IEEE Journal of Indoor and Seamless Positioning and Navigation最新文献

Switching Model Stein Variational Sampling Filter for Mixed LOS/NLOS Industrial Indoor Positioning 切换模型Stein变分采样滤波器用于混合LOS/NLOS工业室内定位

IEEE Journal of Indoor and Seamless Positioning and Navigation Pub Date : 2025-07-16 DOI: 10.1109/JISPIN.2025.3589958

Marco Piavanini;Mattia Brambilla;Monica Nicoli

{"title":"Switching Model Stein Variational Sampling Filter for Mixed LOS/NLOS Industrial Indoor Positioning","authors":"Marco Piavanini;Mattia Brambilla;Monica Nicoli","doi":"10.1109/JISPIN.2025.3589958","DOIUrl":"https://doi.org/10.1109/JISPIN.2025.3589958","url":null,"abstract":"Internet of Things wireless technologies serve as key enabler for location-based services in emerging applications, such as autonomous robotics, industrial automation, augmented reality, and virtual reality. Wideband technologies, including ultra wideband (UWB) and 5G-advanced millimeter-waves, are the preferred solutions in these contexts for their high potentials in precise positioning. A main challenge is the mitigation of radio propagation effects that arise in complex environments, such as in industrial facilities, where frequent blockage events limit the accuracy and integrity of localization services. This article tackles the problem focusing on precise indoor navigation in industrial environments with dense and dynamic blockage conditions. Our proposal relies on an innovative particle filtering technique, based on the Stein variational adaptive importance sampling, to improve the sampled representation of the location posterior distribution by integrating prior information on the intermittent visibility-blockage dynamics. We assess the proposed solution through indoor experiments conducted in industrial scenarios using UWB devices. Our results show significant improvements with respect to state-of-the-art filters in terms of both accuracy and robustness of the location tracking.","PeriodicalId":100621,"journal":{"name":"IEEE Journal of Indoor and Seamless Positioning and Navigation","volume":"3 ","pages":"215-226"},"PeriodicalIF":0.0,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11081429","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reconstruction of an Independent Data-Driven TEC Model Using Machine Learning 用机器学习重建独立数据驱动的TEC模型

IEEE Journal of Indoor and Seamless Positioning and Navigation Pub Date : 2025-06-09 DOI: 10.1109/JISPIN.2025.3577979

Majed Ramzi Imad;Jani Käppi;Elena Simona Lohan;Jari Nurmi;Jari Syrjärinne

{"title":"Reconstruction of an Independent Data-Driven TEC Model Using Machine Learning","authors":"Majed Ramzi Imad;Jani Käppi;Elena Simona Lohan;Jari Nurmi;Jari Syrjärinne","doi":"10.1109/JISPIN.2025.3577979","DOIUrl":"https://doi.org/10.1109/JISPIN.2025.3577979","url":null,"abstract":"This article proposes a new model based on supervised machine learning designed for global total electron content (TEC) prediction without relying on atmospheric or solar parameters. The model uses a feedforward neural network (FFNN) with two hidden layers, giving it low complexity and computational cost. By leveraging machine-learning techniques, this model improves a previously established data-driven model proposed by the authors. Our model is trained using TEC data from solar cycle 23, solar cycle 24, and different combinations of both solar cycles. The model is then tested with global ionospheric maps from the <inline-formula><tex-math>$25text{th}$</tex-math></inline-formula> solar cycle, which were obtained from the International GNSS Service (IGS) database. Our model is also tested with TEC data from the Madrigal database over specific locations and on days with different solar activity levels. The International Reference Ionosphere (IRI) model was used as a benchmark to our model throughout these tests. The results prove that training with data from concatenated solar cycles yields the best performance. When tested with IGS data, our model achieved an average mean absolute error (MAE) of <inline-formula><tex-math>$5.33$</tex-math></inline-formula> TEC units, which is nearly 15.5% less than what IRI achieved. When compared with data from Madrigal, the model achieved an average MAE of 3.9, 7.1, and 19.9 TEC units on days with quiet, active, and extreme solar activities, respectively. In contrast, the IRI model achieved an average MAE of 5.4, 8, and 15.5 for the same days. Remarkably, our new model has a size of only 36 <inline-formula><tex-math>$mathrm{k}$</tex-math></inline-formula>B, representing over a 1800-fold reduction in size compared to the original data-driven model. Consequently, our proposed model can be regarded as a simple and robust yet precise and independent global TEC model.","PeriodicalId":100621,"journal":{"name":"IEEE Journal of Indoor and Seamless Positioning and Navigation","volume":"3 ","pages":"205-214"},"PeriodicalIF":0.0,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11028966","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multipath-Assisted Smartphone Tracking Using a Single Speaker and a Built-In Monaural Microphone 使用单个扬声器和内置单声道麦克风的多路径辅助智能手机跟踪

IEEE Journal of Indoor and Seamless Positioning and Navigation Pub Date : 2025-06-09 DOI: 10.1109/JISPIN.2025.3577976

Ibuki Yoshida;Masanari Nakamura;Hiroaki Murakami;Hiromichi Hashizume;Masanori Sugimoto

{"title":"Multipath-Assisted Smartphone Tracking Using a Single Speaker and a Built-In Monaural Microphone","authors":"Ibuki Yoshida;Masanari Nakamura;Hiroaki Murakami;Hiromichi Hashizume;Masanori Sugimoto","doi":"10.1109/JISPIN.2025.3577976","DOIUrl":"https://doi.org/10.1109/JISPIN.2025.3577976","url":null,"abstract":"The use of location data offers significant convenience in both daily life and industry. However, global positioning system (GPS) is not effective indoors, so alternative technologies are necessary. Current positioning technologies require multiple transmitters and receivers or precollected data, leading to high installation and implementation costs. Our study presents a low-cost tracking method that utilizes a single speaker installed on the ceiling and a smartphone’s monaural microphone. We leverage reflected waves from the walls and floor, treating them as signals from virtual speakers at the mirror-image positions of these surfaces. This approach ensures the generation of necessary signals for positioning and allows for accurate tracking using only a single speaker. However, as all the reflected waves are quite similar, it becomes challenging to associate each reflected wave with its corresponding virtual speaker. We designed an evaluation function to address this, considering real-world challenges, such as undetected reflected waves, outliers, and overlapping signals. We evaluate the correspondence between the prediction and the observation using a likelihood function, weighted by the number of outliers. When the reflected signals are overlapped, we introduce ambiguity by increasing the variance of the normal distribution. Our method accurately identifies reflected waves and estimates the target’s trajectory with precision. We evaluated the method under varying conditions across multiple paths, achieving positioning accuracy with a 50th percentile error of 0.34 m and a 90th percentile error of 0.64 m. This led to a 62% performance improvement compared to the scenario that does not account for real-world challenges.","PeriodicalId":100621,"journal":{"name":"IEEE Journal of Indoor and Seamless Positioning and Navigation","volume":"3 ","pages":"195-204"},"PeriodicalIF":0.0,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11029125","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144367037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing Spreading Code Authentication in GNSS: A Statistical Multisignal Approach 增强GNSS扩频码认证：一种统计多信号方法

IEEE Journal of Indoor and Seamless Positioning and Navigation Pub Date : 2025-04-28 DOI: 10.1109/JISPIN.2025.3564896

Francesco Ardizzon;Laura Crosara;Stefano Tomasin;Nicola Laurenti

{"title":"Enhancing Spreading Code Authentication in GNSS: A Statistical Multisignal Approach","authors":"Francesco Ardizzon;Laura Crosara;Stefano Tomasin;Nicola Laurenti","doi":"10.1109/JISPIN.2025.3564896","DOIUrl":"https://doi.org/10.1109/JISPIN.2025.3564896","url":null,"abstract":"The threat of signal spoofing against global navigation satellite system has grown in recent years and has motivated the study of antispoofing techniques. This article addresses the challenge of verifying the authenticity of signals protected by spreading code authentication. Conventional methods rely on either the correlation or cross-energy checks between the received signal and a local replica of the transmitted signal generated by the verifier using the authentic code. However, these methods are vulnerable to specific attacks. In particular, we show how to forge an effective spoofing signal just by using publicly available information. As a countermeasure, we propose a two-step authentication protocol leveraging the statistical independence of legitimate signals. First, we define a <italic>reliability metric</i> based on the generalized likelihood ratio for each signal, with higher values indicating greater signal reliability. In the second step, we select the most reliable signals to compute the position, velocity, and time (PVT) and perform a multisignal authentication check, combining the reliability metrics to validate the authenticity of the final PVT solution. Its robustness is proved by testing it against a wide class of attacks. Among others, these include the optimal attack against the cross-energy check and the attack that will be proven to be statistically optimal against the proposed check itself. Finally, we also test the performance of the scheme in a scenario where only a subset of the signals has been spoofed.","PeriodicalId":100621,"journal":{"name":"IEEE Journal of Indoor and Seamless Positioning and Navigation","volume":"3 ","pages":"128-141"},"PeriodicalIF":0.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10979356","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144090733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Toward Feature-Based Low-Latency Localization With Rotating LiDARs 基于特征的旋转激光雷达低延迟定位

IEEE Journal of Indoor and Seamless Positioning and Navigation Pub Date : 2025-04-18 DOI: 10.1109/JISPIN.2025.3562512

Lukas Beer;Thorsten Luettel;Mirko Maehlisch

{"title":"Toward Feature-Based Low-Latency Localization With Rotating LiDARs","authors":"Lukas Beer;Thorsten Luettel;Mirko Maehlisch","doi":"10.1109/JISPIN.2025.3562512","DOIUrl":"https://doi.org/10.1109/JISPIN.2025.3562512","url":null,"abstract":"An accurate global position is often considered to be one of the main requirements for autonomous driving. Even though GNSS provides a solution, it is dependent on the environment and not accurate enough. In this article, we present a fully GNSS-free localization, which uses maps and LiDAR to estimate the position of the vehicle. We tackle two major drawbacks of LiDAR-based localization: the limitation to the mapped area and a generally high latency. We use two different maps: a high-precision geometric HD map and a more general semantic occupancy grid map, resulting from OpenStreetMap. This allows us to provide a high-precision localization within the mapped area and a rough position estimate outside the mapped area. The coupling ensures seamless transitions when leaving or entering the HD map area, without losing the position and without the need for GNSS or loop closures. The latency is minimized by employing a continuous feature extraction. Instead of waiting for the full 360<inline-formula><tex-math>$^circ$</tex-math></inline-formula> rotation of the LiDAR, we extract semantic features during the rotation by combining a continuous instance and semantic segmentation. This reduces the latency to a minimum. We evaluate our approach in real-world experiments and show that it can localize the vehicle with a mean absolute error of 0.12 m using a full rotation of the LiDAR sensor, and 0.17 m with the continuous processing pipeline.","PeriodicalId":100621,"journal":{"name":"IEEE Journal of Indoor and Seamless Positioning and Navigation","volume":"3 ","pages":"105-116"},"PeriodicalIF":0.0,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10970261","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143908352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Metric-Based Few-Shot Learning With Triplet Selection for Adaptive GNSS Interference Classification 基于度量的基于三元组选择的少镜头学习自适应GNSS干扰分类

IEEE Journal of Indoor and Seamless Positioning and Navigation Pub Date : 2025-04-17 DOI: 10.1109/JISPIN.2025.3562140

Felix Ott;Lucas Heublein;Tobias Feigl;Alexander Rügamer;Christopher Mutschler

{"title":"Metric-Based Few-Shot Learning With Triplet Selection for Adaptive GNSS Interference Classification","authors":"Felix Ott;Lucas Heublein;Tobias Feigl;Alexander Rügamer;Christopher Mutschler","doi":"10.1109/JISPIN.2025.3562140","DOIUrl":"https://doi.org/10.1109/JISPIN.2025.3562140","url":null,"abstract":"Jamming devices pose a significant threat as they disrupt signals from the global navigation satellite system (GNSS) and thus compromise the accuracy and robustness of positioning systems. The detection of anomalies in frequency snapshots is essential to effectively counteract these interferences. Furthermore, the ability to adapt to diverse and previously unseen interference characteristics is critical to ensuring the reliability of GNSS in real-world applications. In this article, we propose a few-shot learning (FSL) approach to adapt to new classes of interference. We employ pairwise learning techniques, including triplet and quadruplet loss functions, during the training process to enhance the latent representation. In addition, we conducted a benchmark evaluation of state-of-the-art triplet learning methodologies utilizing GNSS datasets. Our method incorporates quadruplet selection, allowing the model to learn representations from various classes of positive and negative interference. Moreover, our quadruplet variant selects pairs based on aleatoric and epistemic uncertainty, facilitating differentiation between similar classes. We evaluated all methods using a publicly available indoor GNSS dataset collected in controlled environments characterized by various multipath effects, and using a dataset obtained from a highway bridge spanning a real-world German highway. Furthermore, we record and publish a second dataset from a highway featuring eight interference classes, in which our FSL method utilizing quadruplet loss demonstrates superior performance in jammer classification accuracy, achieving a rate of 97.66%.","PeriodicalId":100621,"journal":{"name":"IEEE Journal of Indoor and Seamless Positioning and Navigation","volume":"3 ","pages":"81-104"},"PeriodicalIF":0.0,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10969504","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143908429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Positioning and Tracking in DECT-2020 NR With Proactive Anchor Selection for Range, Angle, and RSS Measurements 在DECT-2020 NR中进行定位和跟踪，主动选择锚点进行范围、角度和RSS测量

IEEE Journal of Indoor and Seamless Positioning and Navigation Pub Date : 2025-04-11 DOI: 10.1109/JISPIN.2025.3559907

Antti Saikko;Jukka Talvitie;Joonas Säe;Juho Pirskanen;Mikko Valkama

{"title":"Positioning and Tracking in DECT-2020 NR With Proactive Anchor Selection for Range, Angle, and RSS Measurements","authors":"Antti Saikko;Jukka Talvitie;Joonas Säe;Juho Pirskanen;Mikko Valkama","doi":"10.1109/JISPIN.2025.3559907","DOIUrl":"https://doi.org/10.1109/JISPIN.2025.3559907","url":null,"abstract":"This article addresses efficient positioning and user device tracking in Internet-of-Things (IoT) networks with particular focus on the new DECT-2020 New Radio standard—the first noncellular 5G technology standard in the world. Stemming from fundamental performance requirements of IoT networks, for example, related to energy consumption, latency, and reliability, it is important to utilize available radio resources efficiently, while avoiding redundant transmissions and signaling. In this article, we extend our earlier proposed tracking-based positioning solution, which utilized Fisher information to select the most beneficial range and angle measurements, to cover also received signal strength (RSS)-based measurements and particle filter-based solutions. By exploiting prior information inherited from tracking-based positioning solutions, it is possible to proactively select the most valuable positioning measurements, and thus save valuable effort and time in acquiring and processing positioning measurements without sacrificing the positioning performance in practice. Through extensive numerical evaluations, considering range, angle, and RSS measurements, we show that the proposed anchor selection method is able to outperform the traditional signal-to-noise ratio-based measurement selection approach, while enabling positioning with a smaller number of measurements. In addition, we illustrate the effect of prior information quality on the proposed method performance by varying the measurement interval in the tracking process. The numerical results show that when only two anchors are utilized, approximately up to 10%–50% reduction in positioning root-mean-square error can be achieved depending on the considered measurement type.","PeriodicalId":100621,"journal":{"name":"IEEE Journal of Indoor and Seamless Positioning and Navigation","volume":"3 ","pages":"70-80"},"PeriodicalIF":0.0,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10963685","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving OSNMAlib: New Formats, Features, and Monitoring Capabilities 改进OSNMAlib：新的格式、特性和监控功能

IEEE Journal of Indoor and Seamless Positioning and Navigation Pub Date : 2025-04-08 DOI: 10.1109/JISPIN.2025.3558771

Aleix Galan-Figueras;Cristian Iñiguez;Ignacio Fernandez-Hernandez;Sofie Pollin;Gonzalo Seco-Granados

{"title":"Improving OSNMAlib: New Formats, Features, and Monitoring Capabilities","authors":"Aleix Galan-Figueras;Cristian Iñiguez;Ignacio Fernandez-Hernandez;Sofie Pollin;Gonzalo Seco-Granados","doi":"10.1109/JISPIN.2025.3558771","DOIUrl":"https://doi.org/10.1109/JISPIN.2025.3558771","url":null,"abstract":"Galileo will declare Open Service Navigation Message Authentication (OSNMA), a civil Global Navigation Satellite System (GNSS) signal authentication scheme, operational in the near future. OSNMAlib, an open-source library that implements OSNMA, was presented two years ago after the test phase of the protocol started and has since undergone several upgrades. In this article, we disclose these upgrades, which comprise new input sources, new features and optimizations, and the creation of an OSNMA real-time monitoring website. For each input source, we describe how can they be integrated within an OSNMA library and what pitfalls to avoid. The new features include optimizations for data retrieval such as the use of dual frequency and Reed-Solomon encoding, which are evaluated in urban and open sky scenarios using real recorded data. The new JavaScript Object Notation (JSON) logging format aimed at researchers is used in <italic>osnmalib.eu</i> website to display, in a friendly and understandable way, the live Galileo and OSNMA messages and the OSNMAlib authentication output. In addition, the website also provides the I/NAV data bits to help snapshot receivers and other GNSS-based applications.","PeriodicalId":100621,"journal":{"name":"IEEE Journal of Indoor and Seamless Positioning and Navigation","volume":"3 ","pages":"117-127"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10955685","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143949158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Range-Free Positioning in NB-IoT Networks by Machine Learning: Beyond W$k$NN 基于机器学习的NB-IoT网络无距离定位：超越W$k$NN

IEEE Journal of Indoor and Seamless Positioning and Navigation Pub Date : 2025-04-07 DOI: 10.1109/JISPIN.2025.3558465

Luca De Nardis;Marco Savelli;Giuseppe Caso;Federico Ferretti;Lorenzo Tonelli;Nadir Bouzar;Anna Brunstrom;Özgü Alay;Marco Neri;Fouzia Elbahhar Bokour;Maria-Gabriella Di Benedetto

{"title":"Range-Free Positioning in NB-IoT Networks by Machine Learning: Beyond W$k$NN","authors":"Luca De Nardis;Marco Savelli;Giuseppe Caso;Federico Ferretti;Lorenzo Tonelli;Nadir Bouzar;Anna Brunstrom;Özgü Alay;Marco Neri;Fouzia Elbahhar Bokour;Maria-Gabriella Di Benedetto","doi":"10.1109/JISPIN.2025.3558465","DOIUrl":"https://doi.org/10.1109/JISPIN.2025.3558465","url":null,"abstract":"Existing proposals for positioning in narrowband Internet of Things (NB-IoT) networks based on range estimation are characterized by either low accuracy or lack of compliance with 3GPP standards. While range-free approaches taking advantage of machine learning (ML) have been recently proposed as a potential way forward, their evaluation has been carried out only in simulated environments, with the exception of weighted <inline-formula><tex-math>$k$</tex-math></inline-formula> nearest neighbors (W<inline-formula><tex-math>$k$</tex-math></inline-formula>NN), recently tested on experimental data. This work investigates five ML strategies for range-free positioning in NB-IoT networks, based on W<inline-formula><tex-math>$k$</tex-math></inline-formula>NN and its combination with preprocessing and classification algorithms as well as on artificial neural networks (ANNs). The strategies are evaluated on experimental data and are compared based on a set of key performance indicators measuring both positioning performance and processing load. Two different datasets taken at different times and locations were adopted, enabling the validation of strategies optimized on one testbed on the other, as well as the study of the impact of dataset features on performance. Results show that range-free positioning using ML is a viable solution in commercial NB-IoT networks, and that W<inline-formula><tex-math>$k$</tex-math></inline-formula>NN and ANNs are at the two extremes in terms of a performance/complexity tradeoff; intermediate tradeoffs can be achieved by combining W<inline-formula><tex-math>$k$</tex-math></inline-formula>NN with preprocessing techniques and classification models.","PeriodicalId":100621,"journal":{"name":"IEEE Journal of Indoor and Seamless Positioning and Navigation","volume":"3 ","pages":"53-69"},"PeriodicalIF":0.0,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10950079","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143875273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comprehensive Assessment of Open Science Practices in Indoor Positioning: Open Data, Code, and Material 室内定位中开放科学实践的综合评估：开放数据、代码和材料

IEEE Journal of Indoor and Seamless Positioning and Navigation Pub Date : 2025-03-14 DOI: 10.1109/JISPIN.2025.3570258

Grigorios G. Anagnostopoulos;Paolo Barsocchi;Antonino Crivello;Cristiano Pendão;Ivo Silva;Joaquín Torres-Sospedra

{"title":"Comprehensive Assessment of Open Science Practices in Indoor Positioning: Open Data, Code, and Material","authors":"Grigorios G. Anagnostopoulos;Paolo Barsocchi;Antonino Crivello;Cristiano Pendão;Ivo Silva;Joaquín Torres-Sospedra","doi":"10.1109/JISPIN.2025.3570258","DOIUrl":"https://doi.org/10.1109/JISPIN.2025.3570258","url":null,"abstract":"Transparency and verifiability have long been regarded as cornerstones of the scientific ethos and practice. However, persistent reproducibility challenges across numerous disciplines have brought renewed attention to the imperative for widespread adoption of open science practices. These considerations are particularly relevant to the research field of indoor positioning. Open data and open code sharing are gradually gaining traction in the field, but are still far from standard practice. This study comprehensively evaluates the extent of the adoption of open science practices within the community of the International Conference on Indoor Positioning and Indoor Navigation (IPIN), by systematically analyzing all reference papers from the 2019 to 2024 editions of the IPIN. The work thoroughly examines the open data and code usage, and the use of other types of open materials while performing a particular close-up review of the open data that are leveraged in these studies. Our findings reveal that 21.7% of papers use open research data, 8.3% utilize open code, and 20.2% incorporate other open materials. However, only 6.8% of papers provide both open data and code. Moreover, emerging patterns and intuitive best practices are highlighted. The complete characterization of all reviewed publications is publicly available. This study brings to light the need for wider adoption of open science practices, to enhance the transparency, reproducibility, replicability, and reliability of research outcomes in the field of indoor positioning.","PeriodicalId":100621,"journal":{"name":"IEEE Journal of Indoor and Seamless Positioning and Navigation","volume":"3 ","pages":"175-194"},"PeriodicalIF":0.0,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11003858","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144229467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0