• Journal of Advanced Navigation Technology
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• v.23 no.3
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• pp.221-227
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• 2019

In this paper, interacting multiple model (IMM) filter was designed that guarantees a stable navigation performance even in the unstable satellite navigation position. In order to design IMM filter in INS / GPS integrated navigation system, sub filter of the IMM filter is defined as Kalman filter. In the IMM filter configuration, two subfilters are determined. Each Kalman filter defines the six-teenth state composed of position, velocity, attitude, and sensor error from the INS error equation and the states additionally derived in case of the coloured measurement noise. In order to verify the performance of the proposed filter, we compared the performance how the filter works in the presence of arbitrary error in GPS navigation solution. The Monte Carlo simulation was performed 100 times and the results were compared with the root mean square(RMS). The results show that the proposed method is stable against errors and show fast convergence.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.499-506
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• 2015

Global navigation satellite systems (GNSS) is operating widely in civil and military area. GNSS signals, however, can be easily interfered because its signal is vulnerable to jamming. Thus, a sort of backup or alternative system is needed in order that the navigation performance is assured to a certain degree in case of GNSS jamming. In order to suggest a series of backup or alternative system of regional navigation, in this paper, we introduced a high altitude long endurance unmanned aerial vehicle (HALE UAV) with pseudolites using inverted GPS and transceiver system. We simulated the positioning error of the regional navigation system using HALE UAV with inverted GPS or transceivers concepts. We estimated the position error of HALE UAV calculate user position errors based on the position error of HALE UAV and general pseudorange error.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.984-989
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• 2003

The integrated global position system (GPS) and inertial navigation system (INS) has been considered as a cost-effective way of providing an accurate and reliable navigation system for civil and military system. Even the integration of a navigation sensor as a supporting device requires the development of non-traditional approaches and algorithms. The objective of this paper is to assess the feasibility of integrated with GPS and INS information, to provide the navigation capability for long term accuracy of the integrated system. Advanced algorithms are used to integrate the GPS and INS sensor data. That is fuzzy inference system based Weighted Extended Kalman Filter(FWEKF) algorithm INS signal corrections to provided an accurate navigation system of the integrated GPS and INS. Repeatedly, these include INS error, calculated platform corrections using GPS outputs, velocity corrections, position correction and error model estimation for prediction. Therefore, the paper introduces the newly developed technology which is aimed at achieving high accuracy results with integrated system. Finally, in this paper are given the results of simulation tests of the integrated system and the results show very good performance

• Journal of Positioning, Navigation, and Timing
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• v.9 no.2
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• pp.117-124
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• 2020

In this paper, the symmetric position drift of the integration approach in pedestrian dead reckoning (PDR) system with dual foot-mounted IMU is analyzed. The PDR system that uses the inertial sensor attached to the shoe is called the IA-based PDR system. Since this system is designed based on the inertial navigation system (INS), it has the same characteristics as the error of the INS, then zero-velocity update (ZUPT) is used to correct this error. However, an error that cannot be compensated perfectly by ZUPT exists, and the trend of the position error is the symmetric direction along the side of the shoe(left, right foot) with the IMU attached. The symmetric position error along the side of the shoe gradually increases with walking. In this paper, we analyze the causes of symmetric position drift and show the results. It suggests the possibility of factors other than the error factors that are generally considered in the PDR system based on the integration approach.

• Journal of Positioning, Navigation, and Timing
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• v.3 no.2
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• pp.71-81
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• 2014

Time synchronization system using dual frequency bands is designed and the error sources are analyzed for alternative synchronized-pseudolite navigation system (S-PNS) which aims at military application. To resolve near/far problem, dual frequency band operation is proposed instead of pulsing transmission which degrades level of reception. In dual frequency operation H/W delay should be considered to eliminate errors caused by inter-frequency bias (IFB) difference between the receivers of the pseudolites and users. When time synchronization is performed across the sea, multipath error is occurred severely since the elevation angle between pseudolites is low so total reflection can be happened. To investigate the difference of multipath effects according to location, pseudolites are set up coastal area and land area and performances are compared. The error source related with tropospheric delay is becoming dominant source as the coverage of the PNS is broadening. The tropospheric delay is measured by master pseudolite receiver directly using own pseudorange and slave pseudorange. Flight test is performed near coastal area using S-PNS equipped with developed time synchronization system and test results are also presented.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.584-591
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• 2014

This paper presents a novel aided navigation method for AUV (Autonomous Underwater Vehicles). The navigation system for AUV includes several sensors such as IMU (Inertial Measurement Unit), DVL (Doppler Velocity Log) and depth sensor. In general, the $13^{th}$ order INS error model, which includes depth error, velocity error, attitude error, and the accelerometer and gyroscope biases as state variables is used with measurements from DVL and depth sensors. However, the model may degrade the estimation performance of the heading state. Therefore, the $11^{th}$ INS error model is proposed. Its validity is verified by using a degree of observability and analyzing steady state error. The performance of the proposed model is shown by the computer simulation. The results show that the performance of the reduced $11^{th}$ order error model is better than that of the conventional $13^{th}$ order error model.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.114.5-114
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• 2001

In this paper, the model for personal navigation system using low-cost inertial sensors and error compensation method with GPS are proposed. Simulation is accomplished for the performance test. WNS(Walking Navigation System) is a kind of personal navigation using the number of a walk, stride and azimuth. Because the accuracy of these variables determines the navigational performance, computational methods have been investigated. The step is detected using the motion pattern by walking motion, stride is determined by neural network and azimuth is calculated with gyro´s output. The neural network filters off unnecessary motions. However, error compensation method is needed, because the error of navigation information increases with time ...

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.4
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• pp.116-123
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• 2008

In this paper we study the performance of the measurement time-delay estimation of tightly-coupled GPS/INS(Global positioning system/Inertial Navigation system) system. Generally, the heading error estimation performance of loosely-coupled GPS/INS system using GPS's Navigation Solution is poor. In the case of tightly-coupled GPS/INS system using pseudo-range and pseudo-range rate, the heading error estimation performance is better. However, the time-delay error on the measurement(pseudo-range rate) make the heading error estimation performance degraded. So that, we propose the time-delay model on the measurement and compose the time-delay estimator. And we confirm that the heading error estimation performance in the case of measurement time-delay existence is similar with the case of no-delay by Monte-Carlo simulation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.2
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• pp.171-178
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• 2008

Galileo is the Europe's global navigation satellite system corresponding to the GPS. The GIOVE-A test experiment has been finished and the second test satellite GIOVE-B will be launched soon. The integration of GPS and Galileo lead an increase of visible satellite number. We can obtain an improved navigation performance in signal blocked area such as urban or forest. GPS and Galileo have each time-coordinate system and use the different error model to calculate the navigation solution. In this paper, we studied on GPS and Galileo channel error model and time-coordinate system. Using this result, we implement the integrated navigation algorithm. In simulation, we analyzed the navigation error caused by time and coordinate disagreement and verified performance of integrated navigation algorithm in terms of visible satellite number, DOP(Dilution of Pression) and position error.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.1
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• pp.35-44
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• 2022

In this paper, a dual foot (DF)-PDR system is proposed for the fusion of integration (IA)-based PDR systems independently applied on both shoes. The horizontal positions of the two shoes estimated from each PDR system are fused based on a particle filter. The proposed method bounds the position error even if the walking time increases without an additional sensor. The distribution of particles is a non-Gaussian distribution to express the lateral error due to systematic drift. Assuming that the shoe position is the pedestrian position, the multi-modal position distribution can be fused into one using the Gaussian sum. The fused pedestrian position is used as a measurement of each particle filter so that the position error is corrected. As a result, experimental results show that position of pedestrians can be effectively estimated by using only the inertial sensors attached to both shoes.