• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.7
• /
• pp.633-643
• /
• 2005

An unmanned aerial vehicle (UAV) is an aircraft controlled by .emote commands from ground station and/o. pre-programmed onboard autopilot system. A navigation system in the UAV provides a navigation data for a flight control computer(FCC). The FCC requires accurate and reliable position, velocity and attitude information for guidance and control. This paper proposes an ADGPS/INS integrated navigation system for a UAV. The proposed navigation system comprises an attitude determination GPS (ADGPS) receive., a navigation computer unit, and a low-cost commercial MEMS inertial measurement unit(IMU). The navigation algorithm contains a fault detection and isolation (FDI) function fur integrity. In order to evaluate the performance of the proposed navigation system, two flight tests were preformed using a small aircraft. The first flight test was carried out to confirm fundamental operation of the proposed navigation system and to check the effectiveness of the FDI algorithm. In the second flight test, the navigation performance and the benefit of the GPS attitude information were checked in a high dynamic environment. The flight test results show that the proposed ADGPS/INS integrated navigation system gives a reliable performance even when anomalous GPS data is provided and better navigation performance than a conventional GPS/INS integration unit.

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.1984-1986
• /
• 2001

In order to provided continuous solutions, latest developing navigation systems tend to integrate GPS receiver with INS or DR. Using the GPS carrier-phase measurements, an attitude GPS receiver with three antennas obtain the 3-dimensional attitude such as roll, pitch, and heading as well as position and velocity. With these angle measurements, in the attitude GPS/INS integrated system, attitude or gyro errors can be directly compensated. In this paper, we develop an integrated navigation system that combines attitude GPS receiver with INS. The performance of real-time integrated navigation system is determined by not only the implements of integration filter but also the synchronization of measurements. To meet these real-time requirements, the navigation software is implemented in multi-tasking structure in this paper. We also employ time-synchronization technique in the multi-sensor fusion. Experimental results show that the performance of the attitude GPS/INS integrated system is consistent even when cycle-slip occurs in carrier-phase measurements.

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2075-2077
• /
• 2001

For precise positioning, GPS carrier measurements are often used. In this case, accurate position having mm${\sim}$cm error can be obtained. For 3D positioning, in CDGPS, more than five carrier phase measurements are required. When GPS signals are blocked or carrier phase measurements are insufficient, it cannot provide positioning solution. By integrating CDGPS with INS, continuity of positioning solution can be guaranteed. However, when a vehicle moves in low speed or in stationary, the CDGPS/INS integrated system is difficult to compensate INS attitude errors because GPS velocity error become relatively lange. In this paper, we used the 3D attitude GPS receiver to compensate the INS attitude error. By field experiments, it is shown that the proposed integration system maintains the navigation performance even when a vehicle is in low speed or GPS signal is blocked for a period of time.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.2
• /
• pp.133-139
• /
• 2007

An unmanned ground vehicle can perform its mission automatically without human control in unknown environment. To move up to a destination in various surrounding situation, navigational information is indispensible. In order to be adopted for an unmanned vehicle, the navigation box is small, light weight and low power consumption. This paper suggests navigation system using a low grade MEMS IMU for supplying position, velocity, and attitude of an unmanned ground vehicle. This system consists of low cost and light weight MEMS sensors and a GPS receiver to meet unmanned vehicle requirements. The sensors are basically integrated by loosely coupled method using Kalman filter and internal algorithms are divided into initial alignment, sensor error compensation, and complex navigation algorithm. The performance of the designed navigation system has been analyzed by real time field test and compared to commercial tactical grade GPS/INS system.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.2433-2435
• /
• 2000

Inertial Navigation System(INS) provides short-term accurate navigation solution but its error grows with time due to integration characteristics. Meanwhile, Global Positioning System(GPS) provides long-term stable solution but it has poor error characteristics in high dynamic region. So for its synergistic relationship, an integrated INS/GPS systems has been widely used as an advanced navigation system. Generally, two kinds of integration method are used. One is loosely coupled mode which uses GPS-derived position and velocity as measurements in an integrated Kalman filter. The other is tightly coupled one which uses pseudorange and pseudorange rate as Kalman filter measurements. In this paper the system error models and observation models for two kinds of integrated systems are derived, respectively, and their performance are compared through Monte-Carlo simulations.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• v.1
• /
• pp.133-138
• /
• 2006

Singular value decomposition (SDV) approach is applied to the observability analysis of GPS/INS in this paper. A measure of observability for a subspace is introduced. It indicates the minimum size of perturbation in the information matrix that makes the subspace unobservable. It is shown that the measure has direct connections with observability of systems, error covariance, and singular structure of the information matrix. The observability measure given in this paper is applicable to the multi-input/multi-output time-varying systems. An example on the observability analysis of GPS/INS is given. The measure of observability is confirmed to be less sensitive to system model perturbation. It is also shown that the estimation error for the vertical component of gyro bias can be considered unobservable for small initial error covariance for a constant velocity horizontal motion.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.1706-1709
• /
• 2003

This paper demonstrates a unique method for measuring vehicle states such as body sideslip angle and tire sideslip angle using Global Positioning System(GPS) velocity information in conjunction with other sensors. A method for integrating Inertial Navigation System (INS) sensors with GPS measurements to provide higher update rate estimates of the vehicle states is presented, and the method can be used to estimate the tire cornering stiffness. The experimental results for the GPS velocity-based sideslip angle measurement. From the experimental results, it can be concluded that the proposed method has an advantage for future implementation in a vehicle safety system.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_3
• /
• pp.1349-1359
• /
• 2021

Acquisition of precise position and velocity information of GNSS-INS (Global Navigation Satellite System; Inertial Navigation System) sensors in obtaining SAR SLC (Single Look Complex) images from raw data using BPA (Backprojection Algorithm) was regarded decisive. Several studies on BPA were accompanied by Kalman Filter for sensor noise oppression, but often implemented once where insufficient information was given to determine whether the filtering was effectively applied. Multiple operation of Kalman Filter on GNSS-INS sensor was presented in order to assess the effective order of sensor noise calibration. FMCW (Frequency Modulated Continuous Wave)-SAR raw data was collected from twice airborne experiments whose GNSS-INS information was practically and repeatedly filtered via Kalman Filter. It was driven that the FMCW-SAR raw data with diverse path information could derive different order of Kalman Filter with optimum operation of BPA image restoration.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.49 no.3
• /
• pp.12-18
• /
• 2012

This paper presents a computation method of LOS(Line Of Sight) angle using IMU(Inertial Measurement Unit) for an antenna on aerial vehicle to point to a stationary satellite. In the overall system, the antenna is located at the front of the vehicle, and an IMU is introduced to account for body flexure dynamic. And using the differences between the position and velocity of the IMU based navigation and those of GPS/INS at the vehicle center. Kalman filter is designed to suppress Strapdown INS drift errors.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.26 no.3
• /
• pp.214-226
• /
• 2023

A transfer alignment is used to initialize, align, and calibrate a SINS(Slave INS) using a MINS(Master INS) in motion. This paper presents an airborne transfer alignment with velocity and azimuth matching to estimate inertial sensor biases under the wing flexure influence. This study also considers the lever arm, time delay and relative orientation between MINS and SINS. The traditional transfer alignment only uses velocity matching. In contrast, this paper utilizes the azimuth matching to prevent divergence of the azimuth when the aircraft is stationary or quasi-stationary since the azimuth is less affected by the wing flexibility. The performance of the proposed Kalman filter is analyzed using two factors; one is the estimation performance of gyroscope and accelerometer bias and the other is comparing aircraft dynamics and attitude covariance. The performance of the proposed filter is verified using a long term flight test. The test results show that the proposed scheme can be effectively applied to various platforms that require airborne transfer alignment.