A High-degree Cubature Kalman Filter (CKF) is proposed to deal with the Strapdown Inertial Navigation System (SDINS) alignment problem. In-flight Alignment (IFA) is an effective method to compensate for attitude errors of the navigation system. While providing precise attitude error compensation, however, the external source aided alignment often creates a nonlinear filtering problem caused by a large misalignment angle. Introduced recently, Cubature Kalman Filter is a suitable technique for various nonlinear problems. In this paper, a higher degree CKF is applied to this accuracy-is-everything SDINS IFA problem. The simulation results show that the proposed technique outperformed a traditional nonlinear filter in terms of precision and alignment time.
This paper addresses the problem of the software update or upgrade of embedded equipments on a missile assembly with booster. Because the embedded equipments are assembled delicately and closely one another with various communication and power cables, they should be very carefully disassembled to directly upgrade the software of a certain embedded equipment. This may cause not only the costs for disassembly and reassembly but also additional tests to verify the completeness of the reassembled missile as a missile assembly with booster. This paper presents an indirect data transfer technique based on MIL-STD-1553B through Guidance Control Unit to easily upgrade the software of other equipments without any additional costs caused by disassembly and reassembly. The presented technique was successfully applied to the software upgrade of various equipments on real missile assembly with booster.
In guided missile systems, reducing terminal-position error is the primary objective of the inertial navigation system. As a seeker is used to sense and track a target, the critical function of the inertial navigation system is to provide the seeker with accurate missile attitude information and help the seeker to keep tracking a target continuously. As inertial sensor body and missile body alignment errors are taken into account, it is desirable to minimize the alignment errors between the missile seeker and the attitude of inertial navigation system. Among the alignment errors, this paper addresses the methods of measuring and compensating misalignment between inertial sensor body and housing frame and shows test results of several experiments.
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