• Journal of Positioning, Navigation, and Timing
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• v.10 no.3
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• pp.179-187
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• 2021

To estimate the location of the train, we consider an integrated navigation system that combines Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS). This system provides accurate navigation results in open sky by combining only the advantages of both systems. However, since measurement update cannot be performed in GNSS signal blocked areas such as tunnels, mountain, and urban areas, pure INS is used. The error of navigation information increases in this area. In order to reduce this problem, the train's Non-Holonomic Constraints (NHC) information can be used. Therefore, we deal with the INS/GNSS/NHC integrated navigation system in this paper. However, in the process of installing the navigation system on the train, a Mounting Misalignment Error of the IMU (MMEI) inevitably occurs. In this case, if the NHC is used without correcting the error, the navigation error becomes even larger. To solve this problem, a method of easily estimating the MMEI without an external device is introduced. The navigation filter is designed using the Extended Kalman Filter (EKF) by considering the MMEI. It is assumed that there is no vertical misalignment error, so only the horizontal misalignment error is considered. The performance of the integrated navigation system according to the presence or absence of the MMEI and the estimation performance of the MMEI according to the method of using NHC information are analyzed based on simulation. As a result, it is confirmed that the MMEI is accurately estimated by using the NHC information together with the GNSS information, and the performance and reliability of the integrated navigation system are improved.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.491-494
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• 2006

Kalman filtering (KF) is hard to be applied to the SINS (Strap-down Inertial Navigation System)/RDSS (Radio Determination Satellite Service) integrated navigation system directly because the time delay of RDSS positioning in active mode is random. BP (Back-Propagation) Neuron computing as a powerful technology of Artificial Neural Network (ANN), is appropriate to solve nonlinear problems such as the random time delay of RDSS without prior knowledge about the mathematical process involved. The new algorithm betakes a BP neural network (BPNN) and velocity feedback to aid KF in order to overcome the time delay of RDSS positioning. Once the BP neural network was trained and converged, the new approach will work well for SINS/RDSS integrated navigation. Dynamic vehicle experiments were performed to evaluate the performance of the system. The experiment results demonstrate that the horizontal positioning accuracy of the new approach is 40.62 m (1 ${\sigma}$), which is better than velocity-feedback-based KF. The experimental results also show that the horizontal positioning error of the navigation system is almost linear to the positioning interval of RDSS within 5 minutes. The approach and its anti-jamming analysis will be helpful to the applications of SINS/RDSS integrated systems.

• 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.

• Journal of Ocean Engineering and Technology
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• v.28 no.6
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• pp.566-573
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• 2014

This paper presents the results of an integrated navigation performance analysis for selecting the sensor of an unmanned underwater vehicle (UUV) using Monte Carlo numerical simulation. An inertial measurement unit (IMU) and Doppler velocity log (DVL) are considered to build the integrated navigation system. The position error and price of the sensor are selected as performance indices to evaluate the volunteer integrated navigation systems. Monte-Carlo simulation is introduced to analyze the circular error probability (CEP) and its variance. Simulation results provide the proper sensor combination for integrated navigation in relation to the performance and price.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.241-245
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• 2005

Strapdown inertial navigation system (SINS) integrated with astronavigation system (ANS) yields reliable mission capability and enhanced navigational accuracy for spacecrafts. The theory and characteristics of integrated system based on unscented Kalman filtering is investigated in this paper. This Kalman filter structure uses unscented transform to approximate the result of applying a specified nonlinear transformation to a given mean and covariance estimate. The filter implementation subsumed here is in a direct feedback mode. Axes misalignment angles of the SINS are observation to the filter. A simple approach for simulation of axes misalignment using stars observation is presented. The SINS error model required for the filtering algorithm is derived in space-stabilized mechanization. Simulation results of the integrated navigation system using a medium accuracy SINS demonstrates the validity of this method on improving the navigation system accuracy with the estimation and compensation for gyros drift, and the position and velocity errors that occur due to the axes misalignments.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.3
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• pp.165-173
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• 2018

Underwater vehicles use Inertial Navigation System (INS) with high-performance Inertial Measurement Unit (IMU) for high precision navigation. However, when underwater navigation is performed for a long time, the INS error gradually diverges, therefore, an integrated navigation method using auxiliary sensors is used to solve this problem. In terms of underwater vehicles, the vertical axis error is primarily compensated through Vertical Channel Damping (VCD) using a depth gauge, and an integrated navigation filter can be designed to perform horizontal axis error and sensor error correction using a speedometer such as Electromagnetic-Log (EM-Log). However, since EM-Log outputs the forward direction relative speed of the vehicle with respect to the sea and sea current, INS correction filter using this may cause a rather large error. Although it is possible to design proper filters if the exact model of the sea current is known, it is impossible to know the accurate model in reality. Therefore, this study proposes an INS/EM-Log integrated navigation filter with the function to estimate sea current using an Interacting Multiple Model (IMM) filters, and the performance of this filter is analyzed through a simulation performed in various environments.

• Journal of Positioning, Navigation, and Timing
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• v.3 no.2
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• pp.53-62
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• 2014

In the guided missile and unmanned vehicle system, the navigation system is one of the most important components. Recently, low-cost effective smart projectiles and guided bomb are being developed using MEMS based navigation system which has high-G, low-cost and small size. In this paper, locally developed MEMS based GPS/INS integrated navigation system will be introduced in comparison with the state of the art of MEMS based navigation system. And technical design and development method is described to satisfy the required performance of GPS receiver, MEMS inertial sensor assembly, navigation computer and software.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.3
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• pp.242-250
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• 2003

We propose the monitoring system scheme for the CPS/INS integrated navigation system. The design requirements of the monitoring system are suggested and the software scheme based on GUI is proposed. The proposed monitoring system consists of an I/O interface part, a navigation data display part, and a post-processing part. The I/O interface part is responsible for data communication between the monitoring system and a navigation computer unit. The navigation data display part provides various display methods to show the navigation data to user in real-time. The post-processing part collects the navigation data to analyze the performance of navigation system. The proposed monitoring system software was developed using the Visual C++ programming language and a van test was carried out to demonstrate the real-time operation of the monitoring system. The test result shows that the proposed monitoring system can be effectively applied to the CPS/INS integrated navigation system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.7
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• pp.592-601
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• 2018

The GPS/INS integrated navigation system, which is one of the electronic equipments mounted on military aircraft store, can not directly receive GPS signals by the aircraft wing before the drop, so GPS navigation data is received from the aircraft and used for filter integration, afterwards, the integrated navigation is performed using the GPS information directly received through the antenna. In this case, it is possible to operate the mount in old aircraft without any modification of the aircraft when GPS data is transmitted using wireless. However, the delay occurs while the aircraft navigation data is transmitted to the integrated navigation filter of the aircraft store via wireless, which affects the time synchronization of the GPS measurement and the INS information, affecting the integrated navigation performance. In this paper, an algorithm to analyze and compensate the effect of generation and transmission delay that can occur when implementing GPS/INS integrated navigation system of aircraft store that receives GPS data via wireless.

• 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.