Pub Date : 2014-03-12DOI: 10.1109/WPNC.2014.6843300
Stephan Adler, S. Schmitt, M. Kyas
This paper presents results of a large real world experimental setup of an indoor localization system. We used a time-of-flight based radio range measurement system to collect a large body of ranging data between a mobile reference system and multiple anchor nodes with a fixed and known position. For our experiment the reference system moved autonomously through an office building while collecting ranging data. We used this data to analyze the impact of environmental parameters on the ranging accuracy. We saw effects which are not predicted by the standard channel models for multiple scenarios and discuss these effects in detail.
{"title":"Path loss and multipath effects in a real world indoor localization scenario","authors":"Stephan Adler, S. Schmitt, M. Kyas","doi":"10.1109/WPNC.2014.6843300","DOIUrl":"https://doi.org/10.1109/WPNC.2014.6843300","url":null,"abstract":"This paper presents results of a large real world experimental setup of an indoor localization system. We used a time-of-flight based radio range measurement system to collect a large body of ranging data between a mobile reference system and multiple anchor nodes with a fixed and known position. For our experiment the reference system moved autonomously through an office building while collecting ranging data. We used this data to analyze the impact of environmental parameters on the ranging accuracy. We saw effects which are not predicted by the standard channel models for multiple scenarios and discuss these effects in detail.","PeriodicalId":106193,"journal":{"name":"2014 11th Workshop on Positioning, Navigation and Communication (WPNC)","volume":"32 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123750838","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 : 2014-03-12DOI: 10.1109/WPNC.2014.6843308
M. Tkocz, K. Janschek
In this paper we present a novel approach for the estimation of metric velocities and metric distances to landmarks utilizing monocular images and inertial measurements only. The proposed algorithm is based on an Extended Kalman Filter and is closely related to the well known Simultaneous Localization and Mapping (SLAM). In contrast to standard SLAM formulations the state of an agent is expressed in the body frame instead of the inertial frame. This formulation results in direct observability of the velocity and landmark distances for dynamic trajectories and the ability to maintain a consistent estimate for non-dynamic trajectories.
{"title":"Metric velocity and landmark distance estimation utilizing monocular camera images and IMU data","authors":"M. Tkocz, K. Janschek","doi":"10.1109/WPNC.2014.6843308","DOIUrl":"https://doi.org/10.1109/WPNC.2014.6843308","url":null,"abstract":"In this paper we present a novel approach for the estimation of metric velocities and metric distances to landmarks utilizing monocular images and inertial measurements only. The proposed algorithm is based on an Extended Kalman Filter and is closely related to the well known Simultaneous Localization and Mapping (SLAM). In contrast to standard SLAM formulations the state of an agent is expressed in the body frame instead of the inertial frame. This formulation results in direct observability of the velocity and landmark distances for dynamic trajectories and the ability to maintain a consistent estimate for non-dynamic trajectories.","PeriodicalId":106193,"journal":{"name":"2014 11th Workshop on Positioning, Navigation and Communication (WPNC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115788948","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 : 2014-03-12DOI: 10.1109/WPNC.2014.6843293
Arghavan Amini, R. Vaghefi, J. M. Garza, R. Buehrer
In this paper, the problem of mobile tracking in dense environments is studied. The Global Positioning System (GPS) is the most accessible positioning technique. However, GPS does not work properly in indoor and dense areas, as the receiver typically does not have access to a sufficient number of line-of-sight satellites. Therefore, localization in these networks can be alternatively done by using measurements collected within the network and without the aid of any external resources (e.g., GPS). The mobile tracking problem includes several static reference nodes whose locations are fixed and known, and many mobile nodes whose locations are unknown and needed to be determined. The problem of mobile tracking can be solved in two forms: centralized and distributed. A centralized algorithm can result in high complexity and latency, while a distributed algorithm might lead to large estimation errors. In this paper, a novel cooperative localization technique is introduced which is able to deliver a promising localization accuracy while maintain the latency and complexity as low as possible. The performance of the proposed algorithm is compared with those of other algorithms in terms of localization accuracy, latency, and required data communication through computer simulations. The simulation results show the effectiveness of the proposed algorithm in comparison with either centralized and distributed algorithms. An important application of this work is vehicle localization in dense environments where the vehicles do not have access to GPS satellites and must be localized by the elements within the network.
{"title":"GPS-free cooperative mobile tracking with the application in vehicular networks","authors":"Arghavan Amini, R. Vaghefi, J. M. Garza, R. Buehrer","doi":"10.1109/WPNC.2014.6843293","DOIUrl":"https://doi.org/10.1109/WPNC.2014.6843293","url":null,"abstract":"In this paper, the problem of mobile tracking in dense environments is studied. The Global Positioning System (GPS) is the most accessible positioning technique. However, GPS does not work properly in indoor and dense areas, as the receiver typically does not have access to a sufficient number of line-of-sight satellites. Therefore, localization in these networks can be alternatively done by using measurements collected within the network and without the aid of any external resources (e.g., GPS). The mobile tracking problem includes several static reference nodes whose locations are fixed and known, and many mobile nodes whose locations are unknown and needed to be determined. The problem of mobile tracking can be solved in two forms: centralized and distributed. A centralized algorithm can result in high complexity and latency, while a distributed algorithm might lead to large estimation errors. In this paper, a novel cooperative localization technique is introduced which is able to deliver a promising localization accuracy while maintain the latency and complexity as low as possible. The performance of the proposed algorithm is compared with those of other algorithms in terms of localization accuracy, latency, and required data communication through computer simulations. The simulation results show the effectiveness of the proposed algorithm in comparison with either centralized and distributed algorithms. An important application of this work is vehicle localization in dense environments where the vehicles do not have access to GPS satellites and must be localized by the elements within the network.","PeriodicalId":106193,"journal":{"name":"2014 11th Workshop on Positioning, Navigation and Communication (WPNC)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130732808","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 : 2014-03-12DOI: 10.1109/WPNC.2014.6843304
M. Ehrig, Markus Petri, V. Sark, J. G. Terán, E. Grass
In this paper, we present a high data rate communication system with an integrated high-resolution ranging feature. The point-to-point communication system is based on an OFDM baseband processor (BB) with data rates up to 3.9 Gbps, a medium access controller (MAC), and an analog frontend (AFE) for the 60 GHz band. The ranging system determines the distance between two stations using the round trip time of flight method (RTToF) in line-of-sight (LOS) environments. The MAC coordinates the channel access between the communication part and the ranging part. The system is integrated in a demonstrator platform based on field programmable gate arrays (FPGA). The ranging performance was simulated and measured in an indoor environment. The resolution is up to centimeter range.
{"title":"Combined high-resolution ranging and high data rate wireless communication system in the 60 GHz band","authors":"M. Ehrig, Markus Petri, V. Sark, J. G. Terán, E. Grass","doi":"10.1109/WPNC.2014.6843304","DOIUrl":"https://doi.org/10.1109/WPNC.2014.6843304","url":null,"abstract":"In this paper, we present a high data rate communication system with an integrated high-resolution ranging feature. The point-to-point communication system is based on an OFDM baseband processor (BB) with data rates up to 3.9 Gbps, a medium access controller (MAC), and an analog frontend (AFE) for the 60 GHz band. The ranging system determines the distance between two stations using the round trip time of flight method (RTToF) in line-of-sight (LOS) environments. The MAC coordinates the channel access between the communication part and the ranging part. The system is integrated in a demonstrator platform based on field programmable gate arrays (FPGA). The ranging performance was simulated and measured in an indoor environment. The resolution is up to centimeter range.","PeriodicalId":106193,"journal":{"name":"2014 11th Workshop on Positioning, Navigation and Communication (WPNC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115029055","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 : 2014-03-12DOI: 10.1109/WPNC.2014.6843292
R. Vaghefi, R. Buehrer
This paper represents a preliminary study of cooperative positioning in Long Term Evolution (LTE) systems. Many applications, such as location-based services and Enhanced 911 (E911), require that the locations of users in a cellular system are available. The global navigation satellite system (GNSS) is the most accessible positioning systems which are widely used in cellphones. However, poor operation in indoor and dense environments leads us to use cellular localization as a backup solution. In cellular localization, the locations of users are determined via measurements obtained within the network without aid of any external sources (e.g., GNSS). Observed time difference of arrival (OTDOA) is a positioning technique introduced in Release 9 of the 3GPP LTE specification. In OTDOA technique, the User Equipment (UE) measures the time difference of signals between several eNodeBs (base stations in LTE) and uses a trilateration algorithm to find its location. In the current 3GPP LTE specification, the UE can only collect measurements from eNodeBs. Therefore, in many situations, the UE is not able to communicate to a sufficient number of eNodeBs and cannot find its location without ambiguity. In this paper, we propose a cooperative localization technique for LTE systems in which the UE communicates not only with eNodeBs but also with other UEs. It will be shown that cooperative localization can significantly improve the localizability in the network, meaning that more UEs can be localized. Cooperative localization also enhances the accuracy which is highly beneficial for some applications, especially E911. A series of computer simulations are conducted to show the benefits of cooperative localization where the 3GPP simulation parameters are assumed.
{"title":"Improving positioning in LTE through collaboration","authors":"R. Vaghefi, R. Buehrer","doi":"10.1109/WPNC.2014.6843292","DOIUrl":"https://doi.org/10.1109/WPNC.2014.6843292","url":null,"abstract":"This paper represents a preliminary study of cooperative positioning in Long Term Evolution (LTE) systems. Many applications, such as location-based services and Enhanced 911 (E911), require that the locations of users in a cellular system are available. The global navigation satellite system (GNSS) is the most accessible positioning systems which are widely used in cellphones. However, poor operation in indoor and dense environments leads us to use cellular localization as a backup solution. In cellular localization, the locations of users are determined via measurements obtained within the network without aid of any external sources (e.g., GNSS). Observed time difference of arrival (OTDOA) is a positioning technique introduced in Release 9 of the 3GPP LTE specification. In OTDOA technique, the User Equipment (UE) measures the time difference of signals between several eNodeBs (base stations in LTE) and uses a trilateration algorithm to find its location. In the current 3GPP LTE specification, the UE can only collect measurements from eNodeBs. Therefore, in many situations, the UE is not able to communicate to a sufficient number of eNodeBs and cannot find its location without ambiguity. In this paper, we propose a cooperative localization technique for LTE systems in which the UE communicates not only with eNodeBs but also with other UEs. It will be shown that cooperative localization can significantly improve the localizability in the network, meaning that more UEs can be localized. Cooperative localization also enhances the accuracy which is highly beneficial for some applications, especially E911. A series of computer simulations are conducted to show the benefits of cooperative localization where the 3GPP simulation parameters are assumed.","PeriodicalId":106193,"journal":{"name":"2014 11th Workshop on Positioning, Navigation and Communication (WPNC)","volume":"296 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117050585","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 : 2014-03-12DOI: 10.1109/WPNC.2014.6843302
A. Golestani, Neda Petreska, Dennis Wilfert, C. Zimmer
In this paper we present a method for improving the precision of an RSSI-based energy-constrained localization system employed in an IEEE 802.15.4 sensor network. The goal application is localization of people in dynamic indoor environments. We introduce an approach which divides the anchor nodes into groups and assigns a path loss exponent to each group. The results from the conveyed tests in our building show a location error smaller than 3m, despite the low energy constraints. Moreover, we provide a hardware platform independent system suitable for both standard and proprietary solutions.
{"title":"Improving the precision of RSSI-based low-energy localization using path loss exponent estimation","authors":"A. Golestani, Neda Petreska, Dennis Wilfert, C. Zimmer","doi":"10.1109/WPNC.2014.6843302","DOIUrl":"https://doi.org/10.1109/WPNC.2014.6843302","url":null,"abstract":"In this paper we present a method for improving the precision of an RSSI-based energy-constrained localization system employed in an IEEE 802.15.4 sensor network. The goal application is localization of people in dynamic indoor environments. We introduce an approach which divides the anchor nodes into groups and assigns a path loss exponent to each group. The results from the conveyed tests in our building show a location error smaller than 3m, despite the low energy constraints. Moreover, we provide a hardware platform independent system suitable for both standard and proprietary solutions.","PeriodicalId":106193,"journal":{"name":"2014 11th Workshop on Positioning, Navigation and Communication (WPNC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126002840","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 : 2014-03-12DOI: 10.1109/WPNC.2014.6843284
R. Piché, Mike Koivisto
When particle filters are used to estimate indoor position with floor plan constraints, it can happen that, even when all the particles lie in the corridor, the particles' mean is not in the corridor. Such a position estimate is perceived by the user as a mistake in the algorithm. Projecting the particles' mean to the nearest corridor location is an obvious ad-hoc solution, but it is not optimal and the trajectory may be discontinuous in time. Another solution is to use a maximum a-posteriori estimate for the particle cloud where the particles in an inaccessible region are eliminated. However, this optimal solution might also have discontinuous trajectory and so it is not ideal for the real time positioning. In this work, the following principled approach is taken. Given a particle cloud representation of a posterior distribution for position, the position estimate is defined as the solution of a least squares problem with linear inequality constraints. This problem can be solved efficiently and reliably using standard numerical optimization algorithms and codes. Results are presented for simulated data and real-world data.
{"title":"A method to enforce map constraints in a particle filter's position estimate","authors":"R. Piché, Mike Koivisto","doi":"10.1109/WPNC.2014.6843284","DOIUrl":"https://doi.org/10.1109/WPNC.2014.6843284","url":null,"abstract":"When particle filters are used to estimate indoor position with floor plan constraints, it can happen that, even when all the particles lie in the corridor, the particles' mean is not in the corridor. Such a position estimate is perceived by the user as a mistake in the algorithm. Projecting the particles' mean to the nearest corridor location is an obvious ad-hoc solution, but it is not optimal and the trajectory may be discontinuous in time. Another solution is to use a maximum a-posteriori estimate for the particle cloud where the particles in an inaccessible region are eliminated. However, this optimal solution might also have discontinuous trajectory and so it is not ideal for the real time positioning. In this work, the following principled approach is taken. Given a particle cloud representation of a posterior distribution for position, the position estimate is defined as the solution of a least squares problem with linear inequality constraints. This problem can be solved efficiently and reliably using standard numerical optimization algorithms and codes. Results are presented for simulated data and real-world data.","PeriodicalId":106193,"journal":{"name":"2014 11th Workshop on Positioning, Navigation and Communication (WPNC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129089663","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 : 2014-03-12DOI: 10.1109/WPNC.2014.6843288
Yang Liu, M. Dashti, Mohd Amiruddin Abd Rahman, Jie Zhang
Celebrated fingerprinting techniques localize users by statistically learning the signal to location relations. However, collecting a lot of labelled data to train an accurate localization model is expensive and labour-intensive. In this paper, an economic and easy-to-deploy indoor localization model suitable for ubiquitous smartphone platforms is established. The method processes embedded inertial sensors readings through a inertial localization system. A particle filter is developed to integrate the building map constraints and inertial localization results to estimate user's location. To increase the algorithm convergence rate, the user's initial/on-line room-level localization is achieved using WiFi signals. To achieve room-level accuracy, only very few training WiFi data, i.e. one per room or per segment of a corridor, are required. A novel crowdsourcing technique to build and update training database is presented. On these basis, an indoor localization system is proposed and evaluated. The results show that comparable location accuracy to previous approaches without even dense wireless site survey requirements is achievable.
{"title":"Indoor localization using smartphone inertial sensors","authors":"Yang Liu, M. Dashti, Mohd Amiruddin Abd Rahman, Jie Zhang","doi":"10.1109/WPNC.2014.6843288","DOIUrl":"https://doi.org/10.1109/WPNC.2014.6843288","url":null,"abstract":"Celebrated fingerprinting techniques localize users by statistically learning the signal to location relations. However, collecting a lot of labelled data to train an accurate localization model is expensive and labour-intensive. In this paper, an economic and easy-to-deploy indoor localization model suitable for ubiquitous smartphone platforms is established. The method processes embedded inertial sensors readings through a inertial localization system. A particle filter is developed to integrate the building map constraints and inertial localization results to estimate user's location. To increase the algorithm convergence rate, the user's initial/on-line room-level localization is achieved using WiFi signals. To achieve room-level accuracy, only very few training WiFi data, i.e. one per room or per segment of a corridor, are required. A novel crowdsourcing technique to build and update training database is presented. On these basis, an indoor localization system is proposed and evaluated. The results show that comparable location accuracy to previous approaches without even dense wireless site survey requirements is achievable.","PeriodicalId":106193,"journal":{"name":"2014 11th Workshop on Positioning, Navigation and Communication (WPNC)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127625352","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 : 2014-03-12DOI: 10.1109/WPNC.2014.6843298
N. Amiot, M. Laaraiedh, B. Uguen
This paper presents a novel mobility model to perform realistic simulations of human movements and behaviors. The proposed model is based on discrete event simulation and graph theory. The proposed model is implemented in a wireless propagation simulator and used to evaluate various wireless network protocols including: propagation, localization and communication.
{"title":"Improved mobility modeling for indoor localization applications","authors":"N. Amiot, M. Laaraiedh, B. Uguen","doi":"10.1109/WPNC.2014.6843298","DOIUrl":"https://doi.org/10.1109/WPNC.2014.6843298","url":null,"abstract":"This paper presents a novel mobility model to perform realistic simulations of human movements and behaviors. The proposed model is based on discrete event simulation and graph theory. The proposed model is implemented in a wireless propagation simulator and used to evaluate various wireless network protocols including: propagation, localization and communication.","PeriodicalId":106193,"journal":{"name":"2014 11th Workshop on Positioning, Navigation and Communication (WPNC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116830203","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 : 2014-03-12DOI: 10.1109/WPNC.2014.6843287
Jens Einsiedler, Daniel Becker, I. Radusch
In the last decade, Global Navigation Satellite Systems (GNSS) have taken a key role in vehicular applications. However, GNSS-based systems are inoperable in enclosed areas like carparks. To overcome this problem, we developed an infrastructure-based positioning system which utilizes customary monocular surveillance cameras to determine the position of vehicles within a carpark. The position information is also provided via car-to-infrastructure communication to the appropriate vehicle in order to substitute the in-vehicle positioning system. In this paper, we focus exclusively on the visual detection and positioning component of this system for detecting and locating moving objects in the carpark. A detailed evaluation demonstrates that the proposed system is able to meet the requirements of common vehicular use cases such as navigation, obstacle warning or autonomous driving.
{"title":"External visual positioning system for enclosed carparks","authors":"Jens Einsiedler, Daniel Becker, I. Radusch","doi":"10.1109/WPNC.2014.6843287","DOIUrl":"https://doi.org/10.1109/WPNC.2014.6843287","url":null,"abstract":"In the last decade, Global Navigation Satellite Systems (GNSS) have taken a key role in vehicular applications. However, GNSS-based systems are inoperable in enclosed areas like carparks. To overcome this problem, we developed an infrastructure-based positioning system which utilizes customary monocular surveillance cameras to determine the position of vehicles within a carpark. The position information is also provided via car-to-infrastructure communication to the appropriate vehicle in order to substitute the in-vehicle positioning system. In this paper, we focus exclusively on the visual detection and positioning component of this system for detecting and locating moving objects in the carpark. A detailed evaluation demonstrates that the proposed system is able to meet the requirements of common vehicular use cases such as navigation, obstacle warning or autonomous driving.","PeriodicalId":106193,"journal":{"name":"2014 11th Workshop on Positioning, Navigation and Communication (WPNC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123866375","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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