Pub Date : 2022-02-07DOI: 10.1017/S0373463322000030
Angel Martín, R. Capilla, A. B. Anquela
Abstract Location and navigation services based on global navigation satellite systems (GNSS) are needed for real-time high-precision positioning applications in relevant economic sectors, such as precision agriculture, transport, civil engineering or mapping. Real-time navigation users of GNSS networks have significantly increased all around the world, since the 1990s, and usage has exceeded initial expectations. Therefore, if the evolution of GNSS network users is monitored, the dynamics of market segments can be studied. The implementation of this hypothesis requires the treatment of big volumes of navigation data over several years and the continuous monitoring of customers. This paper is focused on the management of massive connection of GNSS users in an efficient way, in order to obtain analysis and statistics. Big data architecture and data analyses based on data mining algorithms have been implemented as the best way to approach the hypothesis. Results demonstrate the dynamic of users of different market segments, the increasing demand over the years and, specifically, conclusions are obtained about the trends, year-on-year correlation and business volume recovering after economic crisis periods.
{"title":"Big data architecture and data mining analysis for market segment applications of differential global navigation satellite system (GNSS) services: case study of the analysis of the demand for navigation and agriculture","authors":"Angel Martín, R. Capilla, A. B. Anquela","doi":"10.1017/S0373463322000030","DOIUrl":"https://doi.org/10.1017/S0373463322000030","url":null,"abstract":"Abstract Location and navigation services based on global navigation satellite systems (GNSS) are needed for real-time high-precision positioning applications in relevant economic sectors, such as precision agriculture, transport, civil engineering or mapping. Real-time navigation users of GNSS networks have significantly increased all around the world, since the 1990s, and usage has exceeded initial expectations. Therefore, if the evolution of GNSS network users is monitored, the dynamics of market segments can be studied. The implementation of this hypothesis requires the treatment of big volumes of navigation data over several years and the continuous monitoring of customers. This paper is focused on the management of massive connection of GNSS users in an efficient way, in order to obtain analysis and statistics. Big data architecture and data analyses based on data mining algorithms have been implemented as the best way to approach the hypothesis. Results demonstrate the dynamic of users of different market segments, the increasing demand over the years and, specifically, conclusions are obtained about the trends, year-on-year correlation and business volume recovering after economic crisis periods.","PeriodicalId":50120,"journal":{"name":"Journal of Navigation","volume":"75 1","pages":"421 - 436"},"PeriodicalIF":2.4,"publicationDate":"2022-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42660658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-07DOI: 10.1017/S0373463322000066
Tao Liu, Shuo Wang, Z. Lei, Jinfeng Zhang, Xiaocai Zhang
Abstract When conducting accident analysis, the assessment of risk is one of the important links. Moreover, with regards to crew training, risk cognition is also an important training subject. However, most of the existing researches only rely on a single or a few data sources. It is necessary to fuse the collected multi-source data to obtain a more comprehensive risk evaluation model. There are few studies on the three-dimensional (3D) multi-modal data-fusion-based trajectory risk cognition. In this paper, a fuzzy logic-based trajectory risk cognition method is proposed based on multi-model spatial data fusion and accident data mining. First, the necessity of multi-model spatial data fusion is analysed and a data-fusion-based scene map is constructed. Second, a risk cognition model fused by multiple factors, multi-dimensional spatial calculations as well as data mining results is proposed, including a novel ship boundary calculation approach and newly constructed factors. Finally, a radar chart is used to illustrate the risk, and a risk cognition system is developed. Experiment results confirm the effectiveness of the method. It can be applied to train human operators of unmanned ship systems.
{"title":"Trajectory risk cognition of ship collision accident based on fusion of multi-model spatial data","authors":"Tao Liu, Shuo Wang, Z. Lei, Jinfeng Zhang, Xiaocai Zhang","doi":"10.1017/S0373463322000066","DOIUrl":"https://doi.org/10.1017/S0373463322000066","url":null,"abstract":"Abstract When conducting accident analysis, the assessment of risk is one of the important links. Moreover, with regards to crew training, risk cognition is also an important training subject. However, most of the existing researches only rely on a single or a few data sources. It is necessary to fuse the collected multi-source data to obtain a more comprehensive risk evaluation model. There are few studies on the three-dimensional (3D) multi-modal data-fusion-based trajectory risk cognition. In this paper, a fuzzy logic-based trajectory risk cognition method is proposed based on multi-model spatial data fusion and accident data mining. First, the necessity of multi-model spatial data fusion is analysed and a data-fusion-based scene map is constructed. Second, a risk cognition model fused by multiple factors, multi-dimensional spatial calculations as well as data mining results is proposed, including a novel ship boundary calculation approach and newly constructed factors. Finally, a radar chart is used to illustrate the risk, and a risk cognition system is developed. Experiment results confirm the effectiveness of the method. It can be applied to train human operators of unmanned ship systems.","PeriodicalId":50120,"journal":{"name":"Journal of Navigation","volume":"75 1","pages":"299 - 318"},"PeriodicalIF":2.4,"publicationDate":"2022-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41573446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-21DOI: 10.1017/S0373463321000862
Chenyang Yao, G. Gao, Weijiong Chen, T. Qin, Zhuan Li
Abstract Applying non-accident critical events (NACEs) as an alternative measuring method to assess ship collision risk has become popular in recent years. NACEs has shown temporal features in different waters. This study uses the quaternion ship domain method to identify NACEs around the Yangtze Estuary and adjacent coastal waters from the Automatic Identification System (AIS) data in October 2019. The results indicate that NACEs show different temporal features in estuaries and coastal waters. The relationship between tides, channel types and ships is discussed. In addition, we established a statistical method for the occurrence time of NACEs and the state of tides according to the half-tide level and the nearest time. The outcomes of this study provide a direction for exploring the relationship between NACEs and environmental conditions, which is also instructive for the study of the causes of ship accidents.
{"title":"Temporal features of non-accident critical events impact from tides around the Yangtze Estuary and adjacent coastal waters","authors":"Chenyang Yao, G. Gao, Weijiong Chen, T. Qin, Zhuan Li","doi":"10.1017/S0373463321000862","DOIUrl":"https://doi.org/10.1017/S0373463321000862","url":null,"abstract":"Abstract Applying non-accident critical events (NACEs) as an alternative measuring method to assess ship collision risk has become popular in recent years. NACEs has shown temporal features in different waters. This study uses the quaternion ship domain method to identify NACEs around the Yangtze Estuary and adjacent coastal waters from the Automatic Identification System (AIS) data in October 2019. The results indicate that NACEs show different temporal features in estuaries and coastal waters. The relationship between tides, channel types and ships is discussed. In addition, we established a statistical method for the occurrence time of NACEs and the state of tides according to the half-tide level and the nearest time. The outcomes of this study provide a direction for exploring the relationship between NACEs and environmental conditions, which is also instructive for the study of the causes of ship accidents.","PeriodicalId":50120,"journal":{"name":"Journal of Navigation","volume":"75 1","pages":"346 - 363"},"PeriodicalIF":2.4,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49549207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Determination of calibration parameters is essential for the fusion performance of an inertial measurement unit (IMU) and odometer integrated navigation system. Traditional calibration methods are commonly based on the filter frame, which limits the improvement of the calibration accuracy. This paper proposes a graph-optimisation-based self-calibration method for the IMU/odometer using preintegration theory. Different from existing preintegrations, the complete IMU/odometer preintegration model is derived, which takes into consideration the effects of the scale factor of the odometer, and misalignments in the attitude and position between the IMU and odometer. Then the calibration is implemented by the graph-optimisation method. The KITTI dataset and field experimental tests are carried out to evaluate the effectiveness of the proposed method. The results illustrate that the proposed method outperforms the filter-based calibration method. Meanwhile, the performance of the proposed IMU/odometer preintegration model is optimal compared with the traditional preintegration models.
{"title":"Graph-optimisation-based self-calibration method for IMU/odometer using preintegration theory","authors":"Shiyu Bai, Jizhou Lai, Pin Lyu, Yiting Cen, Bingqing Wang, Xin Sun","doi":"10.1017/S0373463321000722","DOIUrl":"https://doi.org/10.1017/S0373463321000722","url":null,"abstract":"Determination of calibration parameters is essential for the fusion performance of an inertial measurement unit (IMU) and odometer integrated navigation system. Traditional calibration methods are commonly based on the filter frame, which limits the improvement of the calibration accuracy. This paper proposes a graph-optimisation-based self-calibration method for the IMU/odometer using preintegration theory. Different from existing preintegrations, the complete IMU/odometer preintegration model is derived, which takes into consideration the effects of the scale factor of the odometer, and misalignments in the attitude and position between the IMU and odometer. Then the calibration is implemented by the graph-optimisation method. The KITTI dataset and field experimental tests are carried out to evaluate the effectiveness of the proposed method. The results illustrate that the proposed method outperforms the filter-based calibration method. Meanwhile, the performance of the proposed IMU/odometer preintegration model is optimal compared with the traditional preintegration models.","PeriodicalId":50120,"journal":{"name":"Journal of Navigation","volume":"75 1","pages":"594 - 613"},"PeriodicalIF":2.4,"publicationDate":"2022-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43239255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-13DOI: 10.1017/S0373463321000941
Binghua Shi, Yixin Su, Cheng Lian, Chang Xiong, Yang Long, Chenglong Gong
Abstract Recognition of obstacle type based on visual sensors is important for navigation by unmanned surface vehicles (USV), including path planning, obstacle avoidance, and reactive control. Conventional detection techniques may fail to distinguish obstacles that are similar in visual appearance in a cluttered environment. This work proposes a novel obstacle type recognition approach that combines a dilated operator with the deep-level features map of ResNet50 for autonomous navigation. First, visual images are collected and annotated from various different scenarios for USV test navigation. Second, the deep learning model, based on a dilated convolutional neural network, is set and trained. Dilated convolution allows the whole network to learn deep features with increased receptive field and further improves the performance of obstacle type recognition. Third, a series of evaluation parameters are utilised to evaluate the obtained model, such as the mean average precision (mAP), missing rate and detection speed. Finally, some experiments are designed to verify the accuracy of the proposed approach using visual images in a cluttered environment. Experimental results demonstrate that the dilated convolutional neural network obtains better recognition performance than the other methods, with an mAP of 88%.
{"title":"Obstacle type recognition in visual images via dilated convolutional neural network for unmanned surface vehicles","authors":"Binghua Shi, Yixin Su, Cheng Lian, Chang Xiong, Yang Long, Chenglong Gong","doi":"10.1017/S0373463321000941","DOIUrl":"https://doi.org/10.1017/S0373463321000941","url":null,"abstract":"Abstract Recognition of obstacle type based on visual sensors is important for navigation by unmanned surface vehicles (USV), including path planning, obstacle avoidance, and reactive control. Conventional detection techniques may fail to distinguish obstacles that are similar in visual appearance in a cluttered environment. This work proposes a novel obstacle type recognition approach that combines a dilated operator with the deep-level features map of ResNet50 for autonomous navigation. First, visual images are collected and annotated from various different scenarios for USV test navigation. Second, the deep learning model, based on a dilated convolutional neural network, is set and trained. Dilated convolution allows the whole network to learn deep features with increased receptive field and further improves the performance of obstacle type recognition. Third, a series of evaluation parameters are utilised to evaluate the obtained model, such as the mean average precision (mAP), missing rate and detection speed. Finally, some experiments are designed to verify the accuracy of the proposed approach using visual images in a cluttered environment. Experimental results demonstrate that the dilated convolutional neural network obtains better recognition performance than the other methods, with an mAP of 88%.","PeriodicalId":50120,"journal":{"name":"Journal of Navigation","volume":"75 1","pages":"437 - 454"},"PeriodicalIF":2.4,"publicationDate":"2022-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41430273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-13DOI: 10.1017/S0373463321000953
Magdalena I. Asborno, S. Hernandez, K. Mitchell, Manzi Yves
Abstract Travel demand models (TDMs) with freight forecasts estimate performance metrics for competing infrastructure investments and potential policy changes. Unfortunately, freight TDMs fail to represent non-truck modes with levels of detail adequate for multi-modal infrastructure and policy evaluation. Recent expansions in the availability of maritime movement data, i.e. Automatic Identification System (AIS), make it possible to expand and improve representation of maritime modes within freight TDMs. AIS may be used to track vessel locations as timestamped latitude–longitude points. For estimation, calibration and validation of freight TDMs, this work identifies vessel trips by applying network mapping (map-matching) heuristics to AIS data. The automated methods are evaluated on a 747-mile inland waterway network, with AIS data representing 88% of vessel activity. Inspection of 3820 AIS trajectories was used to train the heuristic parameters including stop time, duration and location. Validation shows 84⋅0% accuracy in detecting stops at ports and 83⋅5% accuracy in identifying trips crossing locks. The resulting map-matched vessel trips may be applied to generate origin–destination matrices, calculate time impedances, etc. The proposed methods are transferable to waterways or maritime port systems, as AIS continues to grow.
{"title":"Inland waterway network mapping of AIS data for freight transportation planning","authors":"Magdalena I. Asborno, S. Hernandez, K. Mitchell, Manzi Yves","doi":"10.1017/S0373463321000953","DOIUrl":"https://doi.org/10.1017/S0373463321000953","url":null,"abstract":"Abstract Travel demand models (TDMs) with freight forecasts estimate performance metrics for competing infrastructure investments and potential policy changes. Unfortunately, freight TDMs fail to represent non-truck modes with levels of detail adequate for multi-modal infrastructure and policy evaluation. Recent expansions in the availability of maritime movement data, i.e. Automatic Identification System (AIS), make it possible to expand and improve representation of maritime modes within freight TDMs. AIS may be used to track vessel locations as timestamped latitude–longitude points. For estimation, calibration and validation of freight TDMs, this work identifies vessel trips by applying network mapping (map-matching) heuristics to AIS data. The automated methods are evaluated on a 747-mile inland waterway network, with AIS data representing 88% of vessel activity. Inspection of 3820 AIS trajectories was used to train the heuristic parameters including stop time, duration and location. Validation shows 84⋅0% accuracy in detecting stops at ports and 83⋅5% accuracy in identifying trips crossing locks. The resulting map-matched vessel trips may be applied to generate origin–destination matrices, calculate time impedances, etc. The proposed methods are transferable to waterways or maritime port systems, as AIS continues to grow.","PeriodicalId":50120,"journal":{"name":"Journal of Navigation","volume":"75 1","pages":"251 - 272"},"PeriodicalIF":2.4,"publicationDate":"2022-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46713066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-13DOI: 10.1017/S0373463321000825
Amin Basiri, V. Mariani, Giuseppe Silano, Muhammad Aatif, L. Iannelli, L. Glielmo
Abstract Multi-rotor Unmanned Aerial Vehicles (UAVs), although originally designed and developed for defence and military purposes, in the last ten years have gained momentum, especially for civilian applications, such as search and rescue, surveying and mapping, and agricultural crops and monitoring. Thanks to their hovering and Vertical Take-Off and Landing (VTOL) capabilities and the capacity to carry out tasks with complete autonomy, they are now a standard platform for both research and industrial uses. However, while the flight control architecture is well established in the literature, there are still many challenges in designing autonomous guidance and navigation systems to make the UAV able to work in constrained and cluttered environments or also indoors. Therefore, the main motivation of this work is to provide a comprehensive and exhaustive literature review on the numerous methods and approaches to address path-planning problems for multi-rotor UAVs. In particular, the inclusion of a review of the related research in the context of Precision Agriculture (PA) provides a unified and accessible presentation for researchers who are initiating their endeavours in this subject.
{"title":"A survey on the application of path-planning algorithms for multi-rotor UAVs in precision agriculture","authors":"Amin Basiri, V. Mariani, Giuseppe Silano, Muhammad Aatif, L. Iannelli, L. Glielmo","doi":"10.1017/S0373463321000825","DOIUrl":"https://doi.org/10.1017/S0373463321000825","url":null,"abstract":"Abstract Multi-rotor Unmanned Aerial Vehicles (UAVs), although originally designed and developed for defence and military purposes, in the last ten years have gained momentum, especially for civilian applications, such as search and rescue, surveying and mapping, and agricultural crops and monitoring. Thanks to their hovering and Vertical Take-Off and Landing (VTOL) capabilities and the capacity to carry out tasks with complete autonomy, they are now a standard platform for both research and industrial uses. However, while the flight control architecture is well established in the literature, there are still many challenges in designing autonomous guidance and navigation systems to make the UAV able to work in constrained and cluttered environments or also indoors. Therefore, the main motivation of this work is to provide a comprehensive and exhaustive literature review on the numerous methods and approaches to address path-planning problems for multi-rotor UAVs. In particular, the inclusion of a review of the related research in the context of Precision Agriculture (PA) provides a unified and accessible presentation for researchers who are initiating their endeavours in this subject.","PeriodicalId":50120,"journal":{"name":"Journal of Navigation","volume":"75 1","pages":"364 - 383"},"PeriodicalIF":2.4,"publicationDate":"2022-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45944983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1017/s037346332200011x
{"title":"NAV volume 75 issue 1 Cover and Front matter","authors":"","doi":"10.1017/s037346332200011x","DOIUrl":"https://doi.org/10.1017/s037346332200011x","url":null,"abstract":"","PeriodicalId":50120,"journal":{"name":"Journal of Navigation","volume":" ","pages":"f1 - f2"},"PeriodicalIF":2.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46273062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1017/S0373463321000588
Kate Jeffery, Wanying Guo, Danny Ball, Julia Rodriguez-Sanchez
We investigated the contribution of visual imagination to the cognitive mapping of a building when initial exploration was simulated either visually by using a passive video walk-through, or mentally by using verbal guidance. Building layout had repeating elements with either rotational or mirror symmetry. Cognitive mapping of the virtual building, determined using questionnaires and map drawings, was present following verbal guidance but inferior to that following video guidance. Mapping was not affected by the building's structural symmetry. However, notably, it correlated with small-scale mental rotation scores for both video and verbal guidance conditions. There was no difference between males and females. A common factor that may have influenced cognitive mapping was the availability of visual information about the relationships of the building elements, either directly perceived (during the video walk-through) or imagined (during the verbal walk-through and/or during recall). Differences in visual imagination, particularly mental rotation, may thus account for some of the individual variance in cognitive mapping of complex built environments, which is relevant to how designers provide navigation-relevant information.
{"title":"Visual imagination and cognitive mapping of a virtual building.","authors":"Kate Jeffery, Wanying Guo, Danny Ball, Julia Rodriguez-Sanchez","doi":"10.1017/S0373463321000588","DOIUrl":"10.1017/S0373463321000588","url":null,"abstract":"<p><p>We investigated the contribution of visual imagination to the cognitive mapping of a building when initial exploration was simulated either visually by using a passive video walk-through, or mentally by using verbal guidance. Building layout had repeating elements with either rotational or mirror symmetry. Cognitive mapping of the virtual building, determined using questionnaires and map drawings, was present following verbal guidance but inferior to that following video guidance. Mapping was not affected by the building's structural symmetry. However, notably, it correlated with small-scale mental rotation scores for both video and verbal guidance conditions. There was no difference between males and females. A common factor that may have influenced cognitive mapping was the availability of visual information about the relationships of the building elements, either directly perceived (during the video walk-through) or imagined (during the verbal walk-through and/or during recall). Differences in visual imagination, particularly mental rotation, may thus account for some of the individual variance in cognitive mapping of complex built environments, which is relevant to how designers provide navigation-relevant information.</p>","PeriodicalId":50120,"journal":{"name":"Journal of Navigation","volume":"75 1","pages":"1-14"},"PeriodicalIF":2.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7612610/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46462511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1017/s0373463322000108
{"title":"NAV volume 75 issue 1 Cover and Back matter","authors":"","doi":"10.1017/s0373463322000108","DOIUrl":"https://doi.org/10.1017/s0373463322000108","url":null,"abstract":"","PeriodicalId":50120,"journal":{"name":"Journal of Navigation","volume":" ","pages":"b1 - b2"},"PeriodicalIF":2.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49627947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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