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This paper presents the hybrid database referenced navigation algorithm using terrain height and gravity anomaly information together. Geophysical information database can be used for navigation with inertial sensors on the GPS denied environment. Terrain height is the most commonly used as secondary navigation information with INS. However, the terrain referenced navigation is sometimes impossible to estimate the position because of the lack of uniqueness on the flat terrain. Therefore, we propose the hybrid database referenced navigation technique which utilizes a gravity anomaly information along with terrain height. In this paper, the point mass filter is used for estimation of the vehicle's position. And weighting logic for hybrid database referenced navigation is designed based on the kurtosis of posteriori pdf (probability density function) because that of posteriori pdf has a proportional relationship to the estimation accuracy. Each estimation result is mixed together according to the kurtosis. As a result, it is shown by the numerical simulation that the proposed method has a better performance than the navigation result obtained from individual database.

A time domain signal tracking algorithm is proposed to estimate the frequency of a chirp type global navigation satellite system (GNSS) interference. The unknown interference frequency of GNSS is estimated by the received signal using properties of trigonometrical functions, but this value has a lot of error caused by measurement noise and the frequency change of the interference. In order to reduce the ierror, an adaptive fading Kalman filter is applied to the proposed algorithm. Furthermore, a low pass differentiator (LPD) and a pattern enhancement algorithm are used to estimate the sweep period of chirp type interference. The performance of the tracking algorithm is verified by comparing to conventional algorithms. By analyzing the results of comparisons, the proposed algorithm has better tracking performance than conventional algorithms when the jammer to signal ratio (J/S) of GNSS interference signal is more than 30dB, which seriously affects the accuracy of the GNSS.

Precise control of UAV (Unmanned Aerial Vehicle) or MAV (Micro Aerial Vehicle), requires the accurate determination of vehicle orientation. Attitude and heading reference systems (AHRS) are popularly used for vehicle orientation determination. In these systems, Euler angle estimation is more appropriate than quaternion estimation because the accelerometer measurement and magnetometer measurement are separated. Furthermore, the accelerometer and magnetometer measurements have independent effects on the tilt and heading angles. An Euler based attitude estimation system that uses two-stage extended Kalman filtering is proposed. To avoid singularity of Euler angle, a new heading estimation parameter is introduced and a filter mode switching algorithm is proposed. The experimental results indicated that the proposed system performed better than a quaternion algorithm based on magnetometer disturbance. Furthermore, the results indicated that the proposed algorithm was immune to the singularity problem.

The simulator development for fault detection and isolation (FDI) of a LEO satellite is presented. The simulator was constructed using satellite dynamics, FDI, sensors and actuators, flight software and a visualization block. Two FDI algorithms were applied. The first was an outlier detection method. The outlier detection method was based on the Kalman filter incorporating thresholds, data windows and average methods. This filter detected, isolated and recovered sudden abnormal data. The second FDI algorithm was a parity space approach for the gyro sensor FDI. The simulator was developed under the Matlab/Simulink environment. The results indicated that the simulator can be used for any LEO satellite.

In the inertial navigation system, the altitude error diverges exponentially if external sensors do not compensate it. To suppress divergence of the error, non-inertial aiding sensors that provide vertical information are utilized. With these sensors, the wellknown baro-inertial damping loop or the well-known Kalman filter mechanization can be constituted to compensate the error of the vertical channel. In this paper, a new error compensation scheme for INS vertical channel is proposed, especially with a barometer and GPS by fusing the two well established methods. The performance of the proposed scheme is analyzed by computer simulation.

This paper presents a new fault detection and isolation method which is called EPSA(Extended Parity Space Approach). This method is particularly suitable for fault detection and isolation of the system with two faulty sensors. To analyze the situations of two-faults, the situations are classified into four types. Based on this analysis, the procedure to isolate the faulty sensors in each situation is suggested. Also how to decide the threshold value is suggested. The proposed FDI method is verified through Monte Carlo simulation.

In this paper, fault detection and isolation algorithm for inertial sensor system is proposed. To identify the inertial sensor fault, single antenna GPS receiver is used as an effective redundancy source. To use GPS receiver as redundancy for the inertial sensors, the algorithm to estimate the attitude and acceleration using single antenna GPS receiver is adopted. Using Doppler shift of carrier phase signal and kinetic characteristics of aircraft, attitude information of aircraft can be obtained through one GPS antenna at the coordinated flight condition. Based on this idea, fault diagnosis algorithm for inertial sensors using single antenna GPS based attitude is proposed. For more effective FDI, decision variable considering aircraft maneuver is considered. The effectiveness of the proposed algorithm is verified through the numerical simulations for the various cases.