Publications

@conference{Chang2020b,

title = {Effects of CICERO Receiver Characteristics on the Quality of Radio Occultation Data},

author = {Hyeyeon Chang and Jiyun Lee and Yang Wang and Brian Breitsch and Y. Jade Morton},

year  = {2020},

date = {2020-12-01},

booktitle = {AGU Fall Meeting 2020},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Chang2020,

title = {Preliminary Assessment of CICERO Radio Occultation Performance by Comparing with COSMIC I Data},

author = {Hyeyeon Chang and Jiyun Lee and Yang Wang and Brian Breitsch and Y. Jade Morton},

doi = {10.33012/2020.17754},

year  = {2020},

date = {2020-09-21},

booktitle = {Proceedings of the 33rd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2020)},

pages = {3888-3900},

abstract = {Community Initiative for Cellular Earth Remote Observation (CICERO) is a planned constellation of low-earth-orbiting 6U cubeSats for performing GNSS radio occultation (RO) of Earth’s atmosphere and surface. The goal of CICERO is to provide the first and high-quality commercial radio occultation data from space at low costs while enhancing weather and climate forecasting capabilities. Before CICERO data are used for reliable weather forecasting, the assessment of its performance is necessary. This study shows the performance of CICERO by comparing it with that of COSMIC I. The performance analysis was carried out with respect to geographic distribution, altitude distribution, and refractivity error. The results show that CICERO can acquire global coverage of data at low altitudes as well as COSMIC I, which is important for climate research. In addition, the analysis of refractivity error and its impact on temperature demonstrates that the miniature version of the GNSS RO receiver could satisfy certain accuracy requirements of the GNSS RO measurements. Thus, the cubeSat constellation CICERO can provide radio occultation measurements comparable to those of the COSMIC I mission. The study demonstrates the capabilities of nanosat-based LEO cubeSats to improve data obtainability and accuracy for weather forecasting.},

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@conference{Sun2020,

title = {Performance Benefit from Dual-Frequency GNSS-based Aviation Applications under Ionospheric Scintillation: A New Approach to Fading Process Modeling},

author = {Kiyoung Sun and Hyeyeon Chang and Jiyun Lee and Jiwon Seo and Y.T. Jade Morton and Sam Pullen},

doi = {10.33012/2020.17184},

year  = {2020},

date = {2020-02-14},

booktitle = {Proceedings of the 2020 International Technical Meeting of The Institute of Navigation},

pages = {889 - 899},

address = {San Diego, California},

abstract = {Deep signal fading due to ionospheric scintillation may cause loss-of-lock on one or more satellites in GNSS receiver tracking loops, which can degrade the navigation availability of GNSS-based aviation applications. Scintillation impact can be mitigated via the frequency diversity, which decreases the chance of satellite loss in the presence of deep and frequent signal fades. This study presents an improved fading process model that generates correlated fading processes of dual-frequency signals and simulates the resulting scintillation impact to evaluate the availability benefit of utilizing dual-frequency GNSS in aviation applications under scintillation. The correlated fading process was described by combining single-frequency only and dual-frequency concurrent fading processes under the assumption that each fading process can be modeled as a Poisson process. Times between deep fading onsets and fading durations observed from GPS L1/L5 dual-frequency measurements collected at Hong Kong in March 2nd, 2014 were used to model the GPS L1 only, L5 only, and L1/L5 concurrent fading processes. Availability simulations for SBAS service supporting the LPV200 phase of flight were conducted by considering the effects of satellite geometry degradation and shortened carrier smoothing time, which are caused by signal losses from deep fades generated by the newly proposed fading process model. A parametric analysis of availability resulting from variations in both the probability of loss-of-lock (under deep fading) and the receiver reacquisition time (following loss-of-lock) was conducted to provide receiver requirement standards for SBAS-based aviation under severe scintillation. The results show noticeable availability improvement from dual-frequency SBAS-based aviation applications over existing single-frequency SBAS.},

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tppubtype = {conference}

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@conference{Lee2020,

title = {Optimal Continuity Allocation for a Tightly-coupled KF-based GNSS/IMU Navigation System with Redundant IMUs},

author = {Jinsil Lee and Dongwoo Kim and Dongchan Min and Gihun Nam and Jiyun Lee},

doi = {10.33012/2020.17201},

year  = {2020},

date = {2020-02-14},

booktitle = {Proceedings of the 2020 International Technical Meeting of The Institute of Navigation},

pages = {1101 - 1116},

address = {San Diego, California},

abstract = {This paper introduces an optimal continuity allocation algorithm for a tightly-coupled Kalman-filter (KF)-based Global Navigation Satellite System (GNSS) and multiple Inertial Measurement Units (IMUs) integrated navigation system. Beyond our recent work on the integrity and continuity algorithm of a KF-based GNSS and a single IMU navigation system, the method proposed in this paper enables IMU sensor exclusion while assuring total continuity and integrity requirements under redundant IMU sensor configuration. Two filtering scenarios in the presence of redundant IMU sensors are considered: 1) individual filters that utilize state estimates from a single set of filters at a time, and uses other filters as backup solutions, and 2) a decentralized filter where all the parallel local filters process each IMU sensor measurement and local estimates are subsequently fused in a master filter to achieve the global estimations. First, an analytical equation that can evaluate the continuity risk probability under each filter scenario is derived. Second, based on the fact that sub-filters within the decentralized filter share the same GNSS measurements with different IMU sensors, an inter-filter correlation between test statistics of the decentralized filter is considered to tightly allocate continuity to each monitor. Inter-filter correlation is quantified recursively by the KF, and the monitor thresholds are determined from the formulated joint distributions by the inter-filter correlation. Lastly, a minimum bounding protection level (PL) is determined by optimally allocating continuity risk to each monitor. Continuity allocation considering the correlation significantly improves the overall availability by lowering the continuity burden of each monitor. Simulation results show the benefits of utilizing redundant IMU in terms of system availability and the benefits of taking into account the exact inter-filter correlation for the case of a decentralized filter when allocating continuity requirements for each monitor.},

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@conference{Lee2019c,

title = {Integrity Algorithm to Protect against Sensor Faults in Tightly-coupled KF State Prediction},

author = {Jinsil Lee and Minchan Kim and Dongchan Min and Jiyun Lee},

doi = {10.33012/2019.16867},

year  = {2019},

date = {2019-09-23},

booktitle = {Proceedings of the 32nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2019)},

pages = {594 - 627},

address = {Miami, Florida},

abstract = {Recently, autonomous vehicles including self-driving cars, or autonomous drones are getting a great deal of attention with the expectation that they can partially replace or augment human performance while improving operational efficiency and increase the range of applications. There are many technical issues to solve for realizing the mission including mechanical and electrical problem, control and path planning, and navigation. Among the required technologies, navigation is one of the essential components for the development of autonomous vehicles because vehicles conduct control and path following operations autonomously by trusting the given navigation information. In this response, multi-sensor navigation systems have been actively developed to improve navigation accuracy as well as continuity under various operational conditions. Currently, various sensors including Global Navigation Satellite System (GNSS), Inertial Measurement Unit (IMU), vision sensor, barometer, magnetometer, and LIDAR (for cars) are integrated to provide the navigation solution. Many studies developed the integration algorithms of these sensors, and the accuracy and continuity are significantly improved. As the many inputs from various sensors are integrated, navigation solutions are more often exposed to potential sensor faults. For the practical use of the autonomous vehicle in a ‘real world’ environment, navigation safety in addition to the navigation accuracy and continuity is critical to ensure the safe operation of the autonomous vehicles. This raises the most obvious and important question which is “How can we prove that the solution from the multi-sensor navigation system is safe to use?”. This study leverages the concept of navigation integrity which is carried out in civil aviation navigation. Integrity is a measure of trust in navigation solutions, and integrity algorithm detects navigation sensor faults causing unacceptably large positioning error and computes position error bound (protection level, PL) against undetected sensor faults. In civil aviation, integrity algorithms have been developed for different types of GNSS standalone and augmentation systems including Receiver Autonomous Integrity Monitoring (RAIM), and Satellite or Ground Based Augmentation Systems (SBAS or GBAS) to ensure navigation integrity to the extremely high level of integrity (of the order of from 10-7 to 10-9). In an integrity algorithm, the PL is computed by quantifying the impact of undetected sensor faults which propagates through a filter estimation algorithm. Thus, a PL derivation algorithm should be designed depending on estimation filters. The developed integrity algorithms for civil aviation (reviewed in the previous paragraph) is designed based on the weighted least square (WLS) filter algorithm which is a snapshot estimator in accordance with the positioning algorithm. In contrast, the multi-sensor navigation systems mostly use a Kalman filter (KF), which is a ‘recursive’ filter, for estimating navigation solutions. The recursive filter utilizes all previous sensor information in addition to the current time sensor input to determine the state estimates. This means sensor faults occurred in the previous measurements affect the position estimates as well as sensor faults in the current time measurements. This fault propagation characteristic in a recursive KF should be carefully considered when designing a KF based integrity algorithm. This raises the need for the new integrity algorithm for multi-sensor navigation systems which utilizes KF for sensor integration. The KF based integrity algorithms that quantify the fault impact on state estimates are actively being discussed in recent publications [1]-[3]. One assumption made in the previous studies is that faults occur in the GNSS measurement sequence which is used for the KF measurement update. Studies in [1] and [2] quantified the worst-case integrity risk of KF estimates by determining the worst-case fault vector in an analytical approach based on the relationship between state error and range residual based monitor test statistics. [2] specifically applied the KF based integrity algorithm to evaluate the integrity risk against a GNSS spoofing within a GNSS/IMU integrated system with an assumption that the IMU is a fault-free sensor. As another approach, [3] proposed to compute a real-time PL equation for KF estimates. To improve real-time capability, it applied an external snapshot based WLS RAIM monitor for fault monitoring and computed PL by simulating the impact of remaining fault on KF estimates through the KF algorithm that users are utilizing for their positioning. Based on the fact that there are two main filtering steps which are a state prediction and measurement update, the integrity algorithm for the sensor faults occurring in the state prediction step is also required in multi-sensor navigation systems to fully assure the system safety. In the state prediction step, an estimated state in a previous epoch is propagated to the next epoch based on a given static model or using sensor measurements which provide information for the state prediction. In multi-sensor navigation systems, sensors which provide the information for vehicle motions are used for the state prediction step. There are sensors generally applied in state prediction step including IMU, and vision sensor. Those sensors are also vulnerable to faults [4]-[5], and integrity against those sensors should be considered within the system integrity algorithms. In [6], we illustrated how an unexpected step type IMU faults (potentially due to fracture, stiction, or delamination) affect the KF estimates when it is used for the state prediction in a GNSS/IMU integrated navigation system. It was also shown that the impact of fault on position solutions due to the IMU sensor faults could be expressed using the KF innovation vector in real-time. A PL was determined for the IMU sensor fault hypothesis using the KF innovation vector and additional noise bounding terms. In this paper, we extend the concept of integrity assurance against faults occurring in sensors used for state prediction, proposed in [6], to KF-based multi-sensor navigation systems. We analyze the key difference in the impact of faults occurring in the prediction step and the measurement update step on state estimates. Under the assumption that no simultaneous fault occurs on two integrated sensors (one for the state prediction, and the other for the measurement update), the most fundamental parameter we can utilize from a KF is a KF innovation vector. If the innovation can fully capture the recursive impact of faults on state estimates in real-time, the user PL can be formulated utilizing the innovation vector with additional uncertainty terms for noise bounding. Based on the analytical formulation of the recursive fault impact on user position under each fault condition, it is shown that the innovation vector can express the fault impact on user position only when the fault occurs in sensors used for the state prediction. In case of a fault occurring in sensors used for the measurement update step, additional information on the fault vector is required to fully express the magnitude of the resulting position error caused by the fault. In other words, the innovation vector cannot be used to compute user PL in real-time when there is a fault on sensors used for the measurement update. Table 1 summarizes the content in this paragraph. Based on the finding, this study proposes a generalized integrity architecture which can be used for a KF based multi-sensor navigation system to assure navigation integrity. In the integrity architecture, three fault hypotheses are defined which are a nominal hypothesis (H0), a fault hypothesis occurred in a sensor for the measurement update step (H1), and a fault hypothesis occurred in a sensor for the prediction step (H2). For the H0 hypothesis, nominal covariance from the KF is used for PL computation. Under the H1 fault hypothesis, an additional fault monitoring algorithm is required to detect faults and quantify the undetected fault magnitude after fault monitoring in order to compute the real-time protection level. The algorithms which use RAIM proposed by the previous study [3] can be utilized for computing a real-time PL for this fault hypothesis. Lastly, the KF innovation vector is used to detect the fault and to compute a PL for the H2 fault hypothesis. For the H2 fault hypothesis, fault detection is conducted on the user position domain by comparing the fault impact determined using the KF innovation vector in real-time with a pre-defined threshold without employing additional fault monitoring algorithms. The proposed integrity algorithm can be applied to various types of multi-sensor navigation systems to compute PL against the sensor faults occurring in the state prediction step. In this study, we verified and showed the applicability of the developed integrity algorithm using two types of KF based multi-sensor systems which are a GNSS/IMU integrated navigation system and a GNSS/vision integrated navigation system. IMU and Vision sensors were used to predict the filter state, and GNSS was used to update the filter. Three PLs are computed for each fault hypothesis. We employed the algorithm proposed in [3] for computing a real-time PL against GNSS faults within the KF. New PLs both for the IMU and vision sensor were determined using the KF innovation sequence based on the proposed integrity algorithm. The computed PLs for IMU and vision sensors well bounded the KF estimates both under no-fault condition and fault-injected condition. The proposed integrity algorithm for KF-based multi-sensor navigation systems against sensor faults in the KF prediction step can be broadly used to fully assure the safety of autonomous vehicles. References [1] M. Joerger, and B. Pervan (2013). "Kalman Filter-Based Integrity Monitoring Against Sensor Faults." Journal of Guidance, Control, and Dynamics 36(2): 349-361. [2] C. Tanil et al. (2017). "An INS monitor to detect GNSS spoofers capable of tracking vehicle position." IEEE Transactions on Aerospace and Electronic Systems. [3] Bhattacharyya, S. and D. Gebre-Egziabher (2015). "Kalman filter based RAIM for GNSS receivers." IEEE Transactions on Aerospace and Electronic Systems 51(3): 2444-2459. [4] Bhatti, Umar Iqbal, and Washington Yotto Ochieng. "Failure modes and models for integrated GPS/INS systems." The Journal of Navigation 60.2 (2007): 327-348. [5] Fu, Li et al. “Vision-Aided RAIM: A New Method for GPS Integrity Monitoring in Approach and Landing Phase” Sensors (Basel, Switzerland) vol. 15,9 22854-73. 10 Sep. 2015, doi:10.3390/s150922854 [6] J. Lee, et al., “Integrity assurance of Kalman-filter based GNSS/IMU integrated systems against IMU faults for UAV applications,” ION GNSS 2018, Miami, Florida, pp. 2484-2500.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Kim2019,

title = {Use of Local-area Differential GNSS System for Polar Exploration},

author = {Dongwoo Kim and Minchan Kim and Jinsil Lee and Jiyun Lee},

year  = {2019},

date = {2019-07-26},

booktitle = {The 13th International Symposium on Antarctic Earth Sciences},

address = {Incheon, Republic of Korea},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Min2019,

title = {Deep Neural Network Based Multipath Mitigation Method for Carrier Based Differential GNSS Systems},

author = {Dongchan Min and Minchan Kim and Jinsil Lee and Jiyun Lee},

doi = {10.33012/2019.16856},

year  = {2019},

date = {2019-04-15},

booktitle = {Proceedings of the ION 2019 Pacific PNT Meeting (2019 ION PNT)},

pages = {451-466},

address = {Honolulu, Hawaii},

abstract = {Carrier based Differential Global Navigation Satellite System (CD-GNSS) is getting lots of attention as a promising technology for drones since it can provide centimeter-level accuracy. Unlike widely used CD-GNSS applications such as geodetic survey, CD- GNSS systems to be used for drone applications should provide a certain level of integrity along with accuracy. However, there is a critical challenge in guaranteeing the integrity of CD-GNSS systems for drone applications due to a long filter duration which is the time necessary to resolve cycle ambiguity correctly. One of the most dominant factors that limits reducing the filter duration is the code multipath error. In this response, this paper proposes a code multipath mitigation method using Deep Neural Network (DNN) for drone systems. It is well known that DNN is a powerful for nonlinear regression problems toward which multipath estimation is applicable and can be trained using a large quantity of data. The target scenario of this study is chosen as a drone flying at a sufficiently high altitude (where no multipath reflections exist from surrounding obstacles) before lowering its altitude for other phases of operation. Therefore, the dominant factor of multipath errors of the drone is the signal reflection from its body frame. Considering the fact, the input parameters were chosen for developing the DNN model as elevation, azimuth and tilt angle of antenna which characterize signals reflected by the frame and Signal to Noise Ratio (SVR) which characterizes the slight change of signals. The validity of the proposed model was investigated and its multipath mitigation performance was evaluated under the target scenario using real data. The results show that the multipath error is mitigated by about 30% in terms of the standard deviation of multipath error and the filter duration is reduced by about 66%.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

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@conference{Lee2019b,

title = {Assessment and Mitigation of Ionospheric Spatial Decorrelation on GBAS: Lessons Learned},

author = {Jiyun Lee},

doi = {10.33012/2019.16840},

year  = {2019},

date = {2019-04-15},

booktitle = {Proceedings of the ION 2019 Pacific PNT Meeting (2019 ION PNT)},

pages = {807-826},

address = {Honolulu, Hawaii},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Chang2019,

title = {Assessment of Ionospheric Spatial Decorrelation for Daytime Operations of GBAS in the Brazilian Region},

author = {Hyeyeon Chang and Moonseok Yoon and Jiyun Lee and Sam Pullen and Leonardo Marini Pereira},

doi = {10.33012/2019.16673},

year  = {2019},

date = {2019-02-04},

booktitle = {Proceedings of the 2019 International Technical Meeting of The Institute of Navigation (ION ITM 2019)},

pages = {618-631},

address = {Reston, Virginia},

abstract = {	Extensive ionospheric studies were conducted to support the initial phase of system design approval (SDA) for the existing SLS-4000 GBAS installed at Galeão Airport (GIG) in Rio de Janeiro, Brazil. This paper focuses on determining the broadcast value of the standard deviation of vertical ionospheric gradients (or sigma_vig) that is required to bound ionospheric spatial gradients at the Brazilian region under nominal conditions during daytime hours. The days for the analysis were selected by a combination of high levels of daytime or nighttime scintillation and/or severe values of the geomagnetic storm index. The time-step method, which is useful for gaining sufficient samples at distances less than the physical separation distance of ground stations, was utilized to estimate ionospheric spatial gradients. The results show that the bounding sigma_vig values are in the range of 8-13 mm/km, when daytime was defined to exist between 6 AM and 6 PM local time. Because the time-step method estimates gradients over a time interval instead of at a single time, the results include temporal as well as spatial gradients, meaning that they overestimate the spatial gradients that are the desired results. Thus, a new method called “geometric modeling” was proposed to estimate ionospheric temporal gradients and evaluate the temporal effect added to the bounding sigma_vig values. As a result, a sigma_vig of 13 mm/km including an approximately 2 mm/km temporal gradient contribution, is conservative enough to bound ionospheric spatial decorrelation for daytime GBAS operations in the Brazilian region.},

keywords = {},

pubstate = {published},

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@conference{Yoon2019c,

title = {Integrity Risk Evaluation of Impact of Ionospheric Anomalies on GAST D GBAS},

author = {Moonseok Yoon and Jiyun Lee and Sam Pullen},

doi = {10.33012/2019.16685},

year  = {2019},

date = {2019-02-04},

booktitle = {Proceedings of the 2019 International Technical Meeting of The Institute of Navigation (ION ITM 2019)},

pages = {100-112},

address = {Reston, Virginia},

abstract = {To insure safe approach and landing operations of GAST D GBAS, this study develops a three-step worst-case parameter search and integrity risk evaluation method to identify the worst-case sets of ionospheric threat parameters and evaluate the worstpossible integrity risk. Parameters of the ionospheric gradient impact simulation are first classified into two groups, “Worst-Case (WC)” and “average,” based on the underlying “specific risk” integrity requirements. “WC” parameters are those for which a clear basis for averaging could not be established because the probabilistic distribution of these parameters cannot be established with confidence due to the lack of sufficient independent observation data. These “WC” parameters must use the worst-case value of that parameter in calculating integrity risk, meaning the value of the parameter that maximizes the integrity risk. Parameters chosen to be “average” are those which are known to be essentially random from the point of view of a GBAS precision approach impacted by an ionospheric front. The parameters treated as “average” can apply values from a sampled distribution (usually from a Uniform distribution) between the minimum and maximum values of that parameter as the basis for calculating integrity risk. The first step of this method performs a randomized search over all of the parameters with a very large total number of samples to identify one or more regions of the ionospheric threat space where the worst-case result (maximum integrity risk) is likely to lie. In the second step, the search for the worst-case set of threat parameters is more refined so that a single worst-case set of parameters can be selected for each region. Once each identified region has a single set of worst-case threat-model parameters, separate “Step 3” simulations can be conducted for each region to estimate integrity risk values, and these final results are what is compared to the SARPs anomalous ionosphere integrity requirements. This paper also evaluates the maximum integrity risk probabilities based on this three-step method using the SARPs ionospheric anomaly threat model and geometric parameters. The resulting integrity risk values for all regions are well below 10-9 , showing that the GAST D SARPs integrity requirement is met based on this combined worst-case/average definition of the anomalous ionospheric threat.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

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@conference{Sun2018bb,

title = {Ionospheric Scintillation Effects on GBAS Ground Station Pseudorange Errors},

author = {Kiyoung Sun and Moonseok Yoon and Michael Felux and Jiyun Lee},

url = {http://adsabs.harvard.edu/abs/2018AGUFMSA13C2790S},

year  = {2018},

date = {2018-12-10},

booktitle = {AGU Fall Meeting 2018},

address = {Washington D.C},

abstract = {Ground-Based Augmentation Systems (GBAS) provide differential corrections and integrity information for aviation users to support aircraft precision approach and landing. However, the navigation performance of GBAS can be severely degraded by ionospheric scintillation. In extreme cases, deep fades in GPS signal amplitude lead to satellite signal loss which reduces the number of satellites available for use and consequently degrades navigation accuracy and availability.

Even if a receiver can tolerate the signal loss described above, a serious risk still remains on the navigation performance due to intensified ground and airborne pseudorange errors, resulting from the receiver tracking process in the presence of scintillation. In GBAS, ground and airborne error sources include thermal noise and multipath, which cannot be removed from differential corrections. These errors are modeled and used for airborne positioning algorithm and integrity protection level computations. Thus, if the ground and airborne errors increased by scintillation are not bounded by the existing model, they may pose an integrity threat to GBAS users.



In this paper, the effects of scintillation on GBAS ground station pseudorange errors were analyzed using multi-frequency GPS data collected from the reference station in Bahir Dar, Ethiopia located near the equatorial region. To quantify the ground station pseudorange errors, the standard deviations of receiver noise and multipath estimates are calculated from the linear combinations of dual-frequency GPS measurements under strong scintillation. The processed statistics were compared to the existing GBAS ground error model which was determined from receiver noise and multipath under nominal conditions. GBAS availability was also evaluated by computing Vertical Protection Levels (VPLs) with the broadcast integrity parameters newly estimated under scintillation and comparing those to the Vertical Alert Limit (VAL).



The results show that the GBAS ground error statistics under strong scintillation noticeably exceed those defined by the current GBAS ground error model. While a new GBAS ground error model can guarantee the navigation integrity in scintillation conditions, the system may suffer availability degradation depending on the severity of the scintillation.},

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tppubtype = {conference}

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@conference{Sun2018b,

title = {Neural Network Aided Reconstruction of Ionospheric Tomography for Limited GNSS Measurements},

author = {Kiyoung Sun and Pilhoon Choi and Sunjin Kim and Jiyun Lee},

year  = {2018},

date = {2018-12-06},

booktitle = {2018 10th Kyushu University-KAIST Symposium on Aerospace Engineering},

address = {Daejeon, Rep. of Korea},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Lee2018b,

title = {Performance Comparison of Neural Networks for Geomagnetic Field Based Indoor Positioning System},

author = {Hyojin Lee and Harhee Park and Dongchan Min and Jiyun Lee},

year  = {2018},

date = {2018-12-06},

booktitle = {2018 10th Kyushu University-KAIST Symposium on Aerospace Engineering},

address = {Daejeon, Rep. of Korea},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Lee2018,

title = {Integrity Assurance of Kalman-Filter based GNSS/IMU Integrated Systems Against IMU Faults for UAV Applications},

author = {Jinsil Lee and Minchan Kim and Jiyun Lee and Sam Pullen},

doi = {10.33012/2018.15977},

year  = {2018},

date = {2018-09-24},

booktitle = {Proceedings of the 31st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2018)},

pages = {2484 - 2500},

address = {Miami, Florida},

abstract = {This study proposes an integrity architecture for an Extended Kalman filter (EKF) based Global Navigation Satellite System (GNSS)/Inertial Measurement Unit (IMU) integrated system to assure integrity of unmanned aerial vehicle (UAV) navigation systems. An integrity risk allocation tree is developed for each sensor fault hypothesis including the nominal hypothesis, a GNSS fault hypothesis, and an IMU sensor fault hypothesis. This paper then proposes a real-time EKF vertical protection level (VPL) against IMU sensor faultsto assure navigation integrity based on the relationship between EKF innovations and EKF state errors resulting from potential IMU faults and measurement noise. Simulations for the derived EKF VPLs are conducted under a specific IMU-fault condition and under no-IMU-fault condition to investigate typical performance. This study will be extended to assure the navigation integrity of different types of multi-sensor systems for UAV applications.},

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pubstate = {published},

tppubtype = {conference}

}

@conference{Chang2017b,

title = {Assessment of Ionospheric Gradient Statistics for Operating GBAS in Geomagnetic Equatorial Region},

author = {Hyeyeon Chang and Jiyun Lee},

year  = {2017},

date = {2017-12-11},

booktitle = {AGU Fall Meeting 2017},

address = {New Orleans, LA},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Sun2017,

title = {Ionospheric Scintillation Effects on GBAS Ground Multipath Error in Low-latitude Regions},

author = {Kiyoung Sun and Jiyun Lee},

year  = {2017},

date = {2017-12-07},

booktitle = {2017 9th Kyushu University-KAIST Symposium on Aerospace Engineering},

address = {Fukuoka, Japan},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Chang2017,

title = {Case study for GBAS Operation in Equatorial Region on Nominal day at Daytime},

author = {Hyeyeon Chang and Jiyun Lee},

year  = {2017},

date = {2017-12-07},

booktitle = {2017 9th Kyushu University-KAIST Symposium on Aerospace Engineering},

address = {Fukuoka, Japan},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Hong2017,

title = {Analysis on the Casualty risk from UAS Collision for Deriving Safe Separation Distance},

author = {Giseon Hong and Jiyun Lee},

year  = {2017},

date = {2017-12-07},

booktitle = {2017 9th Kyushu University-KAIST Symposium on Aerospace Engineering},

address = {Fukuoka, Japan},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Lee2017e,

title = {Vertical Protection Level (VPL) derivation of multi-sensor integrated LAD-GNSS for UAV applications},

author = {Jinsil Lee and Jiyun Lee},

year  = {2017},

date = {2017-11-14},

booktitle = {ITSNT 2017},

address = {Toulouse, France},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Kim2017d,

title = {High-Integrity and Low-Cost Local-Area Differential GNSS Prototype for UAV Applications},

author = {Dongwoo Kim and Jinsil Lee and Minchan Kim and Jiyun Lee and Sam Pullen},

doi = {10.33012/2017.15110},

year  = {2017},

date = {2017-09-25},

booktitle = {Proceedings of the 30th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2017)},

pages = {2031 - 2054},

address = {Portland, Oregon},

abstract = {As civilian use of unmanned aerial vehicles (UAVs) increases, safe operation of UAVs while preventing collisions with either humans or ground structures has become a significant concern. To perform autonomous UAV missions Beyond Visual Line-Of-Sight (BVLOS) or in low-altitude airspace safely, achieving high accuracy and reliability of navigation solutions is required. This motivates the development of a cost-effective local-area UAV network that utilizes a Local-Area Differential Global Navigation Satellite System (LAD-GNSS) navigation solution [1, 2]. LAD-GNSS achieves a level of integrity comparable to that of Ground Based Augmentation System (GBAS) Category I operations by monitoring navigation faults at the ground station and by broadcasting integrity information to the UAV [3]. The architecture of this system involves space-conserving hardware configurations and several simplified GBAS integrity monitoring algorithms to reduce both the cost and the complexity of the system. LAD-GNSS is designed to support UAVs with a minimum operating altitude of either 50 ft plus obstacle height (within 5 km of the ground facility) or 200 ft (within 20 km of the ground facility) by providing an accurate position solution and a tight uncertainty bound on its position error. A prototype of LAD-GNSS has been developed and evaluated for both accuracy and integrity performance. The key ground and airborne functions of this system are shown in Figure 1 below. One notable characteristic of this prototype is that it utilizes a two-way datalink between the ground facility and the airborne user, which provides a major improvement in system flexibility. The two-way datalink enables the system not only to allocate integrity risk to each fault hypothesis dynamically to obtain the minimum safe protection level [4] but also to simplify the geometry screening needed to mitigate ionospheric anomalies by computing the maximum error in vertical position (MIEV) only for the satellites known to be tracked by each UAV. Specifically, each UAV continuously sends its GNSS measurements to the ground station, so that error corrections and integrity information can be generated by the ground station just for this known satellite geometry. This information is then broadcast back to the UAV to allow it compute its position solution. The integrity status of each UAV, including its current protection levels, is maintained by the ground facility and is used to guide each vehicle while maintaining safe separation from nearby obstacles and other UAVs. The LAD-GNSS prototype is composed of two parts: a ground module and an onboard module. The ground module operates in a manner similar to a GBAS ground facility. Most of the computations regarding integrity monitoring are performed in the ground module. The onboard module computes position solutions using the corrections broadcast from the ground module. The position solutions are then fed into a flight controller, which is the 3DR Pixhawk. The hardware components of the prototype for the ground module and the airborne module are described as follows. For the ground module, the equipment includes a single pair of NovAtel OEM-V3 receivers and a NovAtel GPS 703 GGG antenna (choke ring type) that can receive L1, L2 and L5 GNSS signals. An Intel NUC mini-PC is used to perform integrity monitoring calculations. For the onboard module, the same receiver model as one of the ground module is mounted on the octocopter UAV platforms. A NovAtel compact GNSS antenna is used for the onboard antenna. Due to the limited UAV payload capacity, a small single-board Raspberry Pi processor, which is capable of performing just the positioning calculations, is loaded on the UAV instead of a mini-PC. An Xbee Pro1 S1 modem, which can support communications over a 1-mile range, is provisionally used for the communication link. The software for both the ground and airborne modules runs in the Linux C language. Flight tests were conducted to evaluate the performance of this LAD-GNSS prototype in Yeongwol. Yeongwol has been designated by the government of South Korea as a permitted area of 95 km^2 for UAV flight tests. The flight paths chosen were designed to cover areas of interest considering practical applications of UAVs, such as agriculture, surveying, mapping, and reconnaissance. The distance of the designed path above the sparsely populated area is 1.5 km. The true trajectory of the UAV was derived by post-processing based on double differenced carrier-phase measurements. The Navigation System Error (NSE) of the system was then computed as the difference between the true UAV path (from post-processing) and the path estimated by LAD-GNSS. While LAD-GNSS can be the primary source of navigation for UAVs, other navigation sensors are required to provide reliable navigation in case of GNSS signal interference or blockage. In this study, the prototype has been provisionally extended to incorporate multiple sensors to assure complete UAV navigation system safety. With the inclusion of multiple sensors, a new fault hypothesis, which is a multi-sensor failure, is added to the existing LAD-GNSS integrity fault tree. The onboard module integrates Inertial Measurement Unit (IMU) sensor output with the LAD-GNSS solution using a Kalman filter (KF). A KF innovation-based fault detection algorithm is developed to protect the UAV from IMU sensor faults. In addition, optimal protection levels are computed by allocating the newly introduced multi-sensor integrity risk dynamically together with the LAD-GNSS integrity risk. This allocation to potential multi-sensor failures would change depending on sensor type and quality. Thus, optimal allocation is essential and would be effective for the proposed multi-sensor integrated system. The extended prototype was also tested at the Yeongwol test site, and its performance was compared with the flights that used LAD-GNSS only. References: [1] S. Pullen, P. Enge, and J. Lee, "High-Integrity Local-Area Differential GNSS Architectures Optimized to Support Unmanned Aerial Vehicles (UAVs)," Proceedings of ION ITM 2013, San Diego, CA, Jan. 28-30, 2013. [2] M. Kim, K. Kim, J. Lee, and S. Pullen, "High Integrity GNSS Navigation and Safe Separation Distance to Support Local-Area UAV Networks," Proceedings of the 27th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2014), Tampa, Florida, September 2014, pp. 869-878. [3] M. Kim, J. Lee, D. Kim, J. Lee, and S. Pullen, “Design of Local Area DGNSS Architecture to Support UAV Networks: Optimal Integrity/Continuity Allocations and Fault Monitoring,” Proceedings of ION PNT 2017, Hawaii, May 2017. [4] B. Pervan, S. Pullen, and J. Christie, “A Multiple Hypothesis Approach to Satellite Navigation Integrity,” Navigation: Journal of the Institute of Navigation, Vol. 45, No. 1, Spring 1998, pp. 61-84.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Kim2017b,

title = {Design of Local Area DGNSS Architecture to Support Unmanned Aerial Vehicle Networks: Concept of Operations and Safety Requirements Validation},

author = {Minchan Kim and Jinsil Lee and Dongwoo Kim and Jiyun Lee},

doi = {10.33012/2017.15091},

year  = {2017},

date = {2017-05-01},

booktitle = {Proceedings of the ION 2017 Pacific PNT Meeting},

pages = {992 - 1001},

address = {Honolulu, Hawaii},

abstract = {Local-area differential global navigation satellite systems (LAD-GNSS) support unmanned aerial vehicles (UAVs) with high integrity and accuracy. This study investigates three major issues in fully establishing LAD-GNSS and analyzes their performance. First, we define the concept and requirements of UAV operation, including segregation of UAV operation coverage in low-altitude airspaces, and the derivation of navigation requirements, such as alert limits (ALs), for each operational coverage. Second, we design a LAD-GNSS architecture by simplifying the hardware and monitoring algorithms of both the ground facility and onboard module, using the well-established ground-based augmentation system (GBAS) as a starting point. Lastly, we perform theoretical performance evaluations comparing position uncertainty bounds, which are represented by protection levels (PLs), to the corresponding navigation requirements for each coverage airspace. We derive and compare PLs and ALs under both nominal and malfunction cases. In addition, we describe a method for deriving PLs for excessive acceleration and code-carrier divergence fault scenarios, which are bounded by using a maximum-allowable error in range. Using these PLs, integrity/continuity allocations are ideally and dynamically assigned to each single-fault hypothesis to obtain optimized PLs that are identical for all fault scenarios. We find that vertical protection levels (VPLs) are reduced by approximately 16% when implementing the optimal allocation method.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Kim2017c,

title = {Monte Carlo Simulation for Impact of Anomalous Ionospheric Gradient on GAST-D GBAS},

author = {Dongwoo Kim and Moonseok Yoon and Jiyun Lee and Sam Pullen and Doug Weed},

doi = {10.33012/2017.15049},

year  = {2017},

date = {2017-05-01},

booktitle = {Proceedings of the ION 2017 Pacific PNT Meeting},

pages = {47-55},

address = {Honolulu, Hawaii},

abstract = {In this paper, a tool based on Monte Carlo simulation is developed for probabilistic analysis of the effects of anomalous ionospheric gradients on GAST-D GBAS approach and landing operations. While parameters associated with ionospheric gradients and satellite geometry are assumed to be at their worst-case values in the traditional certification approach, Monte Carlo simulation takes advantage of the random characteristics of these parameters. In the Monte-Carlo approach, simulation parameters are randomly chosen from the probabilistic distributions chosen for to represent the ionospheric threat model. More than ?10?^9 sampled events are combined into a probability of Hazardously Misleading Information (PHMI), defined as the sum of the probabilities of missed detections (P_mds) weighted by the probability of occurrence of the anomalous ionospheric event leading to each P_md value. The results are represented in terms of a cumulative distribution function showing the overall probability of exceeding a given differential range error size. The maximum allowable range error due to ionospheric gradients to support GAST-D is 2.75 m according to the reformulated requirements of the Standards and Recommended Practices (SARPs). The simulation results showed that the PHMI for differential range errors exceeding 2.75 m was well below ?10?^(-9). Furthermore, individual ionospheric events were investigated to ensure that integrity requirements were met in the traditional interpretation. The maximum differential range error in the simulation results was 2.74 m. Most of the largest differential range errors are generated from the specific geometry where the baseline direction (between the GBAS ground facility and the landing threshold point, or LTP) is closely aligned with the propagation direction of the ionospheric front.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Choi2016,

title = {Near Real-time GNSS-based Ionospheric Model using Expanded Kriging in the East Asia Region},

author = {Pilhoon Choi and Eugene Bang and Jiyun Lee},

url = {http://adsabs.harvard.edu/abs/2016AGUFM.G31B1064C},

year  = {2016},

date = {2016-12-12},

booktitle = {AGU Fall Meeting 2015},

address = {San Francisco, CA},

abstract = {Many applications which utilize radio waves (e.g. navigation, communications, and radio sciences) are influenced by the ionosphere. The technology to provide global ionospheric maps (GIM) which show ionospheric Total Electron Content (TEC) has been progressed by processing GNSS data. However, the GIMs have limited spatial resolution (e.g. 2.5° in latitude and 5° in longitude), because they are generated using globally-distributed and thus relatively sparse GNSS reference station networks. This study presents a near real-time and high spatial resolution TEC model over East Asia by using ionospheric observables from both International GNSS Service (IGS) and local GNSS networks and the expanded kriging method. New signals from multi-constellation (e.g,, GPS L5, Galileo E5) were also used to generate high-precision TEC estimates. The newly proposed estimation method is based on the universal kriging interpolation technique, but integrates TEC data from previous epochs to those from the current epoch to improve the TEC estimation performance by increasing ionospheric observability. To propagate previous measurements to the current epoch, we implemented a Kalman filter whose dynamic model was derived by using the first-order Gauss-Markov process which characterizes temporal ionospheric changes under the nominal ionospheric conditions. Along with the TEC estimates at grids, the method generates the confidence bounds on the estimates using resulting estimation covariance. We also suggest to classify the confidence bounds into several categories to allow users to recognize the quality levels of TEC estimates according to the requirements for user's applications. This paper examines the performance of the proposed method by obtaining estimation results for both nominal and disturbed ionospheric conditions, and compares these results to those provided by GIM of the NASA Jet propulsion Laboratory. In addition, the estimation results based on the expanded kriging method are compared to the results from the universal kriging method for both nominal and disturbed ionospheric conditions.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Chang2016,

title = {Validation of Large Ionospheric Gradient Observed in India on 15th, February 2015},

author = {Hyeyeon Chang and Moonseok Yoon and Jiyun Lee},

year  = {2016},

date = {2016-12-09},

booktitle = {2016 8th Kyushu University-KAIST Symposium on Aerospace Engineering},

address = {Daejeon, Korea},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Hyeon2016,

title = {Application of Weighted Least Square RAIM to Multi-Sensor Navigation Integrated with Space-Based Augmentation System},

author = {Eunjeong Hyeon and Jiyun Lee},

year  = {2016},

date = {2016-12-09},

booktitle = {2016 8th Kyushu University-KAIST Symposium on Aerospace Engineering},

address = {Daejeon, Korea},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Lee2016b,

title = {Integration of Onboard Sensors and Local Area DGNSS to Support High Integrity Unmanned Aerial Vehicles (UAV) Navigation},

author = {Jinsil Lee and Minchan Kim and Jiyun Lee},

doi = {10.33012/2016.14702},

year  = {2016},

date = {2016-09-12},

booktitle = {Proceedings of the 29th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2016)},

pages = {1477 - 1484},

address = {Portland, Oregon},

abstract = {A Local-Area Differential GNSS (LAD-GNSS) provides high integrity and accuracy for Unmanned Aerial Vehicles (UAVs). The integration of onboard sensors to the LAD-GNSS can support continuous and reliable navigation by overcoming GNSS signal vulnerability. This paper proposes the concept of a high integrity navigation architecture into which the LAD-GNSS and onboard sensors are integrated using an extended Kalman filter (EKF). Key components of the integrated system developed in this work, include its integrity/continuity requirement design, fault-monitoring strategies, and the corresponding protection level (PL) computation formulations. In this paper, the total integrity requirements are divided into mainly the following four hypotheses: a fault-free condition, a reference receiver failure, all other failures of LAD-GNSS, and an onboard sensor failure. According to the integrity allocation, fault monitoring strategies and PL computation formulations were proposed. The ground monitor of the LAD-GNSS and the onboard Receiver Autonomous Integrity Monitoring (RAIM) are utilized to monitor a single satellite failure sequentially, and an innovation-based fault-monitoring method is applied to monitor onboard sensor failures. To evaluate the performance of the integrated system, the VPLs under the four hypotheses were calculated using data collected from flight experiments which used an Inertial Navigation Sensor (INS) as an onboard sensor. The results show that the PL for the INS failure hypothesis has the largest vertical protection level (VPL) for the most of the operation time and it suitably bounds vertical position errors during a flight test.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Bang2016bb,

title = {Expanded Ionospheric Estimation and Threat Model Algorithms for SBAS},

author = {Eugene Bang},

doi = {10.33012/2016.14700},

year  = {2016},

date = {2016-09-12},

booktitle = {Proceedings of the 29th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2016)},

pages = {1338 - 1349},

address = {Portland, Oregon},

abstract = {The largest contribution to the Vertical Protection Levels (VPLs) of Satellite-Based Augmentation Systems (SBAS) comes from the Grid Ionospheric Vertical Errors (GIVEs), which are confidence bounds for the vertical ionospheric delay estimates of SBAS. Thus, reducing GIVEs is a critical issue in improving the performance of SBAS. This paper introduces two expanded methodologies to improve the performance of SBAS by reducing the magnitudes of GIVEs. We initially propose an expanded kriging method which integrates ionospheric observables from a previous epoch to a current fit domain to improve the kriging fit performance. Secondly, we propose a new threat metric, Norm-based Angular Metric (NAM), which effectively captures the uniformity of the Ionospheric Pierce Point (IPP) distribution by measuring the angular distribution of the IPPs. We also construct an undersampled ionospheric irregularity threat model with a three-dimensional set of threat metrics by combining the newly developed metric and the existing Rfit and Relative Centroid Metric (RCM). The performance of the proposed algorithms is investigated by conducting availability simulations for SBAS in the Korean region. First, with the proposed kriging method, the coverage of 99.9% availability for APV-I service is increased by approximately 12% within South Korea. Second, the newly developed threat model widened the 99% availability coverage for APV-I service by approximately 13% when SBAS monitor stations are expanded to overseas locations.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Lee2016c,

title = {Vertical Position Error Bounding for Integrated GNSS/Onboard Sensors to Support Unmanned Aerial Vehicle (UAV)},

author = {Jinsil Lee and Eunjeong Hyeon and Minchan Kim and Jiyun Lee},

year  = {2016},

date = {2016-09-01},

booktitle = {ICCAS 2016},

address = {Daejeon, Korea},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Lee2016,

title = {Equatorial Plasma Bubble Effects on GBAS and Its Mitigation Techniques},

author = {Jiyun Lee},

year  = {2016},

date = {2016-06-01},

booktitle = {International Beacon Satellite Symposium 2016},

address = {Trieste, Italy},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}