• Journal of Positioning, Navigation, and Timing
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• v.4 no.3
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• pp.141-150
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• 2015

In this study, a Global Navigation Satellite System (GNSS) / Inertial Navigation System (INS) / odometer / barometer integrated navigation system that uses a commercial navigation device including Micro Electro Mechanical Systems (MEMS) accelerometer and gyroscope in addition to GNSS, odometer information obtained from a vehicle, and a separate MEMS barometer sensor was implemented, and the performance was verified. In the case of GNSS and GNSS/INS integrated navigation system that are generally used in a navigation device, the performance would deteriorate in areas where GNSS signals are not available. Therefore, an integrated navigation system that calculates a better navigation solution in areas where GNSS signals are not available compared to general GNSS/INS by correcting the velocity error of GNSS/INS using an odometer and by correcting the cumulative altitude error of GNSS/INS using a barometer was suggested. To verify the performance of the navigation system, a commercial navigation device (Softman, Hyundai Mnsoft, http://www.hyundai-mnsoft.com) and a barometer sensor (ST Company) were installed at a vehicle, and an actual driving test was performed. To examine the performance of the algorithm, the navigation solutions of general GNSS/INS and the GNSS/INS/odometer/barometer integrated navigation system were compared in an area where GNSS signals are not available. As a result, a navigation solution that has a smaller position error than that of GNSS/INS could be obtained in the area where GNSS signals are not available.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.1
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• pp.93-102
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• 2024

Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS) integrated navigation systems provide highly accurate and reliable navigation solutions and are widely used as civil and military navigation systems. In order to facilitate the GNSS/INS integrated navigation system development task, a simulator can be used to provide inputs for the GNSS/INS integrated navigation system. In this paper, a simulator design using general-purpose Personal Computer (PC) and Off-The-Shelf (OTS) interface boards for a GNSS/INS integrated navigation system is proposed and implementation results are presented. Requirements of the GNSS/INS integrated navigation system simulator are presented and a design method that satisfies the requirements is described. In order to show the usefulness of the proposed design method, a simulator using a general-purpose PC and OTS interface boards for the GPS/INS integrated navigation system are implemented and verified. The implementation results show that the simulator designed by the proposed method generates the GPS L1 C/A signal and IMU data without any problems.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.2
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• pp.197-206
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• 2019

Safe aircraft requires highly reliable navigation information. The traditionally used inertial navigation system (INS) often displays faulty location information due to its innate errors. To overcome this, the INS/GNSS or INS/TRN integrated navigation can be used. However, GNSS is vulnerable to jamming and spoofing, while TRN can be degraded in the flat and repetitive terrains. In this paper, to improve the performance and ensure the high reliability of the navigation system, the INS/GNSS/TRN integrated navigation based on federated filter is designed. Master filter of the integrated navigation uses the estimates and covariances of two local filters - INS/GNSS and INS/TRN integrated filters. The local filters are designed with the EKF that is feedforward type and composed of the 17st state variables. And the INS/GNSS integrated navigation includes the barometer error compensation method. Finally, the proposed INS/GNSS/TRN integrated navigation is verified by vehicle and captive flight tests.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1349-1359
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• 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 Advanced Navigation Technology
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• v.22 no.3
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• pp.220-227
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• 2018

The most widely used method for constructing an inertial navigation system (INS)/global navigation satellite system (GNSS) coupling system is to construct an integrated navigation system using a Kalman filter. However, depending on the trajectory, non-observable state variables may be generated. In this case, the state variables are not estimated. To solve this problem, a integrated navigation system is constructed and then an observability analysis is performed. In this paper, a 24th order position-matched Kalman filter is defined to design an INS/GNSS integrated navigation system for vehicles moving with a large pitch angle change. To verify the appropriateness of the error state variables applied to the Kalman filter, an observability analysis was performed. The trajectory was divided into five segments, and the piece-wise constant system (PWCS) was assumed for each segment, and the results were analytically analyzed. The analytical results and the simulation results confirm that the error state parameters of the Kalman filter are well-designed to the estimation side.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.3
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• pp.199-208
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• 2022

Inertial Navigation System (INS)/Global Navigation Satellite System (GNSS) integrated navigation system can be used for land vehicle navigation. When the GNSS signal is blocked in a dense urban area or tunnel, however, the problem of increasing the error over time is unavoidable because navigation must be performed only with the INS. In this paper, Non-Holonomic Constraints (NHC) information is utilized to solve this problem. The NHC may correct some of the errors of the INS. However, it should be noted that NHC information is not applicable to all areas within the vehicle. In other words, the lever arm effect occurs according to the distance between the Inertial Measurement Unit (IMU) mounting position and the NHC effective point, which causes the NHC condition not to be satisfied at the IMU mounting position. In this paper, an INS/GNSS/NHC integrated navigation filter is designed, and this filter has a function to compensate for the lever arm effect. Therefore, NHC information can be safely used regardless of the vehicle's driving environment. The performance of the proposed technology is verified through Monte-Carlo simulation, and the performance is confirmed through experimental test.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.4
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• pp.279-286
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• 2022

In this paper, we designed a software library that produces integrated Global Navigation Satellite System (GNSS) / Inertial Navigation System (INS) navigation information using the raw measurements provided by the GNSS chipset, gyroscope, accelerometer and magnetometer embedded in android smartphone. Loosely coupled integration method was used to derive information of GNSS /INS integrated navigation. An application built in the designed library was developed and installed on the android smartphone. And we conducted field experiments. GNSS navigation messages were collected in the Radio Technical Commission for Maritime Service (RTCM 3.0) format by the Network Transport of RTCM via Internet Protocol (NTRIP). As a result of experiments, it was confirmed that design requirements were satisfied by deriving navigation such as three-dimensional position and speed, course over ground (COG), speed over ground (SOG), heading and protection level (PL) using the designed library. In addition, the results of this experiment are expected to be applicable to maritime navigation applications using smart device.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.4
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• pp.239-247
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• 2022

The existing studies on the localization in the GNSS (Global Navigation Satellite System) denied environment usually exploit low-cost MEMS IMU (Micro Electro Mechanical Systems Inertial Measurement Unit) sensors to replace the GNSS signals. However, the navigation system still requires GNSS signals for the normal environment. This paper presents an integrated GNSS/INS (Inertial Navigation System) navigation system which combines GNSS and multiple IMU sensors using extended Kalman filter in partially GNSS-denied environments. The position and velocity of the INS and GNSS are used as the inputs to the integrated navigation system. The Mahalanobis distance is used for novelty detection to detect the outlier of GNSS measurements. When the abnormality is detected in GNSS signals, GNSS data is excluded from the fusion process. The performance of the proposed method is evaluated using MATLAB/Simulink. The simulation results show that the proposed algorithm can achieve a higher degree of positioning accuracy in the partially GNSS-denied environment.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.121-125
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• 2006

A new GPS receiver correlator for the deeply-coupled GPS/INS integration system is proposed in order to the computation time problem of the Kalman filter. The proposed correlator consists of two early, prompt and late arm pairs. One pair is for detecting data bit transition boundary and another is for the correlator value calculation between input and replica signal. By detecting the data bit transition boundary, the measurement calculation time can be made longer than data bit period. As a result of this, the computational time problem of the integrated Kalman filter can be resolved. The validity of the proposed method is given through computer simulations.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.2
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• pp.119-126
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• 2022

This paper presents a method to reduce the vibration-induced noise effect of an inertial measurement device mounted on a self-driving vehicle. The inertial sensor used in the GNSS/INS integrated navigation system of a self-driving vehicle is fixed directly on the chassis of vehicle body so that its navigation output is affected by the vibration of the vehicle's engine, resulting in the degradation of the navigational performance. Therefore, these effects must be considered when mounting the inertial sensor. In order to solve this problem, this paper proposes to use an in-house manufactured vibration suppression device and analyzes its impact on reducing the vibration effect. Experimental test results in a static scenario show that the vibration-induced noise effect is more clearly observed in the lateral direction of the vehicle, but can be effectively suppressed by using the proposed vibration suppression device compared to the case without it. In addition, the dynamic positioning test scenario shows the position, speed, and posture errors are reduced to 74%, 67%, and 14% levels, respectively.