Pub Date : 2023-04-24DOI: 10.1109/PLANS53410.2023.10140079
J. Cole, A. Cunningham, Jerry Sweet, Pete Hulbert
In this paper we show feasibility of miniature, high-g MEMS capacitive accelerometers with full-scale ranges of 400 to 10,000g and that are capable of measuring high-g navigation events.
{"title":"Challenges in Developing a Family of MEMS Accelerometers for High-g-Navigation Applications","authors":"J. Cole, A. Cunningham, Jerry Sweet, Pete Hulbert","doi":"10.1109/PLANS53410.2023.10140079","DOIUrl":"https://doi.org/10.1109/PLANS53410.2023.10140079","url":null,"abstract":"In this paper we show feasibility of miniature, high-g MEMS capacitive accelerometers with full-scale ranges of 400 to 10,000g and that are capable of measuring high-g navigation events.","PeriodicalId":344794,"journal":{"name":"2023 IEEE/ION Position, Location and Navigation Symposium (PLANS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114303058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-24DOI: 10.1109/PLANS53410.2023.10139936
Matteo De Petrillo, Derek Ross, Jason N. Gross
In this article, we present a path planning algorithm for a team of an Unmanned Ground Vehicle and an Unmanned Aerial Vehicle (UAV) that leverages Gaussian process regression to plan a path that meets information gathering objectives while reducing the UAV's localization uncertainty by learning to compensate for outlier measurements or missed expected sensor measurements over the trajectory. Simulation results are compared to approach that also compensates for belief space planning but is incapable of handling outliers or unexpected degradation from the environment1.
{"title":"Gaussian Process Regression for Learning Environment Impacts on Localization Accuracy of a UAV with Respect to UGV for Search Planning","authors":"Matteo De Petrillo, Derek Ross, Jason N. Gross","doi":"10.1109/PLANS53410.2023.10139936","DOIUrl":"https://doi.org/10.1109/PLANS53410.2023.10139936","url":null,"abstract":"In this article, we present a path planning algorithm for a team of an Unmanned Ground Vehicle and an Unmanned Aerial Vehicle (UAV) that leverages Gaussian process regression to plan a path that meets information gathering objectives while reducing the UAV's localization uncertainty by learning to compensate for outlier measurements or missed expected sensor measurements over the trajectory. Simulation results are compared to approach that also compensates for belief space planning but is incapable of handling outliers or unexpected degradation from the environment1.","PeriodicalId":344794,"journal":{"name":"2023 IEEE/ION Position, Location and Navigation Symposium (PLANS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123131169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-24DOI: 10.1109/PLANS53410.2023.10139992
M. Kourogi, Ryosuke Ichikari, Takahiro Miura, Satoki Ogiso, T. Okuma
Tracking locations of vehicles such as forklifts in warehouses and factories is crucial since it contributes to the safety of personnel and the output performance of manufacturing and logistics activities. It is necessary to develop a method of locating the vehicles by attaching generic inertial measurement units (IMUs) without any modifications. In this research, we have aimed at providing technologies to estimate locations of the vehicles with the IMUs simply attached to the vehicles based on vibration analysis. We have also developed a novel method of automatic calibration between the proposed vibration signatures and the road conditions without any manual procedures. Integration of acceleration in short terms (within 0.5-2 seconds) and observation of vibration signatures in long terms (> 30 seconds) are fused in the extended Kalman filtering framework to stably estimate the correlation parameters and can also be used to detect changes in the road conditions. In this research, we confirmed that accuracy of localization is below 1-5% of distance travelled on average for electric wheelchairs and handy wagons without any manual calibration procedures by using the smartphones. With aids of generic Bluetooth Low Energy (BLE) beacons, we also confirmed that the error of location can be bounded to below 2 meters on average.
{"title":"Vibration-Based Dead-Reckoning for Vehicle Localization","authors":"M. Kourogi, Ryosuke Ichikari, Takahiro Miura, Satoki Ogiso, T. Okuma","doi":"10.1109/PLANS53410.2023.10139992","DOIUrl":"https://doi.org/10.1109/PLANS53410.2023.10139992","url":null,"abstract":"Tracking locations of vehicles such as forklifts in warehouses and factories is crucial since it contributes to the safety of personnel and the output performance of manufacturing and logistics activities. It is necessary to develop a method of locating the vehicles by attaching generic inertial measurement units (IMUs) without any modifications. In this research, we have aimed at providing technologies to estimate locations of the vehicles with the IMUs simply attached to the vehicles based on vibration analysis. We have also developed a novel method of automatic calibration between the proposed vibration signatures and the road conditions without any manual procedures. Integration of acceleration in short terms (within 0.5-2 seconds) and observation of vibration signatures in long terms (> 30 seconds) are fused in the extended Kalman filtering framework to stably estimate the correlation parameters and can also be used to detect changes in the road conditions. In this research, we confirmed that accuracy of localization is below 1-5% of distance travelled on average for electric wheelchairs and handy wagons without any manual calibration procedures by using the smartphones. With aids of generic Bluetooth Low Energy (BLE) beacons, we also confirmed that the error of location can be bounded to below 2 meters on average.","PeriodicalId":344794,"journal":{"name":"2023 IEEE/ION Position, Location and Navigation Symposium (PLANS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122128748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-24DOI: 10.1109/PLANS53410.2023.10140062
M. Caamano, Daniel Gerbeth, H. Sato, Mihaela‐Simona Circiu, M. Felux
In this paper, we evaluate the performance of the dual-frequency airborne ionospheric gradient monitor proposed for dual-frequency multi-constellation (DFMC) Ground Based Augmentation Systems (GBAS) at different distances from the airport. We use two types of thresholds for this assessment: (i) a constant threshold derived from operational requirements, and (ii) a dynamic threshold that increases with the distance from the airport. Increasing the threshold allows more ionospheric error within the position solution, but also enables the use of the primary single-frequency modes without the need to switch to the ionosphere-free (Ifree) solution for a longer period, which generally degrades the performance because it combines the noise and multipath of two frequencies. Furthermore, we compare the performance of the two potential architectures for DFMC GBAS: (i) the so-called GAST F architecture, which is based on single-frequency 100 seconds smoothing, and (ii) the GAST X architecture, which is based on divergence-free (Dfree) smoothing with variable and potentially longer smoothing time constants. Results with both simulated and real data show that the use of a variable threshold significantly reduces the probability of excluding satellites and switching to the Ifree mode for both GAST F and X, thereby increasing the availability of GBAS.
{"title":"Performance Evaluation of the Ionospheric Threat Mitigation Strategies in Dual-Frequency Multi-Constellation GBAS","authors":"M. Caamano, Daniel Gerbeth, H. Sato, Mihaela‐Simona Circiu, M. Felux","doi":"10.1109/PLANS53410.2023.10140062","DOIUrl":"https://doi.org/10.1109/PLANS53410.2023.10140062","url":null,"abstract":"In this paper, we evaluate the performance of the dual-frequency airborne ionospheric gradient monitor proposed for dual-frequency multi-constellation (DFMC) Ground Based Augmentation Systems (GBAS) at different distances from the airport. We use two types of thresholds for this assessment: (i) a constant threshold derived from operational requirements, and (ii) a dynamic threshold that increases with the distance from the airport. Increasing the threshold allows more ionospheric error within the position solution, but also enables the use of the primary single-frequency modes without the need to switch to the ionosphere-free (Ifree) solution for a longer period, which generally degrades the performance because it combines the noise and multipath of two frequencies. Furthermore, we compare the performance of the two potential architectures for DFMC GBAS: (i) the so-called GAST F architecture, which is based on single-frequency 100 seconds smoothing, and (ii) the GAST X architecture, which is based on divergence-free (Dfree) smoothing with variable and potentially longer smoothing time constants. Results with both simulated and real data show that the use of a variable threshold significantly reduces the probability of excluding satellites and switching to the Ifree mode for both GAST F and X, thereby increasing the availability of GBAS.","PeriodicalId":344794,"journal":{"name":"2023 IEEE/ION Position, Location and Navigation Symposium (PLANS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124292019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-24DOI: 10.1109/PLANS53410.2023.10140010
Lars Grundhöfer, F. Rizzi, Niklas Hehenkamp, S. Gewies
Medium frequency R-Mode is a candidate to providing backup for positioning navigation, and timing, in case of an outage of the Global Navigation Satellite Systems. Its implementation and first results have shown good performance in the R-Mode Baltic Sea test bed. However, to make the technology available to a broad user group, the availability of a cost-efficient receiver is crucial. In this work, we compare four different implementations of SDR-based receivers for medium frequency R-Mode. More specifically, the performances of a LimeSDR, a RTL-SDR and the higher priced Ettus ecosystem will be presented. In addition, an oscilloscope is as SDR. Furthermore, the paper presents a GNUradio-based R-Mode receiver implementation, which is able to perform real-time positioning on the beat signal of the R-Mode signal for static cases with Hardware in the loop testing.
{"title":"Low Cost SDR Receiver for Medium Frequency R-Mode","authors":"Lars Grundhöfer, F. Rizzi, Niklas Hehenkamp, S. Gewies","doi":"10.1109/PLANS53410.2023.10140010","DOIUrl":"https://doi.org/10.1109/PLANS53410.2023.10140010","url":null,"abstract":"Medium frequency R-Mode is a candidate to providing backup for positioning navigation, and timing, in case of an outage of the Global Navigation Satellite Systems. Its implementation and first results have shown good performance in the R-Mode Baltic Sea test bed. However, to make the technology available to a broad user group, the availability of a cost-efficient receiver is crucial. In this work, we compare four different implementations of SDR-based receivers for medium frequency R-Mode. More specifically, the performances of a LimeSDR, a RTL-SDR and the higher priced Ettus ecosystem will be presented. In addition, an oscilloscope is as SDR. Furthermore, the paper presents a GNUradio-based R-Mode receiver implementation, which is able to perform real-time positioning on the beat signal of the R-Mode signal for static cases with Hardware in the loop testing.","PeriodicalId":344794,"journal":{"name":"2023 IEEE/ION Position, Location and Navigation Symposium (PLANS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129864108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-24DOI: 10.1109/PLANS53410.2023.10139933
Sheikh Arif Raihan, Sanat K. Biswas, A. Dempster
A horizontal protection level (HPL) calculation framework for the integrity monitoring of a highly non-linear dynamic system (space launch vehicle) is presented. The protection level is calculated after outlier detection is performed in the faulty measurement sets. The Unscented Kalman Filter (UKF) concept is adopted for the state estimation and protection level calculation for the launch vehicle. The minimum detectable bias obtained from the outlier detection strategy and the innovation covariance from the UKF are used to calculate the protection level which satisfies the conditions of nominal operations. This framework is tested using simulated global navigation satellite system (GNSS) pseudorange measurements and the second order differential equations of the launch vehicle dynamics.
{"title":"Unscented Kalman Filter Based Protection Level for the Integrity of Space Launch Vehicle","authors":"Sheikh Arif Raihan, Sanat K. Biswas, A. Dempster","doi":"10.1109/PLANS53410.2023.10139933","DOIUrl":"https://doi.org/10.1109/PLANS53410.2023.10139933","url":null,"abstract":"A horizontal protection level (HPL) calculation framework for the integrity monitoring of a highly non-linear dynamic system (space launch vehicle) is presented. The protection level is calculated after outlier detection is performed in the faulty measurement sets. The Unscented Kalman Filter (UKF) concept is adopted for the state estimation and protection level calculation for the launch vehicle. The minimum detectable bias obtained from the outlier detection strategy and the innovation covariance from the UKF are used to calculate the protection level which satisfies the conditions of nominal operations. This framework is tested using simulated global navigation satellite system (GNSS) pseudorange measurements and the second order differential equations of the launch vehicle dynamics.","PeriodicalId":344794,"journal":{"name":"2023 IEEE/ION Position, Location and Navigation Symposium (PLANS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116176584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-24DOI: 10.1109/PLANS53410.2023.10139928
J. Blanch, T. Walter
Protection Levels in RAIM and Advanced RAIM are designed to protect against worst-case biases in the satellite or combination of satellites that could be faulted. When examining the curves of probability of missed detection as a function of magnitude, this may seem to be an excessively conservative requirement, given that the fault biases are unknown (and therefore random to a certain extent). In this note, we consider relaxations of this worst-case requirement by assuming that the fault biases have known distribution. We find that even optimistic distributions of the fault biases are unlikely to yield significant benefits in typical ARAIM scenarios.
{"title":"An Evaluation of the Advanced RAIM Threat Model","authors":"J. Blanch, T. Walter","doi":"10.1109/PLANS53410.2023.10139928","DOIUrl":"https://doi.org/10.1109/PLANS53410.2023.10139928","url":null,"abstract":"Protection Levels in RAIM and Advanced RAIM are designed to protect against worst-case biases in the satellite or combination of satellites that could be faulted. When examining the curves of probability of missed detection as a function of magnitude, this may seem to be an excessively conservative requirement, given that the fault biases are unknown (and therefore random to a certain extent). In this note, we consider relaxations of this worst-case requirement by assuming that the fault biases have known distribution. We find that even optimistic distributions of the fault biases are unlikely to yield significant benefits in typical ARAIM scenarios.","PeriodicalId":344794,"journal":{"name":"2023 IEEE/ION Position, Location and Navigation Symposium (PLANS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122345211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-24DOI: 10.1109/PLANS53410.2023.10139949
Mohanad Ahmed, Tarig Ballal, Xing Liu, T. Al-Naffouri
We consider the problem of detecting and mitigating the effect of multipath on GNSS observations. In particular, we focus on carrier-phase observations that are collected at an array of GNSS antennas. We exploit a special antenna array geometry, synchronization among the GNSS receivers, and an attitude estimate provided by an attitude filter or an IMU, to develop a technique to identify the satellite observations that are contaminated with multipath. The proposed technique leverages the antenna geometry to rabidly estimate the attitude parameters for various satellite combinations. Next, a dedicated decision-making algorithm is used to identify the satellite observations affected by multipath. Our simulation results demonstrate the effectiveness of the proposed approach in detecting the occurrence of multipath with high success rates. By rejecting the multipath-affected observations, we show remarkable performance gains when attitude determination is considered as an example application.
{"title":"Multipath Detection and Mitigation from GNSS Observations Using Antenna Arrays","authors":"Mohanad Ahmed, Tarig Ballal, Xing Liu, T. Al-Naffouri","doi":"10.1109/PLANS53410.2023.10139949","DOIUrl":"https://doi.org/10.1109/PLANS53410.2023.10139949","url":null,"abstract":"We consider the problem of detecting and mitigating the effect of multipath on GNSS observations. In particular, we focus on carrier-phase observations that are collected at an array of GNSS antennas. We exploit a special antenna array geometry, synchronization among the GNSS receivers, and an attitude estimate provided by an attitude filter or an IMU, to develop a technique to identify the satellite observations that are contaminated with multipath. The proposed technique leverages the antenna geometry to rabidly estimate the attitude parameters for various satellite combinations. Next, a dedicated decision-making algorithm is used to identify the satellite observations affected by multipath. Our simulation results demonstrate the effectiveness of the proposed approach in detecting the occurrence of multipath with high success rates. By rejecting the multipath-affected observations, we show remarkable performance gains when attitude determination is considered as an example application.","PeriodicalId":344794,"journal":{"name":"2023 IEEE/ION Position, Location and Navigation Symposium (PLANS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125763915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-24DOI: 10.1109/PLANS53410.2023.10139978
Burak Turan, Halil Ozan Ünsal
Inertial Navigation Systems (INS) are the main part of the integrated navigation for most of the aerial vehicles. However, the accuracy of an inertial navigation solution decreases with time as the inertial instrument (e.g., gyroscope and accelerometer) errors are integrated through the navigation equations. Therefore, different aiding techniques are used to limit the drift in these systems. One of the commonly used techniques is the integration of INS with Global Navigation Satellite System (GNSS) signals. By means of this integration, the advantages of both technologies are combined to give a complete and accurate navigation solution. However, GNSS signals travelled from the satellites to the receiver are at a very low power level. This low power level makes the signals susceptible to interference from other unintentional or intentional signals transmitted in the GNSS frequency range. If the interfering signal is sufficiently powerful, it becomes impossible for the receiver to detect the low power GNSS signal. There are different types of interference signals like jamming and spoofing. GNSS jamming, also referred as intentional jamming, is when a jammer generates sufficiently powerful disruptive noise signals at frequency bands used by a GNSS system in order to prevent GNSS receivers from tracking signals and calculating reliable navigation data. As for GNSS spoofing, unlike jamming, deceives the receiver into calculating an incorrect navigation data by generating a false signal that is either created by a signal generator or is a replica of a real recorded GNSS signal. The need for Terrain Referenced Navigation (TRN) arises when these GNSS signals are unavailable, jammed or blocked. In recent years, research on the application of TRN to aerial vehicles has been increased rapidly with the developments in the accuracy of digital terrain elevation database (DTED). Since the land profile is inherently nonlinear, TRN becomes a nonlinear estimation problem. Because of the highly nonlinear problem, linear or linearized estimation techniques such as Kalman or Extended Kalman Filter (EKF) do not work properly for many terrain profiles. In our previously published works, we already presented the nonlinear estimation techniques that can be suitable for the solution of TRN problem. In this paper, we move onto the real-time application of TRN algorithm and present an overview of the real-time flight test results. Thanks to our previous research, a nonlinear filtering method namely the Unscented Kalman Filter (UKF) based on the Unscented Transform (UT) of sigma points is selected and utilized for the real-time solution of problem due to its simplicity and low processor capacity requirement. The designed UKF algorithm is used to provide essentially continuous terrain navigation through closed-loop estimation of navigation errors in combination with fixed-angle-mounted laser altimeter ground clearance measurements and onboard Level-1 DTED obtained from open i
{"title":"Flight Test Results of Terrain Referenced Aircraft Navigation with Laser Altimeter","authors":"Burak Turan, Halil Ozan Ünsal","doi":"10.1109/PLANS53410.2023.10139978","DOIUrl":"https://doi.org/10.1109/PLANS53410.2023.10139978","url":null,"abstract":"Inertial Navigation Systems (INS) are the main part of the integrated navigation for most of the aerial vehicles. However, the accuracy of an inertial navigation solution decreases with time as the inertial instrument (e.g., gyroscope and accelerometer) errors are integrated through the navigation equations. Therefore, different aiding techniques are used to limit the drift in these systems. One of the commonly used techniques is the integration of INS with Global Navigation Satellite System (GNSS) signals. By means of this integration, the advantages of both technologies are combined to give a complete and accurate navigation solution. However, GNSS signals travelled from the satellites to the receiver are at a very low power level. This low power level makes the signals susceptible to interference from other unintentional or intentional signals transmitted in the GNSS frequency range. If the interfering signal is sufficiently powerful, it becomes impossible for the receiver to detect the low power GNSS signal. There are different types of interference signals like jamming and spoofing. GNSS jamming, also referred as intentional jamming, is when a jammer generates sufficiently powerful disruptive noise signals at frequency bands used by a GNSS system in order to prevent GNSS receivers from tracking signals and calculating reliable navigation data. As for GNSS spoofing, unlike jamming, deceives the receiver into calculating an incorrect navigation data by generating a false signal that is either created by a signal generator or is a replica of a real recorded GNSS signal. The need for Terrain Referenced Navigation (TRN) arises when these GNSS signals are unavailable, jammed or blocked. In recent years, research on the application of TRN to aerial vehicles has been increased rapidly with the developments in the accuracy of digital terrain elevation database (DTED). Since the land profile is inherently nonlinear, TRN becomes a nonlinear estimation problem. Because of the highly nonlinear problem, linear or linearized estimation techniques such as Kalman or Extended Kalman Filter (EKF) do not work properly for many terrain profiles. In our previously published works, we already presented the nonlinear estimation techniques that can be suitable for the solution of TRN problem. In this paper, we move onto the real-time application of TRN algorithm and present an overview of the real-time flight test results. Thanks to our previous research, a nonlinear filtering method namely the Unscented Kalman Filter (UKF) based on the Unscented Transform (UT) of sigma points is selected and utilized for the real-time solution of problem due to its simplicity and low processor capacity requirement. The designed UKF algorithm is used to provide essentially continuous terrain navigation through closed-loop estimation of navigation errors in combination with fixed-angle-mounted laser altimeter ground clearance measurements and onboard Level-1 DTED obtained from open i","PeriodicalId":344794,"journal":{"name":"2023 IEEE/ION Position, Location and Navigation Symposium (PLANS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133659415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-24DOI: 10.1109/PLANS53410.2023.10139968
S. Nayak, Guoyuan Wu, M. Barth, Yongkang Liu, E. A. Sisbot, K. Oguchi
Vehicle positioning and tracking is a key component of Intelligent Transportation Systems (ITS). Cooperative positioning techniques through vehicle-to-vehicle (V2V) or vehicle-to-infrastructure (V2I) information sharing can improve the existing proprioceptive based positioning systems such as Global Navigation Satellite System (GNSS) which are prone to errors due to urban canyons, signal jamming, etc. V2V-based positioning might not fulfill all positioning needs, given the low Connected and Automated Vehicle (CAV) penetration in today's traffic. In these scenarios, infrastructure sensors can assist the vehicles in estimating the state of the traffic through I2V communication. The state estimation requires fusion between the infrastructure and the on-board sensor measurements which are often multi-rate and asynchronous in nature. Moreover, the measurements from the infrastructure might be delayed and not time-synchronized with other sensors. Hence, it is imperative to address the practical problems while designing a sensor fusion framework for fusing multiple sensor measurements in a real world scenario. This paper aims at evaluating the improvement in vehicle tracking by fusing roadside LiDAR measurements with the on-board GPS position measurements. Various motion models for the vehicle are studied and implemented with a sequential Kalman filter for estimating the vehicle states.
{"title":"Evaluation of Infrastructure-Assisted Cooperative Tracking of Vehicles Using Various Motion Models","authors":"S. Nayak, Guoyuan Wu, M. Barth, Yongkang Liu, E. A. Sisbot, K. Oguchi","doi":"10.1109/PLANS53410.2023.10139968","DOIUrl":"https://doi.org/10.1109/PLANS53410.2023.10139968","url":null,"abstract":"Vehicle positioning and tracking is a key component of Intelligent Transportation Systems (ITS). Cooperative positioning techniques through vehicle-to-vehicle (V2V) or vehicle-to-infrastructure (V2I) information sharing can improve the existing proprioceptive based positioning systems such as Global Navigation Satellite System (GNSS) which are prone to errors due to urban canyons, signal jamming, etc. V2V-based positioning might not fulfill all positioning needs, given the low Connected and Automated Vehicle (CAV) penetration in today's traffic. In these scenarios, infrastructure sensors can assist the vehicles in estimating the state of the traffic through I2V communication. The state estimation requires fusion between the infrastructure and the on-board sensor measurements which are often multi-rate and asynchronous in nature. Moreover, the measurements from the infrastructure might be delayed and not time-synchronized with other sensors. Hence, it is imperative to address the practical problems while designing a sensor fusion framework for fusing multiple sensor measurements in a real world scenario. This paper aims at evaluating the improvement in vehicle tracking by fusing roadside LiDAR measurements with the on-board GPS position measurements. Various motion models for the vehicle are studied and implemented with a sequential Kalman filter for estimating the vehicle states.","PeriodicalId":344794,"journal":{"name":"2023 IEEE/ION Position, Location and Navigation Symposium (PLANS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128282561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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