J. Stewart, Michael Payne, Gregory Reynolds, Kelly K. D. Risko, Clinton Blankenship
As the focus in the field of navigation increasingly shifts toward alternatives to Global Navigation Satellite System (GNSS) aiding, vision-based navigation (VBN) techniques have proven to be especially promising. The error characteristics of VBN systems are not currently well understood and can vary significantly from system to system. A quality metric is needed in order for a navigation system to evaluate the accuracy of VBN position estimates for inclusion in the overall navigation solution and to aid in navigation algorithm design and sensor fusion. An implementation-agnostic metric allows for direct comparisons between measurement sources. In this paper, a feature tracking algorithm-agnostic vision-based navigation quality metric is devised that uses a common set of variables to evaluate the expected accuracy of a VBN solution without any knowledge of the VBN algorithm being assessed. The quality metric algorithm can therefore be rapidly integrated with any feature tracking VBN sensor or system regardless of its underlying mechanization, reducing the effort required to implement the metric algorithm on fielded systems and allowing for the comparison and fusion of measurements from two or more unique VBN sensors. To aid in the development of the VBN metric algorithm, a baseline georeferenced VBN was designed and implemented in a Monte Carlo simulation using satellite imagery from the National Resource Conservation Service (NRCS) database. The data set contained images that varied in terrain, vehicle height, camera resolution, and camera pose uncertainty. For each Monte Carlo set, the median VBN position error was collected and categorized as either above or below an arbitrary accuracy in meters. This data set was then used to train multiple machine learning models ranging in complexity from linear ordinary least squares to various forms of classification trees, with the goal being to correctly categorize the expected error of the VBN measurements. Multiple combinations of VBN input variables were compared in the models to determine which variables most influenced the accuracy of a given VBN position estimate, with the goal being to train a machine learning algorithm to accurately predict VBN position error with the minimum number of inputs and without over-fitting any single data set. While the least-squares method performed reasonably well, the more sophisticated classification tree topologies proved best able to predict VBN position estimate accuracy using a combination of four variables: pitch/roll uncertainty, yaw uncertainty, vehicle height, and the pixel distance between identified features in the image. The performance of the quality metric was verified using an additional data set created from the NRCS database, as well as an independent flight test data set using a different VBN system. The quality metric algorithm was able to accurately categorize the expected VBN position estimate accuracy for approximately 90% of the VBN estimates
{"title":"Development of an Implementation-Agnostic Quality Metric for Evaluating the Accuracy of Position Estimations from Vision-Based Navigation Algorithms","authors":"J. Stewart, Michael Payne, Gregory Reynolds, Kelly K. D. Risko, Clinton Blankenship","doi":"10.33012/2019.16798","DOIUrl":"https://doi.org/10.33012/2019.16798","url":null,"abstract":"As the focus in the field of navigation increasingly shifts toward alternatives to Global Navigation Satellite System (GNSS) aiding, vision-based navigation (VBN) techniques have proven to be especially promising. The error characteristics of VBN systems are not currently well understood and can vary significantly from system to system. A quality metric is needed in order for a navigation system to evaluate the accuracy of VBN position estimates for inclusion in the overall navigation solution and to aid in navigation algorithm design and sensor fusion. An implementation-agnostic metric allows for direct comparisons between measurement sources. In this paper, a feature tracking algorithm-agnostic vision-based navigation quality metric is devised that uses a common set of variables to evaluate the expected accuracy of a VBN solution without any knowledge of the VBN algorithm being assessed. The quality metric algorithm can therefore be rapidly integrated with any feature tracking VBN sensor or system regardless of its underlying mechanization, reducing the effort required to implement the metric algorithm on fielded systems and allowing for the comparison and fusion of measurements from two or more unique VBN sensors. To aid in the development of the VBN metric algorithm, a baseline georeferenced VBN was designed and implemented in a Monte Carlo simulation using satellite imagery from the National Resource Conservation Service (NRCS) database. The data set contained images that varied in terrain, vehicle height, camera resolution, and camera pose uncertainty. For each Monte Carlo set, the median VBN position error was collected and categorized as either above or below an arbitrary accuracy in meters. This data set was then used to train multiple machine learning models ranging in complexity from linear ordinary least squares to various forms of classification trees, with the goal being to correctly categorize the expected error of the VBN measurements. Multiple combinations of VBN input variables were compared in the models to determine which variables most influenced the accuracy of a given VBN position estimate, with the goal being to train a machine learning algorithm to accurately predict VBN position error with the minimum number of inputs and without over-fitting any single data set. While the least-squares method performed reasonably well, the more sophisticated classification tree topologies proved best able to predict VBN position estimate accuracy using a combination of four variables: pitch/roll uncertainty, yaw uncertainty, vehicle height, and the pixel distance between identified features in the image. The performance of the quality metric was verified using an additional data set created from the NRCS database, as well as an independent flight test data set using a different VBN system. The quality metric algorithm was able to accurately categorize the expected VBN position estimate accuracy for approximately 90% of the VBN estimates","PeriodicalId":201935,"journal":{"name":"Proceedings of the ION 2019 Pacific PNT Meeting","volume":"101 27","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131914342","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}
Yong-Jo Lee, Byungwoon Park, Y. Hwang, Byoung-Sun Lee, J. Ahn
{"title":"Direct Estimation of Multipath in a Deep Urban Area using Multi-GNSS Carrier Phase Variation and Previous Position","authors":"Yong-Jo Lee, Byungwoon Park, Y. Hwang, Byoung-Sun Lee, J. Ahn","doi":"10.33012/2019.16835","DOIUrl":"https://doi.org/10.33012/2019.16835","url":null,"abstract":"","PeriodicalId":201935,"journal":{"name":"Proceedings of the ION 2019 Pacific PNT Meeting","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124161305","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}
The current WAAS signal quality monitor algorithm was designed to mitigate anomalous signal distortions. This paper assesses the ability of this monitor mitigate distortions produced from satellite-induced multipath. Leveraging experience from the SVN-49 anomaly, a single-reflection signal threat model is defined and expanded to include an elevation-angle dependence, which may potentially reduce observability of distortions viewed from widely-distributed monitor receivers. Next, the range errors for both singlefrequency and dual-frequency aviation users are modeled relative to the monitor’s ability to detect them. It is shown that the existing WAAS signal deformation monitor can protect both single and dualfrequency aviation users against a wide range of SVinduced, single-reflection multipath parameters despite significant attenuation of monitor sensitivity due to elevation-angle dependence. BACKGROUND The threat of anomalous signal deformations has existed for users of high-integrity differential GNSS navigation systems for many years. Developers of SBAS and GBAS, in particular, originally analyzed that event and proposed several types of anomalous distortions that, without monitoring and detection, could pose a hazard to aviation users. Subsequently, a threat model that encompassed that thinking was proposed and later adopted as the standard by ICAO in 2000 [1]. That threat model specifically identified two classes of anomalous deformations—digital and analog—to capture the general characteristics of distortions observed on the SV-19 fault. Further, the model was ultimately expanded and proposed as representative worst case for all anomalous signal deformation faults. Signal deformation monitors were subsequently developed to mitigate any/all SVinduced distortions using that ICAO threat model for validation. SVN-49 anomaly in 2009 was caused by an internal reflection in the signal payload; it resembled multipath. That anomaly is not considered a fault, however, because the satellite was never declared healthy. No WAAS users were ever at risk of exposure. Still, the validation threat model was proposed to account for general signal distortions and anomalous multipath is a specific type of distortion against which validated monitors may be assessed. The SVN-49 anomaly was also peculiar in that it had an elevation angle-dependence. (See Figure 1.) That potentially challenges detection capabilities for networks that observe the satellite from widelyseparated locations. Figure 1. L1 C/A chip shape measured for specific elevation angles for SVN-49 (PRN-01) as measured by an 18 MHz NovAtel receiver. [2] Previous work has broadly assessed the capability of the WAAS signal quality monitor to protect singlefrequency aviation users against the multipath threat [3]. However, relatively little has been done to address users of dual-frequency WAAS where range errors due to biases are larger while error bounds are reduced. In addition, to date, nothing has be
{"title":"Signal Deformation Monitoring for Anomalous Multipath Threats","authors":"R. E. Phelts, T. Walter","doi":"10.33012/2019.16853","DOIUrl":"https://doi.org/10.33012/2019.16853","url":null,"abstract":"The current WAAS signal quality monitor algorithm was designed to mitigate anomalous signal distortions. This paper assesses the ability of this monitor mitigate distortions produced from satellite-induced multipath. Leveraging experience from the SVN-49 anomaly, a single-reflection signal threat model is defined and expanded to include an elevation-angle dependence, which may potentially reduce observability of distortions viewed from widely-distributed monitor receivers. Next, the range errors for both singlefrequency and dual-frequency aviation users are modeled relative to the monitor’s ability to detect them. It is shown that the existing WAAS signal deformation monitor can protect both single and dualfrequency aviation users against a wide range of SVinduced, single-reflection multipath parameters despite significant attenuation of monitor sensitivity due to elevation-angle dependence. BACKGROUND The threat of anomalous signal deformations has existed for users of high-integrity differential GNSS navigation systems for many years. Developers of SBAS and GBAS, in particular, originally analyzed that event and proposed several types of anomalous distortions that, without monitoring and detection, could pose a hazard to aviation users. Subsequently, a threat model that encompassed that thinking was proposed and later adopted as the standard by ICAO in 2000 [1]. That threat model specifically identified two classes of anomalous deformations—digital and analog—to capture the general characteristics of distortions observed on the SV-19 fault. Further, the model was ultimately expanded and proposed as representative worst case for all anomalous signal deformation faults. Signal deformation monitors were subsequently developed to mitigate any/all SVinduced distortions using that ICAO threat model for validation. SVN-49 anomaly in 2009 was caused by an internal reflection in the signal payload; it resembled multipath. That anomaly is not considered a fault, however, because the satellite was never declared healthy. No WAAS users were ever at risk of exposure. Still, the validation threat model was proposed to account for general signal distortions and anomalous multipath is a specific type of distortion against which validated monitors may be assessed. The SVN-49 anomaly was also peculiar in that it had an elevation angle-dependence. (See Figure 1.) That potentially challenges detection capabilities for networks that observe the satellite from widelyseparated locations. Figure 1. L1 C/A chip shape measured for specific elevation angles for SVN-49 (PRN-01) as measured by an 18 MHz NovAtel receiver. [2] Previous work has broadly assessed the capability of the WAAS signal quality monitor to protect singlefrequency aviation users against the multipath threat [3]. However, relatively little has been done to address users of dual-frequency WAAS where range errors due to biases are larger while error bounds are reduced. In addition, to date, nothing has be","PeriodicalId":201935,"journal":{"name":"Proceedings of the ION 2019 Pacific PNT Meeting","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114497331","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}
{"title":"Toward GPS-denied Navigation Utilizing Back Projection-based Synthetic Aperture Radar Imagery","authors":"Randall S. Christensen, J. Gunther, D. Long","doi":"10.33012/2019.16797","DOIUrl":"https://doi.org/10.33012/2019.16797","url":null,"abstract":"","PeriodicalId":201935,"journal":{"name":"Proceedings of the ION 2019 Pacific PNT Meeting","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116918803","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}
Yiran Luo, Jian Li, Chunyang Yu, Z. Lyu, Zhe Yue, N. El-Sheimy
This paper presents a vector tracking (VT) architecture based on global navigation satellite system (GNSS) software-defined receiver (SDR). The incoming signal is firstly acquired with the partially matched filter algorithm. Then, the frequency lock loop (FLL) which can tolerate higher dynamics in tracking is exploited to initialize the tracking process of the GNSS SDR. After the incoming signal is stably being locked, the FLL will be replaced by the phase lock loop (PLL) to output the more accurate estimation of the carrier phase error. The measurements, i.e., pseudo-range, carrier phase, Doppler, carrier-to-noise density ratio ( C / N0 ), etc., will subsequently be obtained after the bit and frame synchronization procedures. Furthermore, the weighted non-linear least square (WNLS) method is adopted in this work to compute the navigation solutions on the condition that the number of the space vehicle (SV) is adequate, i.e., more than four SVs for a separate navigation system, global positioning system (GPS), to offer reliable solutions in terms of three-dimension (3-D) positions and clock bias, and 3-D velocities and clock drift. The weighted matrix would be formed with two approaches, and the elevation angle and the C / N0 will be taken into consideration to construct it, respectively. After that, the user velocity estimations and the receiver clock drift with the satellite positions and velocities from the ephemeris in the current channels will be fed back to the carrier numerically controlled oscillator (NCO). Moreover, the code NCO would also be assisted by the formed local frequency replica with the carrier NCO. Therefore, a vector tracking architecture can be finally given in this way. Both delay lock loop (DLL) and PLL are controlled by positioning, velocity, and time (PVT) feedbacks. Field tests demonstrate the performances of the proposed VT-based GNSS SDR for the land vehicle navigation.
{"title":"A GNSS Software-Defined Receiver with Vector Tracking Techniques for Land Vehicle Navigation","authors":"Yiran Luo, Jian Li, Chunyang Yu, Z. Lyu, Zhe Yue, N. El-Sheimy","doi":"10.33012/2019.16834","DOIUrl":"https://doi.org/10.33012/2019.16834","url":null,"abstract":"This paper presents a vector tracking (VT) architecture based on global navigation satellite system (GNSS) software-defined receiver (SDR). The incoming signal is firstly acquired with the partially matched filter algorithm. Then, the frequency lock loop (FLL) which can tolerate higher dynamics in tracking is exploited to initialize the tracking process of the GNSS SDR. After the incoming signal is stably being locked, the FLL will be replaced by the phase lock loop (PLL) to output the more accurate estimation of the carrier phase error. The measurements, i.e., pseudo-range, carrier phase, Doppler, carrier-to-noise density ratio ( C / N0 ), etc., will subsequently be obtained after the bit and frame synchronization procedures. Furthermore, the weighted non-linear least square (WNLS) method is adopted in this work to compute the navigation solutions on the condition that the number of the space vehicle (SV) is adequate, i.e., more than four SVs for a separate navigation system, global positioning system (GPS), to offer reliable solutions in terms of three-dimension (3-D) positions and clock bias, and 3-D velocities and clock drift. The weighted matrix would be formed with two approaches, and the elevation angle and the C / N0 will be taken into consideration to construct it, respectively. After that, the user velocity estimations and the receiver clock drift with the satellite positions and velocities from the ephemeris in the current channels will be fed back to the carrier numerically controlled oscillator (NCO). Moreover, the code NCO would also be assisted by the formed local frequency replica with the carrier NCO. Therefore, a vector tracking architecture can be finally given in this way. Both delay lock loop (DLL) and PLL are controlled by positioning, velocity, and time (PVT) feedbacks. Field tests demonstrate the performances of the proposed VT-based GNSS SDR for the land vehicle navigation.","PeriodicalId":201935,"journal":{"name":"Proceedings of the ION 2019 Pacific PNT Meeting","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129771984","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}
{"title":"Research on Standalone BeiDou Radio Frequency Minimum Performance Test for Mobile Communication Terminals","authors":"Z. Qinjuan, Dai Xun, Chen Xiaochen","doi":"10.33012/2019.16796","DOIUrl":"https://doi.org/10.33012/2019.16796","url":null,"abstract":"","PeriodicalId":201935,"journal":{"name":"Proceedings of the ION 2019 Pacific PNT Meeting","volume":"23 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129026842","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}
{"title":"An Overview of Advanced Receiver Autonomous Integrity Monitoring (ARAIM)","authors":"T. Walter","doi":"10.33012/2019.16848","DOIUrl":"https://doi.org/10.33012/2019.16848","url":null,"abstract":"","PeriodicalId":201935,"journal":{"name":"Proceedings of the ION 2019 Pacific PNT Meeting","volume":"219 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130440651","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}
J. Morton, H. Bourne, Brian Breitsch, Ian Collett, S. Taylor, Neeraj Pujara
{"title":"Mountaintop GNSS-R and GNSS-RO Experiment: New Results and Insights","authors":"J. Morton, H. Bourne, Brian Breitsch, Ian Collett, S. Taylor, Neeraj Pujara","doi":"10.33012/2019.16832","DOIUrl":"https://doi.org/10.33012/2019.16832","url":null,"abstract":"","PeriodicalId":201935,"journal":{"name":"Proceedings of the ION 2019 Pacific PNT Meeting","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128995182","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}
{"title":"GNSS Signal in Railway Train Operation Scenario Quality Grid Generation Method","authors":"Debiao Lu, Jun Tan, B. Cai, Jiang Liu, Jian Wang","doi":"10.33012/2019.16822","DOIUrl":"https://doi.org/10.33012/2019.16822","url":null,"abstract":"","PeriodicalId":201935,"journal":{"name":"Proceedings of the ION 2019 Pacific PNT Meeting","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129038634","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}
R. Hirokawa, K. Nakakuki, S. Fujita, Yuki Sato, A. Uehara
The operational service of CLAS of Japan Quazi-Zenith-Satellite-System (QZSS), a nation-wide satellite-based PPP-RTK service in Japan having the centimeter level positioning accuracy begun on November 1, 2018. In this paper, the result of continuous performance evaluation on the multiple stations of the Japan CORS network is presented, the positioning accuracy and the time-to- ambiguity fix (TTFF) evaluated in the static and kinematic condition. A kinematic van test result applying CLAS correction with a prototype GNSS receiver is also presented, it is confirmed that the positioning accuracy comparable with the conventional RTK. In this performance evaluation, CLAS Test Library (CLASLIB), open-source software tools for PPP-RTK based on RTKLIB is introduced and applied.
日本准天顶卫星系统(QZSS)的CLAS于2018年11月1日开始运营服务，该服务是日本全国性的卫星PPP-RTK服务，定位精度为厘米级。本文介绍了日本CORS网络多台站连续性能评估结果，在静态和运动条件下对定位精度和模糊时间校正(TTFF)进行了评估。利用GNSS接收机样机进行了CLAS校正后的运动小车试验，结果表明，该方法的定位精度与传统的RTK相当。在本次性能评估中，介绍并应用了基于RTKLIB的开源PPP-RTK软件工具CLAS测试库(CLAS Test Library, cllib)。
{"title":"The Operational Phase Performance of Centimeter-Level Augmentation Service (CLAS)","authors":"R. Hirokawa, K. Nakakuki, S. Fujita, Yuki Sato, A. Uehara","doi":"10.33012/2019.16810","DOIUrl":"https://doi.org/10.33012/2019.16810","url":null,"abstract":"The operational service of CLAS of Japan Quazi-Zenith-Satellite-System (QZSS), a nation-wide satellite-based PPP-RTK service in Japan having the centimeter level positioning accuracy begun on November 1, 2018. In this paper, the result of continuous performance evaluation on the multiple stations of the Japan CORS network is presented, the positioning accuracy and the time-to- ambiguity fix (TTFF) evaluated in the static and kinematic condition. A kinematic van test result applying CLAS correction with a prototype GNSS receiver is also presented, it is confirmed that the positioning accuracy comparable with the conventional RTK. In this performance evaluation, CLAS Test Library (CLASLIB), open-source software tools for PPP-RTK based on RTKLIB is introduced and applied.","PeriodicalId":201935,"journal":{"name":"Proceedings of the ION 2019 Pacific PNT Meeting","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121740761","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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