• The Journal of Korea Robotics Society
• /
• v.15 no.1
• /
• pp.24-31
• /
• 2020

Alternative navigation in underwater environments is essential to prevent accumulating drift error of dead reckoning. In case of using an external positioning system, the installation and management process of the transmission station is cumbersome, and the operation range of underwater vehicle is limited. In order to solve this problem, navigation using geophysical information such as terrain, geomagnetic field and gravity can be used. Unlike the terrain, geomagnetic field and gravity are composed of 3-D information, so continuation process is required. In this paper, we present a integrated navigation algorithm using multiple geophysical information for long-term operation of UUV. The proposed algorithm is verified through numerical simulation in an artificially generated environments. As a result, integrated navigation showed higher navigation accuracy than single alternative navigation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.34 no.4
• /
• pp.373-382
• /
• 2016

In this study, an EKF (Extended Kalman Filter) based database reference navigation using both gravity gradient and terrain data was performed to complement the weakness of using only one type of geophysical DB (Database). Furthermore, a new algorithm which combines the EKF and profile matching was developed to improve the stability and accuracy of the positioning. On the basis of simulations, it was found that the overall navigation performance was improved by the combination of geophysical DBs except the two trajectories in which the divergence of TRN (Terrain Referenced Navigation) occurred. To solve the divergence problem, the profile matching algorithm using the terrain data is combined with the EKF. The results show that all trajectories generate the stable performance with positioning error ranges between 14m to 23m although not all trajectories positioning accuracy is improved. The average positioning error from the combined algorithm for all nine trajectories is about 18 m. For further study, a development of a switching geophysical DB or algorithm between the EKF and the profile matching to improve the navigation performance is suggested.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.1
• /
• pp.72-78
• /
• 2007

Determination of the local vertical is not trivial for a moving vehicle and in general will require corrections for the Earth geophysical deflection. The vehicle's local vertical can be estimated by INS integration with initial alignment in SDINS(Strap Down INS) system. In general, the INS has drift error and it cause the performance degradation. In order to compensate the drift error, GPS/INS augmented system is widely used. And in the event that GPS is denied or unavailable, celestial navigation using star tracker can be a backup navigation system especially for the military purpose. In this celestial navigation system, the vehicle's position determination can be achieved using more than two star trackers, and the accuracy of position highly depends on accuracy of local vertical direction. Modern tilt sensors or accelerometers are sensitive to the direction of gravity to arc second(or better) precision. The local gravity provides the direction orthogonal to the geoid and, appropriately corrected, toward the center of the Earth. In this paper the relationship between direction of center of the Earth and actual gravity direction caused by geophysical deflection was analyzed by using precision orbit simulation program embedded the JGM-3 geoid model. And the result was verified and evaluated with mathematical gravity vector model derived from gravitational potential of the Earth. And also for application purpose, the performance variation of pure INS navigation system was analyzed by applying precise gravity model.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.8
• /
• pp.702-708
• /
• 2013

Underwater TRN (Underwater Terrain Referenced Navigation) estimates an underwater vehicle state by measuring a distance between the vehicle and undersea terrain, and comparing it with the known terrain database. TRN belongs to absolute navigation methods, which are used to compensate a drift error of dead reckoning measurements such as IMU (Inertial Measurement Unit) or DVL (Doppler Velocity Log). However, underwater TRN is different to other absolute methods such as USBL (Ultra-Short Baseline) and LBL (Long Baseline), because TRN is independent of the external environment. As a magnetic-field-based navigation, TRN is a kind of geophysical navigation. This paper develops an EKF (Extended Kalman Filter) formulation for underwater TRN. A filter propagation part is composed by an inertial navigation system, and a filter update is executed with echo-sounder measurement. For large-initial-error cases, an adaptive EKF approach is also presented, to keep the filter be stable. At the end, simulation studies are given to verify the performance of the proposed TRN filter. With simplified sensor and terrain database models, the simulation results show that the underwater TRN could support conventional underwater navigation methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.37 no.5
• /
• pp.367-377
• /
• 2019

As an alternative navigation system for the non-GNSS (Global Navigation Satellite System) environment, a new type of DBRN (DataBase Referenced Navigation) which applies both gravity gradient and terrain, and combines filter-based algorithm with profile matching was suggested. To improve the stability of the performance compared to the previous study, both centralized and decentralized EKF (Extended Kalman Filter) were constructed based on gravity gradient and terrain data, and one of filters was selected in a timely manner. Then, the final position of a moving vehicle was determined by combining a position from the filter with the one from a profile matching. In the simulation test, it was found that the overall performance was improved to the 19.957m by combining centralized and decentralized EKF compared to the centralized EKF that of 20.779m. Especially, the divergence of centralized EKF in two trajectories located in the plain area disappeared. In addition, the average horizontal error decreased to the 16.704m by re-determining the final position using both filter-based and profile matching solutions. Of course, not all trajectories generated improved performance but there is not a large difference in terms of their horizontal errors. Among nine trajectories, eights show smaller than 20m and only one has 21.654m error. Thus, it would be concluded that the endemic problem of performance inconsistency in the single geophysical DB or algorithm-based DBRN was resolved because the combination of geophysical data and algorithms determined the position with a consistent level of error.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.2
• /
• pp.131-139
• /
• 2013

In recent years alternative navigation system such as a DBRN (Data-Base Referenced Navigation) system using geophysical information is getting attention in the military navigation systems in advanced countries. Specifically TRN (Terrain Referenced Navigation) algorithm research is important because TRN system is a practical DBRN application in South Korea at present time. This paper presents an integrated navigation algorithm that combines a linear profile-based TRN and INS (Inertial Navigation System). We propose a correlation analysis method between TRN performance and terrain roughness index. Then we propose a conditional position update scheme that utilizes the position output of the conventional linear profile type TRN depending on the terrain roughness index. Performance of the proposed algorithm is verified through Monte Carlo computer simulations using the actual terrain database. The results show that the TRN/INS integrated algorithm, even when the initial INS error is present, overcomes the shortcomings of linear profile-based TRN and improves navigation performance.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.32 no.3
• /
• pp.271-279
• /
• 2014

As an alternative way to overcome the weakness of the global navigation satellite system (GNSS) in hostile situation, a gravity gradient referenced navigation (GGRN) has been developed. This paper analyzed the performance of GGRN with respect to the initial errors, DB resolution as well as update rates. On the basis of simulations, it was found that the performance of GGRN is getting worse when initial errors exist but the navigation results are rapidly converged. Also, GGRN generates better results when DB resolution is higher and update rates are shorter than 20 seconds. However, it is difficult to deduce the optimal parameters for the navigation because some trajectories show better performance in case low-resolution DB is applied or long update rate is supposed. Therefore, further analysis to derive specific update conditions to improve the performance has been performed. Those update conditions would not be generalized for all cases although maximum improvement rate is over 200% in certain case. In the future, some more developments and tests on the combination of various geophysical data and/or algorithms are necessary to construct more stable and reliable navigation system.

• Journal of Positioning, Navigation, and Timing
• /
• v.11 no.4
• /
• pp.305-316
• /
• 2022

Numerous research revealed a strong association between the ionospheric perturbations and various natural hazards. The ionospheric measurements from Global Navigation Satellite System (GNSS) observations provide the state of electron contents in the ionosphere that contributes to investigate the source events. In this study, two geophysical events occurred on 23 January 2018, the 7.9 Mw earthquake in Alaska and Kusatsu-Shiranesan volcanic eruption in Japan, are examined to characterize the fingerprint of each event in the ionosphere. Firstly, we extracted the Total Electron Content (TEC) from GNSS measurements, then isolated disturbed wave signatures from the TEC measurements that is referred to as a traveling ionospheric disturbance (TID). As TIDs are short-term ionospheric variations, the major trend of GNSS TEC measurements should be properly removed. We applied a natural neighbor interpolation method together with a leave-one-out cross validation technique for detrending. After detrending the TEC, the remaining signals are further enhanced by applying a band-pass filter and TIDs are detected from them. Finally, the detected TIDs are verified as the response of the ionosphere to Kusatsu-Shiranesan volcanic eruption and Gulf of Alaska earthquake which propagated through the ionosphere with an average velocity of 530 m/s and 724 m/s, respectively. In addition, a coherence analysis is conducted to discriminate between the signatures from a volcanic explosion and an earthquake. The analysis reveals the TID waveforms from each single event are highly correlated, while a low correlation is found between the TIDs from the earthquake and explosion. This study supports the claim that different geophysical events induce the distinctive characteristics of TIDs that are detectable by the ionospheric measurements of GNSS.

• Journal of Korean Port Research
• /
• v.12 no.1
• /
• pp.19-24
• /
• 1998

The purpose of this study is investigated to suggest the governmental policy and guideline required to establish the coastal zone management and development plan in the Pusan metropolitan city. The results are found as follows; first, a new definition of 'coastal zone' is introduced based on the geophysical characteristics in the city. Second, new policy-oriented guidelines are built on the basis of the coastal function from the viewpoint of the coastal zone management. Third, the coastal zone of the city is classified into 3sub-zone by the geophysical characteristics. Fourth, the comprehensive coastal zone management and development plan is suggested.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.33 no.6
• /
• pp.569-577
• /
• 2015

The navigation algorithm developed based on the extended Kalman filter (EKF) sometimes diverges when the linearity between the measurements and the states is not preserved. In this study, new update conditions together with two conditions from previous study for gravity gradient referenced navigation (GGRN) were deduced for the filter performance. Also, the effect of each update conditions was evaluated imposing the various magnitudes of the database (DB) and the sensor errors. In case the DB and the sensor errors were supposed to 0.1 Eo and 0.01 Eo, the navigation performance was improved in the eight trajectories by using part of gravity gradient components that independently estimate states located within trust boundary. When applying only the components showing larger variation, around 200% of improvement was found. Even the DB and sensor error were supposed to 3 Eo, six update conditions improved performance in at least seven trajectories. More than five trajectories generated better results with 5 Eo error of the DB and the sensor. Especially, two update conditions successfully control divergence, and bounded the navigation error to the 1/10 level. However, these update conditions could not be generalized for all trajectories so that it is recommended to apply update conditions at the stage of planning, or as an index of precision of GGRN when combine with various types of geophysical data and algorithm.