Pub Date : 2023-04-24DOI: 10.1109/PLANS53410.2023.10140088
G. Olsson, Sara Nilsson, E. Axell, E. Larsson, Panos Papadimitratos
It is well known that GNSS receivers are vulnerable to jamming and spoofing attacks, and numerous such incidents have been reported in the last decade all over the world. The notion of participatory sensing, or crowds ensing, is that a large ensemble of voluntary contributors provides measurements, rather than relying on a dedicated sensing infrastructure. The participatory sensing network under consideration in this work is based on GNSS receivers embedded in, for example, mobile phones. The provided measurements refer to the receiver-reported carrier-to-noise-density ratio ($C / N_{0}$) estimates or automatic gain control (AGC) values. In this work, we exploit $C / N_{0}$ measurements to locate a GNSS jammer, using multiple receivers in a crowdsourcing manner. We extend a previous jammer position estimator by only including data that is received during parts of the sensing period where jamming is detected by the sensor. In addition, we perform hardware testing for verification and evaluation of the proposed and compared state-of-the-art algorithms. Evaluations are performed using a Samsung S20+ mobile phone as participatory sensor and a Spirent GSS9000 GNSS simulator to generate GNSS and jamming signals. The proposed algorithm is shown to work well when using $C / N_{0}$ measurements and outperform the alternative algorithms in the evaluated scenarios, producing a median error of 50 meters when the pathloss exponent is 2. With higher pathloss exponents the error gets higher. The AGC output from the phone was too noisy and needs further processing to be useful for position estimation.
{"title":"Using Mobile Phones for Participatory Detection and Localization of a GNSS Jammer","authors":"G. Olsson, Sara Nilsson, E. Axell, E. Larsson, Panos Papadimitratos","doi":"10.1109/PLANS53410.2023.10140088","DOIUrl":"https://doi.org/10.1109/PLANS53410.2023.10140088","url":null,"abstract":"It is well known that GNSS receivers are vulnerable to jamming and spoofing attacks, and numerous such incidents have been reported in the last decade all over the world. The notion of participatory sensing, or crowds ensing, is that a large ensemble of voluntary contributors provides measurements, rather than relying on a dedicated sensing infrastructure. The participatory sensing network under consideration in this work is based on GNSS receivers embedded in, for example, mobile phones. The provided measurements refer to the receiver-reported carrier-to-noise-density ratio ($C / N_{0}$) estimates or automatic gain control (AGC) values. In this work, we exploit $C / N_{0}$ measurements to locate a GNSS jammer, using multiple receivers in a crowdsourcing manner. We extend a previous jammer position estimator by only including data that is received during parts of the sensing period where jamming is detected by the sensor. In addition, we perform hardware testing for verification and evaluation of the proposed and compared state-of-the-art algorithms. Evaluations are performed using a Samsung S20+ mobile phone as participatory sensor and a Spirent GSS9000 GNSS simulator to generate GNSS and jamming signals. The proposed algorithm is shown to work well when using $C / N_{0}$ measurements and outperform the alternative algorithms in the evaluated scenarios, producing a median error of 50 meters when the pathloss exponent is 2. With higher pathloss exponents the error gets higher. The AGC output from the phone was too noisy and needs further processing to be useful for position estimation.","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":"124404696","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/PLANS53410.2023.10139947
Aabhash Bhandari, T. Luong, Jordan D. Larson
This paper presents a software architecture for performing snow water equivalent (SWE) measurements remotely using Common Midpoint Radar (CMR) and two Unmanned Aerial Vehicles (UAV). CMR enables remote sensing of snow dielectric constant, and when combined with snow depth measurements, allows for estimation of SWE in snow covered areas. This paper discusses the development of a custom graphical user interface (GUI) ground control station (GCS) that was used for performing cooperative flight operation with two UAVs for CMR measurements. It presents the software architecture of the GCS which enables command and control, realtime telemetry, planning, and tracking of multiple vehicles in a network. It also introduces aspects of flight planning and antenna gimbal system used in CMR operation. Preliminary results from Ardupilot software-in-the-loop (SITL) simulations and initial flight tests are also presented.
{"title":"Cooperative Guidance and Navigation of UAS for Common Midpoint Radar Remote Sensing","authors":"Aabhash Bhandari, T. Luong, Jordan D. Larson","doi":"10.1109/PLANS53410.2023.10139947","DOIUrl":"https://doi.org/10.1109/PLANS53410.2023.10139947","url":null,"abstract":"This paper presents a software architecture for performing snow water equivalent (SWE) measurements remotely using Common Midpoint Radar (CMR) and two Unmanned Aerial Vehicles (UAV). CMR enables remote sensing of snow dielectric constant, and when combined with snow depth measurements, allows for estimation of SWE in snow covered areas. This paper discusses the development of a custom graphical user interface (GUI) ground control station (GCS) that was used for performing cooperative flight operation with two UAVs for CMR measurements. It presents the software architecture of the GCS which enables command and control, realtime telemetry, planning, and tracking of multiple vehicles in a network. It also introduces aspects of flight planning and antenna gimbal system used in CMR operation. Preliminary results from Ardupilot software-in-the-loop (SITL) simulations and initial flight tests are also presented.","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":"124985670","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/PLANS53410.2023.10140022
Cheng-Wei Wang, Shau-Shiun Jan
With the development of intelligent transportation systems, precise point positioning (PPP) has attracted increasing research attention because of its high accuracy and flexibility. Real-time, fast-convergence PPP can be implemented using free regional augmentation signals that broadcast correction messages for satellite orbit and clock bias. In this study, PPP was combined with Quasi-Zenith Satellite System multi-global navigation satellite system (GNSS) advanced orbit and clock augmentation (MADOCA). Furthermore, integrity monitoring was implemented for MADOCA-PPP in terrestrial applications. Localization integrity is an essential criterion for evaluating whether a navigation solution is trustworthy, and this criterion has been widely used in the GNSS. In this study, integrity monitoring was performed using an ionosphere-free combination of the GPS and GLONASS according to the corresponding MADOCA -corrected residuals. The residual characterization indicated that a Kalman filter-based chi-square test is suitable for conducting fault detection and exclusion. Simulated one or two satellite steps, and ramp faults can be appropriately excluded, which reveals the system's capability for rejecting outliers from abnormal measurements. To construct the error bound for a certain integrity risk, the protection level, which has a Student's t-distribution, was computed. The experimental results were validated in static and kinematic scenarios to assess the integrity and positioning performance of MADOCA-PPP.
{"title":"Kalman Filter-Based Integrity Monitoring for MADOCA - PPP in Terrestrial Applications","authors":"Cheng-Wei Wang, Shau-Shiun Jan","doi":"10.1109/PLANS53410.2023.10140022","DOIUrl":"https://doi.org/10.1109/PLANS53410.2023.10140022","url":null,"abstract":"With the development of intelligent transportation systems, precise point positioning (PPP) has attracted increasing research attention because of its high accuracy and flexibility. Real-time, fast-convergence PPP can be implemented using free regional augmentation signals that broadcast correction messages for satellite orbit and clock bias. In this study, PPP was combined with Quasi-Zenith Satellite System multi-global navigation satellite system (GNSS) advanced orbit and clock augmentation (MADOCA). Furthermore, integrity monitoring was implemented for MADOCA-PPP in terrestrial applications. Localization integrity is an essential criterion for evaluating whether a navigation solution is trustworthy, and this criterion has been widely used in the GNSS. In this study, integrity monitoring was performed using an ionosphere-free combination of the GPS and GLONASS according to the corresponding MADOCA -corrected residuals. The residual characterization indicated that a Kalman filter-based chi-square test is suitable for conducting fault detection and exclusion. Simulated one or two satellite steps, and ramp faults can be appropriately excluded, which reveals the system's capability for rejecting outliers from abnormal measurements. To construct the error bound for a certain integrity risk, the protection level, which has a Student's t-distribution, was computed. The experimental results were validated in static and kinematic scenarios to assess the integrity and positioning performance of MADOCA-PPP.","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":"126711714","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/PLANS53410.2023.10140114
G. McGraw, Gianluca Zampieri, Alexandra Filip-Dhaubhadel, O. Osechas, M. Meurer
This paper presents recent developments towards an LDACS Alternative Positioning, Navigation and Timing (APNT) capability. The focus is on refinement of key error budget components including multipath and airborne radio clock estimation error from two-way timing and ranging processing. In addition, the impact of airborne radio transmitter power control on ranging errors and operational APNT availability is assessed.
{"title":"LDACS APNT Architecture Development & Evolution","authors":"G. McGraw, Gianluca Zampieri, Alexandra Filip-Dhaubhadel, O. Osechas, M. Meurer","doi":"10.1109/PLANS53410.2023.10140114","DOIUrl":"https://doi.org/10.1109/PLANS53410.2023.10140114","url":null,"abstract":"This paper presents recent developments towards an LDACS Alternative Positioning, Navigation and Timing (APNT) capability. The focus is on refinement of key error budget components including multipath and airborne radio clock estimation error from two-way timing and ranging processing. In addition, the impact of airborne radio transmitter power control on ranging errors and operational APNT availability is assessed.","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":"115455217","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/PLANS53410.2023.10140071
P. Rudnik, L. Kurz, A. Winterstein, M. Cuntz
To strengthen tracking in dynamic flight maneuvers the miniaturized real-time Global Navigation Satellite System (GNSS) receiver GALileo ANTenna (GALANT), developed by the German Aerospace Center (DLR), has been equipped with a robust vector tracking algorithm. To harden the receiver the algorithm used on the platform excludes Non-Line-Of-Sight signals by exploiting spatial information gained by the 2×2 antenna array and its processing. This contribution focuses on the planning, execution and evaluation of the experimental validation of the receiver and its tracking algorithm by conduction of open field flight test in the rural area near Munich. The developed system was fitted as payload to a compact hexacopter and the potential benefits in signal tracking are investigated, while the algorithm relies on GNSS information only and uses no other sensor data input such as Inertial Measurement Unit (IMU) or compass. The receiver has been developed to be resilient to intentional and unintentional interference from diverse origins based on spatial suppression of jamming sources, which has been proven in previous tests. Performing these techniques also suppresses satellite signals impinging from the direction of the interference source, which need to be recovered. To test the performance of the implemented vector tracking algorithm with respect to the signal recovery, the receiver is exposed to a jamming source on ground while changing the constellation.
{"title":"Capabilities of a Real-Time EKF Vector Tracking Algorithm for Dynamic Flight Maneuvers With Small UAVs","authors":"P. Rudnik, L. Kurz, A. Winterstein, M. Cuntz","doi":"10.1109/PLANS53410.2023.10140071","DOIUrl":"https://doi.org/10.1109/PLANS53410.2023.10140071","url":null,"abstract":"To strengthen tracking in dynamic flight maneuvers the miniaturized real-time Global Navigation Satellite System (GNSS) receiver GALileo ANTenna (GALANT), developed by the German Aerospace Center (DLR), has been equipped with a robust vector tracking algorithm. To harden the receiver the algorithm used on the platform excludes Non-Line-Of-Sight signals by exploiting spatial information gained by the 2×2 antenna array and its processing. This contribution focuses on the planning, execution and evaluation of the experimental validation of the receiver and its tracking algorithm by conduction of open field flight test in the rural area near Munich. The developed system was fitted as payload to a compact hexacopter and the potential benefits in signal tracking are investigated, while the algorithm relies on GNSS information only and uses no other sensor data input such as Inertial Measurement Unit (IMU) or compass. The receiver has been developed to be resilient to intentional and unintentional interference from diverse origins based on spatial suppression of jamming sources, which has been proven in previous tests. Performing these techniques also suppresses satellite signals impinging from the direction of the interference source, which need to be recovered. To test the performance of the implemented vector tracking algorithm with respect to the signal recovery, the receiver is exposed to a jamming source on ground while changing the constellation.","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":"122617304","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/PLANS53410.2023.10139946
Susanna Kaiser, Pierre Baudet, Ni Zhu, V. Renaudin
In highly shared urban traffic environments, it is essential to protect Vulnerable Road Users (VRU) to avoid collisions with motorized transport. One approach is to predict the intention or the future trajectories of the VRU from their previous path in order to send warnings in case of danger, or even to brake the cars in case of using driver assistance systems. The main objective of this paper is to investigate the short-term and particularly long-term prediction abilities of the AI-based predictors assisted with environmental maps, if applicable. By comparing and evaluating the performance of Polynomial Regression (PR), Gaussian Process Regression (GPR), Convolutional Neural Network (CNN), and Sequence-to-sequence neural networks (SeqToSeq) applied on an open access data set (i.e., Stanford Drone Dataset (SDD)) as well as some simulated data, we can conclude that the SeqToSeq generally performs better than other methods (Average Displacement Error is 25% lower and Final Displacement Error is 20% lower compared to a first order PR). By adding the environmental maps (navigation map and diffusion map), the pedestrian's turnings are better predicted despite the fact that there is little improvement on other metrics. This can be explained by an insufficient amount of training data involving environmental maps in this research work. Thus it is still promising by adding more training data with environmental maps in the future.
{"title":"Investigations on pedestrian long-term trajectory prediction based on AI and environmental maps","authors":"Susanna Kaiser, Pierre Baudet, Ni Zhu, V. Renaudin","doi":"10.1109/PLANS53410.2023.10139946","DOIUrl":"https://doi.org/10.1109/PLANS53410.2023.10139946","url":null,"abstract":"In highly shared urban traffic environments, it is essential to protect Vulnerable Road Users (VRU) to avoid collisions with motorized transport. One approach is to predict the intention or the future trajectories of the VRU from their previous path in order to send warnings in case of danger, or even to brake the cars in case of using driver assistance systems. The main objective of this paper is to investigate the short-term and particularly long-term prediction abilities of the AI-based predictors assisted with environmental maps, if applicable. By comparing and evaluating the performance of Polynomial Regression (PR), Gaussian Process Regression (GPR), Convolutional Neural Network (CNN), and Sequence-to-sequence neural networks (SeqToSeq) applied on an open access data set (i.e., Stanford Drone Dataset (SDD)) as well as some simulated data, we can conclude that the SeqToSeq generally performs better than other methods (Average Displacement Error is 25% lower and Final Displacement Error is 20% lower compared to a first order PR). By adding the environmental maps (navigation map and diffusion map), the pedestrian's turnings are better predicted despite the fact that there is little improvement on other metrics. This can be explained by an insufficient amount of training data involving environmental maps in this research work. Thus it is still promising by adding more training data with environmental maps in the future.","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":"129584422","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/PLANS53410.2023.10140019
Andrew Moore, Julian Gutierrez, Evan Dill, Michael Logan, J. S. Glover, S. Young, Nathan Hoege
Low altitude flight in urban areas is susceptible to degraded GNSS-based navigation system performance due to terrain interference with radio signals from orbital positioning satellites. Predictive navigation performance fidelity tools are needed a) in preflight planning to assist in the creation of safe flight paths and b) in-flight to provide contingency management agents with the navigation risk of proximal flight corridors. Two navigation fidelity prediction services are validated by comparison with over 6000 readings from GNSS sensors collected along a five-mile path through urban areas of Corpus Christi, Texas, on three dates in 2022. Predictions are based on satellite line of sight through 3D terrain data collected in 2018. Each service predicts a set of navigation fidelity metrics over a user-specified time period. One metric estimated by both is the number of visible satellites. A direct comparison of the number of predicted visible satellites with the number sensed by the receiver is used to validate the prediction services. Results show an exact match in the number of predicted satellites for 60% of the measurements, and a match within +/- 4 satellites for 95% of the measurements. As expected, agreement improves away from vertical blocking terrain. Most cases of mismatch are due a lower predicted count than measured (false negatives), and can be accounted for by receiver pickup of stray signals caused by multipath propagation. About 10% of mismatches are false positives and are mostly accounted for by foliage effects. The two services predict visibility of the same set of satellites 80% of the time, differ by two or less satellites 95% of the time, and can compute predictions for one hour of observations in one minute or less. Validation is analyzed statistically and in detailed case studies of selected observation times. The prediction services validated in this study run fast enough for preflight safety planning. The more stringent challenge of in-flight navigation fidelity prediction for contingency management requires both a speedup of the current level of modeling and equally fast stray signal modeling.
{"title":"Accuracy Assessment of Two GPS Fidelity Prediction Services in Urban Terrain","authors":"Andrew Moore, Julian Gutierrez, Evan Dill, Michael Logan, J. S. Glover, S. Young, Nathan Hoege","doi":"10.1109/PLANS53410.2023.10140019","DOIUrl":"https://doi.org/10.1109/PLANS53410.2023.10140019","url":null,"abstract":"Low altitude flight in urban areas is susceptible to degraded GNSS-based navigation system performance due to terrain interference with radio signals from orbital positioning satellites. Predictive navigation performance fidelity tools are needed a) in preflight planning to assist in the creation of safe flight paths and b) in-flight to provide contingency management agents with the navigation risk of proximal flight corridors. Two navigation fidelity prediction services are validated by comparison with over 6000 readings from GNSS sensors collected along a five-mile path through urban areas of Corpus Christi, Texas, on three dates in 2022. Predictions are based on satellite line of sight through 3D terrain data collected in 2018. Each service predicts a set of navigation fidelity metrics over a user-specified time period. One metric estimated by both is the number of visible satellites. A direct comparison of the number of predicted visible satellites with the number sensed by the receiver is used to validate the prediction services. Results show an exact match in the number of predicted satellites for 60% of the measurements, and a match within +/- 4 satellites for 95% of the measurements. As expected, agreement improves away from vertical blocking terrain. Most cases of mismatch are due a lower predicted count than measured (false negatives), and can be accounted for by receiver pickup of stray signals caused by multipath propagation. About 10% of mismatches are false positives and are mostly accounted for by foliage effects. The two services predict visibility of the same set of satellites 80% of the time, differ by two or less satellites 95% of the time, and can compute predictions for one hour of observations in one minute or less. Validation is analyzed statistically and in detailed case studies of selected observation times. The prediction services validated in this study run fast enough for preflight safety planning. The more stringent challenge of in-flight navigation fidelity prediction for contingency management requires both a speedup of the current level of modeling and equally fast stray signal modeling.","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":"129774999","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/PLANS53410.2023.10140028
Hanyuan Fu, Thomas Bonis, V. Renaudin, Ni Zhu
In this paper, we propose an image-based neural network approach (PatternNet) for walking direction estimation with wearable inertial sensors. Gait event segmentation and projection are used to convert the inertial signals to image-like tabular samples, from which a Convolutional neural network (CNN) extracts geometrical features for walking direction inference. To embrace the diversity of individual walking characteristics and different ways to carry the device, tailor-made models are constructed based on individual users' gait characteristics and the device-carrying mode. Experimental assessments of the proposed method and a competing method (RoNIN) are carried out in real-life situations and over 3 km total walking distance, covering indoor and outdoor environments, involving both sighted and visually impaired volunteers carrying the device in three different ways: texting, swinging and in a jacket pocket. PatternNet estimates the walking directions with a mean accuracy between 7 to 10 degrees for the three test persons and is 1.5 times better than RONIN estimates.
{"title":"A Computer Vision Approach for Pedestrian Walking Direction Estimation with Wearable Inertial Sensors: PatternNet","authors":"Hanyuan Fu, Thomas Bonis, V. Renaudin, Ni Zhu","doi":"10.1109/PLANS53410.2023.10140028","DOIUrl":"https://doi.org/10.1109/PLANS53410.2023.10140028","url":null,"abstract":"In this paper, we propose an image-based neural network approach (PatternNet) for walking direction estimation with wearable inertial sensors. Gait event segmentation and projection are used to convert the inertial signals to image-like tabular samples, from which a Convolutional neural network (CNN) extracts geometrical features for walking direction inference. To embrace the diversity of individual walking characteristics and different ways to carry the device, tailor-made models are constructed based on individual users' gait characteristics and the device-carrying mode. Experimental assessments of the proposed method and a competing method (RoNIN) are carried out in real-life situations and over 3 km total walking distance, covering indoor and outdoor environments, involving both sighted and visually impaired volunteers carrying the device in three different ways: texting, swinging and in a jacket pocket. PatternNet estimates the walking directions with a mean accuracy between 7 to 10 degrees for the three test persons and is 1.5 times better than RONIN estimates.","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":"128486142","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/PLANS53410.2023.10140037
Satoki Ogiso, Ikue Mori, Takahiro Miura, S. Nakae, T. Okuma, Yasunori Haga, Shintaro Hatakeyama, Kengo Kimura, Atsushi Kimura, Takeshi Kurata
In this paper, a particle filter that integrates proximity detection via Bluetooth Low Energy (BLE) is proposed. The proposed particle filter provides intermittent but reliable location coordinates. As a result, particles do not disappear from their original locations even over long measurement periods. The proposed method was evaluated in two real-world factory environments over 13 days with a total of 33 factory workers. A total of 901.5 and 1320.2 hours of data were measured in factory 1 and factory 2, respectively. From the measured data, we confirmed that the proposed method could measure typical flow lines for each worker role throughout the experimental period. We report on the measured data by comparing the results of the flow line measurement for the workers' roles and the location estimation results for the received BLE signal obtained throughout the experimental period.
{"title":"Integration of BLE-based proximity detection with particle filter for day-long stability in workplaces","authors":"Satoki Ogiso, Ikue Mori, Takahiro Miura, S. Nakae, T. Okuma, Yasunori Haga, Shintaro Hatakeyama, Kengo Kimura, Atsushi Kimura, Takeshi Kurata","doi":"10.1109/PLANS53410.2023.10140037","DOIUrl":"https://doi.org/10.1109/PLANS53410.2023.10140037","url":null,"abstract":"In this paper, a particle filter that integrates proximity detection via Bluetooth Low Energy (BLE) is proposed. The proposed particle filter provides intermittent but reliable location coordinates. As a result, particles do not disappear from their original locations even over long measurement periods. The proposed method was evaluated in two real-world factory environments over 13 days with a total of 33 factory workers. A total of 901.5 and 1320.2 hours of data were measured in factory 1 and factory 2, respectively. From the measured data, we confirmed that the proposed method could measure typical flow lines for each worker role throughout the experimental period. We report on the measured data by comparing the results of the flow line measurement for the workers' roles and the location estimation results for the received BLE signal obtained throughout the experimental period.","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":"129156112","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/PLANS53410.2023.10140045
J. DeNatale, P. Stupar, S. Martel, J. Lachance
We present recent progress on a high-performance inertial sensor manufacturing processes implemented in a volume compatible 200 mm wafer diameter production environment. The baseline process, derived from Teledyne DALSA's MIDIS™ process platform, incorporates critical design elements specifically designed for navigation-grade device realization. The process enables considerable flexibility to support a broad range of device designs, facilitating the rapid transition of new device concepts to volume production. Recent progress has demonstrated the flexibility of the process through application to alternate gyro resonator device designs. Extensive refinement of the process has been implemented to improve manufacturing metrics and device performance.
{"title":"Manufacturing Platform for High-Performance MEMS Inertial Sensors","authors":"J. DeNatale, P. Stupar, S. Martel, J. Lachance","doi":"10.1109/PLANS53410.2023.10140045","DOIUrl":"https://doi.org/10.1109/PLANS53410.2023.10140045","url":null,"abstract":"We present recent progress on a high-performance inertial sensor manufacturing processes implemented in a volume compatible 200 mm wafer diameter production environment. The baseline process, derived from Teledyne DALSA's MIDIS™ process platform, incorporates critical design elements specifically designed for navigation-grade device realization. The process enables considerable flexibility to support a broad range of device designs, facilitating the rapid transition of new device concepts to volume production. Recent progress has demonstrated the flexibility of the process through application to alternate gyro resonator device designs. Extensive refinement of the process has been implemented to improve manufacturing metrics and device performance.","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":"123441638","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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