Pub Date : 2014-03-12DOI: 10.1109/WPNC.2014.6843289
Benjamin Wagner, Tobias Ritt, D. Timmermann
The positioning and tracing of multiple users is an important data source for ubiquitous assistance in smart environments and its superimposed intention recognition systems. Within application areas like elderly care or ambient assisted living, non-invasive, wireless, privacy preserving j technologies are indispensable. Device-free localization approaches (DFL) provide these advantages with no need for user-attached hardware. In our recent work we provide a passive RFID enabled and radio tomography based approach, which combines privacy and cost effectiveness. Within our previous proof of concepts only one user scenarios were investigated. An open problem within the DFL research is the recognition and distinction of multiple users. In this work we show related approaches and define methods and algorithms for multi user support. We conduct experiments in an indoor room DFL scenario for proof of concept and validation. We show that it is possible to recognize and distinct up to 3 users with reasonable precision.
{"title":"Multiple user recognition with passive RFID tomography","authors":"Benjamin Wagner, Tobias Ritt, D. Timmermann","doi":"10.1109/WPNC.2014.6843289","DOIUrl":"https://doi.org/10.1109/WPNC.2014.6843289","url":null,"abstract":"The positioning and tracing of multiple users is an important data source for ubiquitous assistance in smart environments and its superimposed intention recognition systems. Within application areas like elderly care or ambient assisted living, non-invasive, wireless, privacy preserving j technologies are indispensable. Device-free localization approaches (DFL) provide these advantages with no need for user-attached hardware. In our recent work we provide a passive RFID enabled and radio tomography based approach, which combines privacy and cost effectiveness. Within our previous proof of concepts only one user scenarios were investigated. An open problem within the DFL research is the recognition and distinction of multiple users. In this work we show related approaches and define methods and algorithms for multi user support. We conduct experiments in an indoor room DFL scenario for proof of concept and validation. We show that it is possible to recognize and distinct up to 3 users with reasonable precision.","PeriodicalId":106193,"journal":{"name":"2014 11th Workshop on Positioning, Navigation and Communication (WPNC)","volume":"16 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":"128326091","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.2014.6843297
Behailu Y. Shikur, T. Weber
In this paper, we consider localization in non-line-of-sight environments. We present algorithms to estimate the most likely position or the most likely trajectory of a mobile station given a sequence of time-of-arrival, angle-of-departure, and doppler-shift observations. Discretized positions are considered for computational feasibility of the proposed algorithms. The mobility model of the mobile station is defined by a Markov model. The most likely position and the most likely trajectory of the mobile station are efficiently computed using the forward-backward algorithm and the Viterbi algorithm, respectively given the whole sequence of observations. An online Bayesian recursive algorithm which estimates the most probable position of the mobile station is also proposed. It is shown, through simulations, that we can get a satisfactory performance given that the mobile station is not stationary during the course of the tracking time.
{"title":"Localization in NLOS environments using TOA, AOD, and Doppler-shift","authors":"Behailu Y. Shikur, T. Weber","doi":"10.1109/WPNC.2014.6843297","DOIUrl":"https://doi.org/10.1109/WPNC.2014.6843297","url":null,"abstract":"In this paper, we consider localization in non-line-of-sight environments. We present algorithms to estimate the most likely position or the most likely trajectory of a mobile station given a sequence of time-of-arrival, angle-of-departure, and doppler-shift observations. Discretized positions are considered for computational feasibility of the proposed algorithms. The mobility model of the mobile station is defined by a Markov model. The most likely position and the most likely trajectory of the mobile station are efficiently computed using the forward-backward algorithm and the Viterbi algorithm, respectively given the whole sequence of observations. An online Bayesian recursive algorithm which estimates the most probable position of the mobile station is also proposed. It is shown, through simulations, that we can get a satisfactory performance given that the mobile station is not stationary during the course of the tracking time.","PeriodicalId":106193,"journal":{"name":"2014 11th Workshop on Positioning, Navigation and Communication (WPNC)","volume":"59 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":"121134237","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.2014.6843299
E. Staudinger, A. Dammann
Ranging accuracy and reliability is crucial for any cooperative- and non-cooperative positioning system applied for unmanned vehicle localization, and formation estimation. State of the art systems exploit received signal strength (RSS) from WiFi devices, or ultra-wide bandwidth (UWB) timing based range estimation. RSS proved to be unreliable in environments with multipath, and UWB combats multipath at the cost of high bandwidth and specialized hardware. We tackle this problem with round-trip delay (RTD) based range estimation with orthogonal frequency division multiplex (OFDM) modulated signals which are widely used in WiFi and 3GPP-LTE. In this paper, we present our developed prototype and two different outdoor environments with varying multipath conditions. Measurements along ground truth points are collected for each environment and post-processed. We apply four different estimators, two based on cross-correlation and interpolation, and two based on Maximum-likelihood (ML) multipath estimation. Our analysis reveals that a simple correlation based estimator with interpolation and smart thresholding is sufficient and a very good trade-off between computational complexity and accuracy compared to ML multipath estimators. These outdoor experiments show that our simple ranging technique is suitable for peer-to-peer distance estimation with low bandwidth, low transmit power, and can be exploited for localization and formation estimation in cyber-physical systems.
{"title":"Round-trip delay ranging with OFDM signals — Performance evaluation with outdoor experiments","authors":"E. Staudinger, A. Dammann","doi":"10.1109/WPNC.2014.6843299","DOIUrl":"https://doi.org/10.1109/WPNC.2014.6843299","url":null,"abstract":"Ranging accuracy and reliability is crucial for any cooperative- and non-cooperative positioning system applied for unmanned vehicle localization, and formation estimation. State of the art systems exploit received signal strength (RSS) from WiFi devices, or ultra-wide bandwidth (UWB) timing based range estimation. RSS proved to be unreliable in environments with multipath, and UWB combats multipath at the cost of high bandwidth and specialized hardware. We tackle this problem with round-trip delay (RTD) based range estimation with orthogonal frequency division multiplex (OFDM) modulated signals which are widely used in WiFi and 3GPP-LTE. In this paper, we present our developed prototype and two different outdoor environments with varying multipath conditions. Measurements along ground truth points are collected for each environment and post-processed. We apply four different estimators, two based on cross-correlation and interpolation, and two based on Maximum-likelihood (ML) multipath estimation. Our analysis reveals that a simple correlation based estimator with interpolation and smart thresholding is sufficient and a very good trade-off between computational complexity and accuracy compared to ML multipath estimators. These outdoor experiments show that our simple ranging technique is suitable for peer-to-peer distance estimation with low bandwidth, low transmit power, and can be exploited for localization and formation estimation in cyber-physical systems.","PeriodicalId":106193,"journal":{"name":"2014 11th Workshop on Positioning, Navigation and Communication (WPNC)","volume":"11 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":"132811556","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.2014.6843303
Abdo Gaber, Ali M. Alsaih, A. Omar
This contribution is addressed to the problem of highly resolving the propagation time delays and the relative amplitudes associated with signals in multipath communication channels. The Unitary Matrix Pencil (UMP) algorithm is applied in a new way to estimate these parameters from the measured channel frequency response (CFR) using wideband orthogonal multicarrier signals. The mobile unit (MU) is often in a non-line-of-sight (NLOS) state, and the direct path could be completely blocked due to the harsh nature of indoor environments. There-fore, the estimated time delay of the first path should be identified either as a very weak detected direct path (DDP) or even as an undetected direct path (UDP). Consequently, precise estimation of the channel profile parameters is not enough for high-resolution wireless indoor positioning system. However, it stays representing a key element to identify the UDP condition. In this work, the accurate estimation of channel profile parameters and the proper modeling of DDP and UDP channel profiles will be treated and addressed to the problem of UDP identification. Experimental results using the emerging IEEE 802.11ac standard reveal that the achieved probability of correct identification can be more than 96.6% at the smallest bandwidth.
{"title":"UDP identification for high-resolution wireless indoor positioning based on IEEE 802.11ac","authors":"Abdo Gaber, Ali M. Alsaih, A. Omar","doi":"10.1109/WPNC.2014.6843303","DOIUrl":"https://doi.org/10.1109/WPNC.2014.6843303","url":null,"abstract":"This contribution is addressed to the problem of highly resolving the propagation time delays and the relative amplitudes associated with signals in multipath communication channels. The Unitary Matrix Pencil (UMP) algorithm is applied in a new way to estimate these parameters from the measured channel frequency response (CFR) using wideband orthogonal multicarrier signals. The mobile unit (MU) is often in a non-line-of-sight (NLOS) state, and the direct path could be completely blocked due to the harsh nature of indoor environments. There-fore, the estimated time delay of the first path should be identified either as a very weak detected direct path (DDP) or even as an undetected direct path (UDP). Consequently, precise estimation of the channel profile parameters is not enough for high-resolution wireless indoor positioning system. However, it stays representing a key element to identify the UDP condition. In this work, the accurate estimation of channel profile parameters and the proper modeling of DDP and UDP channel profiles will be treated and addressed to the problem of UDP identification. Experimental results using the emerging IEEE 802.11ac standard reveal that the achieved probability of correct identification can be more than 96.6% at the smallest bandwidth.","PeriodicalId":106193,"journal":{"name":"2014 11th Workshop on Positioning, Navigation and Communication (WPNC)","volume":"81 4 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":"133976969","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.2014.6843285
A. Bilajbegovic, R. Lehmann
The iTraceRT-F200-E (made by iMAR Navigation GmbH) is a modern INS/GNSS device for terrestrial and airborne navigation. We investigate the internal and external accuracies when crossing tunnels by car. We use both the real time solution provided by the internal computer as well as postprocessing solutions computed by Novatel's Waypoint Inertial Explorer 8.10. The accuracy specifications of the manufacturer were not always confirmed.
iTraceRT-F200-E(由iMAR Navigation GmbH制造)是一种用于地面和机载导航的现代INS/GNSS设备。我们考察了汽车穿越隧道时的内部和外部精度。我们既使用内部计算机提供的实时解决方案，也使用Novatel的Waypoint Inertial Explorer 8.10计算的后处理解决方案。制造商的精度规格并不总是得到确认。
{"title":"Geodetic investigation of accuracy and reliability of INS/GNSS system iTraceRT-F200-E for navigation in tunnels","authors":"A. Bilajbegovic, R. Lehmann","doi":"10.1109/WPNC.2014.6843285","DOIUrl":"https://doi.org/10.1109/WPNC.2014.6843285","url":null,"abstract":"The iTraceRT-F200-E (made by iMAR Navigation GmbH) is a modern INS/GNSS device for terrestrial and airborne navigation. We investigate the internal and external accuracies when crossing tunnels by car. We use both the real time solution provided by the internal computer as well as postprocessing solutions computed by Novatel's Waypoint Inertial Explorer 8.10. The accuracy specifications of the manufacturer were not always confirmed.","PeriodicalId":106193,"journal":{"name":"2014 11th Workshop on Positioning, Navigation and Communication (WPNC)","volume":"21 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":"121160511","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.2014.6843286
F. Stephan, S. Zeisberg, O. Michler
One of the important aspects in wireless sensor networks is an energy efficient communication protocol to allow battery powered devices with a lifetime of several of years. The most important step therefor is to maximize the time the network nodes staying in power down modes. The possibility to measure distances with an easy-to-use and low cost phase difference of arrival method between network nodes enables an accurate positioning of these nodes. Because this technology needs additional requirements on synchronization and channel access, this paper describes a centralized multi-hop beaconing protocol to synchronize all the devices and to schedule the guaranteed timeslots for the ranging procedures. This yields to an increase of time in power down mode and an increase of the maximum rate of distance measurements per second. Measurements were made at the implemented system at company ZIGPOS GmbH.
{"title":"Multi-hop synchronization and timeslot distribution method for IEEE 802.15.4 based positioning networks","authors":"F. Stephan, S. Zeisberg, O. Michler","doi":"10.1109/WPNC.2014.6843286","DOIUrl":"https://doi.org/10.1109/WPNC.2014.6843286","url":null,"abstract":"One of the important aspects in wireless sensor networks is an energy efficient communication protocol to allow battery powered devices with a lifetime of several of years. The most important step therefor is to maximize the time the network nodes staying in power down modes. The possibility to measure distances with an easy-to-use and low cost phase difference of arrival method between network nodes enables an accurate positioning of these nodes. Because this technology needs additional requirements on synchronization and channel access, this paper describes a centralized multi-hop beaconing protocol to synchronize all the devices and to schedule the guaranteed timeslots for the ranging procedures. This yields to an increase of time in power down mode and an increase of the maximum rate of distance measurements per second. Measurements were made at the implemented system at company ZIGPOS GmbH.","PeriodicalId":106193,"journal":{"name":"2014 11th Workshop on Positioning, Navigation and Communication (WPNC)","volume":"5 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":"123730583","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.2014.6843291
Behailu Y. Shikur, T. Weber
In this paper we discuss robust cooperative localization in mixed line-of-sight and non-line-of-sight environments using time-of-arrival measurements. The mixed line-of-sight and non-line-of-sight environment is statistically modeled using a contaminated Gaussian mixture model in which the non-line-of-sight propagations are assumed to cause a positive bias in the time-of-arrival measurements. The non-line-of-sight propagations severely degrade the performance of localization algorithms which assume line-of-sight propagations. The maximum likelihood cooperative localization estimation is a highly non-linear and non-convex optimization problem which cannot be solved in a closed-form. Hence, we propose an approximate iterative robust cooperative localization algorithm to mitigate the impact of the non-line-of-sight propagations. The proposed robust localization algorithm yields a satisfactory performance in the presence of the non-line-of-sight propagations which would otherwise severely degrade the localization performance. Monte Carlo simulations show that the proposed robust cooperative localization algorithm is indeed robust to the increase in the ratio of the number of the non-line-of-sight propagations to line-of-sight propagations and the strength of the non-line-of-sight propagations.
{"title":"Robust cooperative localization in mixed LOS and NLOS environments using TOA","authors":"Behailu Y. Shikur, T. Weber","doi":"10.1109/WPNC.2014.6843291","DOIUrl":"https://doi.org/10.1109/WPNC.2014.6843291","url":null,"abstract":"In this paper we discuss robust cooperative localization in mixed line-of-sight and non-line-of-sight environments using time-of-arrival measurements. The mixed line-of-sight and non-line-of-sight environment is statistically modeled using a contaminated Gaussian mixture model in which the non-line-of-sight propagations are assumed to cause a positive bias in the time-of-arrival measurements. The non-line-of-sight propagations severely degrade the performance of localization algorithms which assume line-of-sight propagations. The maximum likelihood cooperative localization estimation is a highly non-linear and non-convex optimization problem which cannot be solved in a closed-form. Hence, we propose an approximate iterative robust cooperative localization algorithm to mitigate the impact of the non-line-of-sight propagations. The proposed robust localization algorithm yields a satisfactory performance in the presence of the non-line-of-sight propagations which would otherwise severely degrade the localization performance. Monte Carlo simulations show that the proposed robust cooperative localization algorithm is indeed robust to the increase in the ratio of the number of the non-line-of-sight propagations to line-of-sight propagations and the strength of the non-line-of-sight propagations.","PeriodicalId":106193,"journal":{"name":"2014 11th Workshop on Positioning, Navigation and Communication (WPNC)","volume":"104 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":"115758542","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.2014.6843305
M. B. Kilani, A. J. Raymond, F. Gagnon, G. Gagnon, P. Lavoie
A tracking scenario comprising a mobile emitter node moving through an indoor environment covered by multiple anchor receivers is investigated in this work. A localization method based on received signal strength indicators (RSSI) and making use of the extended Kalman filter (EKF) and circularly polarized (CP) antennas is proposed. The EKF implements the position-velocity (PV) model, which assumes that the target is moving at a near-constant velocity during any given short time interval Δt. The measurement vector is composed of velocities in addition to RSSI values, which allow to deal with the error term between measurements and the propagation model directly. CP antennas are used on both the anchor nodes and the mobile node. These antennas are known to reduce the effects of multipath, especially those caused by single reflections. As a result, the RSSI values received in line of sight are more accurate and stable than those received from linearly polarized antennas. We tested our approach by tracking the movement of a robot following a predefined trajectory. The maximum location estimation error (LEE) is found to be 0.52 m. In addition, velocity changes are easily tracked during the target movement, which demonstrates the effectiveness of the proposed approach.
{"title":"RSSI-based indoor tracking using the extended Kalman filter and circularly polarized antennas","authors":"M. B. Kilani, A. J. Raymond, F. Gagnon, G. Gagnon, P. Lavoie","doi":"10.1109/WPNC.2014.6843305","DOIUrl":"https://doi.org/10.1109/WPNC.2014.6843305","url":null,"abstract":"A tracking scenario comprising a mobile emitter node moving through an indoor environment covered by multiple anchor receivers is investigated in this work. A localization method based on received signal strength indicators (RSSI) and making use of the extended Kalman filter (EKF) and circularly polarized (CP) antennas is proposed. The EKF implements the position-velocity (PV) model, which assumes that the target is moving at a near-constant velocity during any given short time interval Δt. The measurement vector is composed of velocities in addition to RSSI values, which allow to deal with the error term between measurements and the propagation model directly. CP antennas are used on both the anchor nodes and the mobile node. These antennas are known to reduce the effects of multipath, especially those caused by single reflections. As a result, the RSSI values received in line of sight are more accurate and stable than those received from linearly polarized antennas. We tested our approach by tracking the movement of a robot following a predefined trajectory. The maximum location estimation error (LEE) is found to be 0.52 m. In addition, velocity changes are easily tracked during the target movement, which demonstrates the effectiveness of the proposed approach.","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":"125119154","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.2014.6843295
Yuan Yang, Yubin Zhao, M. Kyas
A large number of indoor positioning systems are based on sensor networks or WLAN ranging techniques with a filter to remove the positioning uncertainty coming from the ranging errors. Bayesian filter has emerged as a useful approach for sequential position estimation, which generally resorts to a numerical solution due to the nonlinearity and the non-Gaussian nature of mobile positioning. The accuracy of numerical Bayesian approaches depends mostly on two factors: the sample density of the state approximation and how closely the state transition model mimics the true motion of each iteration. However, dense samples typically cause high computation and memory complexity; worse, an improper transition model can lead to the problem of filter divergence. We hold that in the presence of at least one line-of-sight (LOS) range, the state space can be effectively confined by the geometries of ranging measurements. Therefore, this paper proposes a geometric filter (GeoF) learning the transition model by the geometry of the most recent TOA ranges. The key idea of GeoF is to adaptively generate the sample set of the state based on the intersections of every pair-wise range circles. Therefore, our approach employs a very small number of samples, causing much smaller implementation and computation overhead compared to general numerical Bayesian approaches. The experiment results of mobile robot localization in typical LOS/NLOS mixed scenarios show that GeoF yields better performance over extended Kalman filter, generic particle filter and grid-based filter.
{"title":"GeoF: A geometric Bayesian filter for indoor position tracking in mixed LOS/NLOS conditions","authors":"Yuan Yang, Yubin Zhao, M. Kyas","doi":"10.1109/WPNC.2014.6843295","DOIUrl":"https://doi.org/10.1109/WPNC.2014.6843295","url":null,"abstract":"A large number of indoor positioning systems are based on sensor networks or WLAN ranging techniques with a filter to remove the positioning uncertainty coming from the ranging errors. Bayesian filter has emerged as a useful approach for sequential position estimation, which generally resorts to a numerical solution due to the nonlinearity and the non-Gaussian nature of mobile positioning. The accuracy of numerical Bayesian approaches depends mostly on two factors: the sample density of the state approximation and how closely the state transition model mimics the true motion of each iteration. However, dense samples typically cause high computation and memory complexity; worse, an improper transition model can lead to the problem of filter divergence. We hold that in the presence of at least one line-of-sight (LOS) range, the state space can be effectively confined by the geometries of ranging measurements. Therefore, this paper proposes a geometric filter (GeoF) learning the transition model by the geometry of the most recent TOA ranges. The key idea of GeoF is to adaptively generate the sample set of the state based on the intersections of every pair-wise range circles. Therefore, our approach employs a very small number of samples, causing much smaller implementation and computation overhead compared to general numerical Bayesian approaches. The experiment results of mobile robot localization in typical LOS/NLOS mixed scenarios show that GeoF yields better performance over extended Kalman filter, generic particle filter and grid-based filter.","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":"128876757","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.2014.6843301
P. Kolios, C. Laoudias, C. Panayiotou
RevolverNet, operates over wireless ad-hoc networks where nodes communicate in duty cycles. When not at sleep, nodes beacon their own data and listen for data coming from neighboring nodes. Importantly, this mode of operation is increasingly becoming a prominent feature in a variety of communication setups, including emergency response networks (ERNs). RevolverNet is purposefully designed to take advantage of these beaconing mechanisms to gather network intelligence and achieve data dissemination in a purely distributed and local fashion. We examine two favourable features of RevolverNet that are attractive to ERNs, namely topological mapping and node localization that are highly applicable to ERNs. We show how these two features can be extracted from the underlying adhoc network in an efficient manner and how they can subsequently be used to disseminate information in the network. We present preliminary results on the performance of RevolverNet and discuss future work.
{"title":"Improving the reliability of emergency response networks using revolvernet","authors":"P. Kolios, C. Laoudias, C. Panayiotou","doi":"10.1109/WPNC.2014.6843301","DOIUrl":"https://doi.org/10.1109/WPNC.2014.6843301","url":null,"abstract":"RevolverNet, operates over wireless ad-hoc networks where nodes communicate in duty cycles. When not at sleep, nodes beacon their own data and listen for data coming from neighboring nodes. Importantly, this mode of operation is increasingly becoming a prominent feature in a variety of communication setups, including emergency response networks (ERNs). RevolverNet is purposefully designed to take advantage of these beaconing mechanisms to gather network intelligence and achieve data dissemination in a purely distributed and local fashion. We examine two favourable features of RevolverNet that are attractive to ERNs, namely topological mapping and node localization that are highly applicable to ERNs. We show how these two features can be extracted from the underlying adhoc network in an efficient manner and how they can subsequently be used to disseminate information in the network. We present preliminary results on the performance of RevolverNet and discuss future work.","PeriodicalId":106193,"journal":{"name":"2014 11th Workshop on Positioning, Navigation and Communication (WPNC)","volume":"210 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":"131637357","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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