Journal articles on the topic 'Indoor Positioning System'
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Puri, Sahil. "Indoor Positioning System using Bluetooth." International Journal of Engineering Research 4, no. 5 (May 1, 2015): 244–47. http://dx.doi.org/10.17950/ijer/v4s5/507.
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Rutvik, Jaini. "Indoor Positioning System." International Journal of Applied Engineering Research 15, no. 12 (December 30, 2020): 1142–46. http://dx.doi.org/10.37622/ijaer/15.12.2020.1142-1146.
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Obretin, Alexandru Marius. "Infrastructure free indoor positioning system." Proceedings of the International Conference on Business Excellence 14, no. 1 (July 1, 2020): 124–33. http://dx.doi.org/10.2478/picbe-2020-0013.
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AbstractLatest technological advancement uncovered new social and entrepreneurial opportunities in fields like civil engineering and facility management. While most outdoor location challenges have been addressed in the past few years, with declassified military technologies such as Motion Imagery Standards Board and North Atlantic Treaty Organization Digital Motion Imagery Standard being integrated into solutions that enhance real-time emulation of surveillance video streams over digital maps, there is plenty of room for innovation when indoor location is considered. The market associated to indoor positioning is expected to significantly grow in the following decade since people spend more and more time indoors and promising advantages of such technologies have been identified in healthcare, retail, logistics and leisure. Yet, conventional indoor positioning systems mostly rely on costly and difficult to maintain infrastructure. Discordantly, the hereby paper is introducing an infrastructure free indoor positioning web application designed for routing people inside facilities and building evacuation scenarios. The proposed architecture is independent on external hardware or beacons, relying on a generic sensors framework that exposes the underlying capabilities of a mobile phone for data collection and internet connection for assessing current location and providing guidance in respect with an already known topography. Therefore, this design might be easily extended to various facilities, individualizing through no initial costs for sensors deployment and light resource consumption for the user, since data is not processed on a native application. Such flexibility is considered to optimize the navigation inside large public places and reduce the time required to find products, people or shops, offering the users more time for what matters.
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Dari, Yohanes Erwin, Suyoto Suyoto Suyoto, and Pranowo Pranowo Pranowo. "CAPTURE: A Mobile Based Indoor Positioning System using Wireless Indoor Positioning System." International Journal of Interactive Mobile Technologies (iJIM) 12, no. 1 (January 23, 2018): 61. http://dx.doi.org/10.3991/ijim.v12i1.7632.
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The existence of mobile devices as a location pointing device using Global Positioning System (GPS) is a very common thing nowadays. The use of GPS as a tool to determine the location of course has a shortage when used indoors. Therefore, the used of indoor location-based services in a room that leverages the use of Access Point (AP) is very important. By using the information of the Received Signal Strength (RSS) obtained from AP, then the location of the device can be determined without the need to use GPS. This technique is called the location fingerprint technique using the characteristics of received RSS’s fingerprint, then use it to determine the position. To get a more accurate position then authors used the K-Nearest Neighbor (KNN) method. KNN will use some of the data that obtained from some AP to assist in positioning the device. This solution of course would be able to determine the position of the devices in a storied building.
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Zou, Deyue, Shutong Niu, Shuhao Chen, Binhong Su, Xinyi Cheng, Jie Liu, Yunfeng Liu, and Yang Li. "A smart city used low-latency seamless positioning system based on inverse global navigation satellite system technology." International Journal of Distributed Sensor Networks 15, no. 9 (September 2019): 155014771987381. http://dx.doi.org/10.1177/1550147719873815.
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People have to move between indoor and outdoor frequently in city scenarios. The global navigation satellite system signal cannot provide reliable indoor positioning services. To solve the problem, this article proposes a seamless positioning system based on an inverse global navigation satellite system signal, which can extend the global navigation satellite system service into the indoor scenario. In this method, a signal source is arranged at a key position in the room, and the inverse global navigation satellite system signal is transmitted to the global navigation satellite system receiver to obtain a preset positioning result. The indoor positioning service is continued with the inertial navigation system after leaving the key position. The inverse global navigation satellite system seamless positioning system proposed in this article can unify indoor and outdoor positioning using the same receiver. The receiver does not need to re-receive navigation information when the scene changes, which avoids the switching process. Through the design of signal layer coverage, the receiver is in a warm start state, and the users can quickly fix the position when the scenario changes, realizing quick access in a true sense. This enables the ordinary commercial global navigation satellite system receiver to obtain indoor positioning capability without modification, and the algorithm can perform accurate positioning indoors and outdoors without switching.
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Jiang, Wei, Yong Li, Chris Rizos, Baigen Cai, and Wei Shangguan. "Seamless Indoor-Outdoor Navigation based on GNSS, INS and Terrestrial Ranging Techniques." Journal of Navigation 70, no. 6 (July 11, 2017): 1183–204. http://dx.doi.org/10.1017/s037346331700042x.
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We describe an integrated navigation system based on Global Navigation Satellite Systems (GNSS), an Inertial Navigation System (INS) and terrestrial ranging technologies that can support accurate and seamless indoor-outdoor positioning. To overcome severe multipath disturbance in indoor environments, Locata technology is used in this navigation system. Such a “Locata-augmented” navigation system can operate in different positioning modes in both indoor and outdoor environments. In environments where GNSS is unavailable, e.g. indoors, the proposed system is designed to operate in the Locata/INS “loosely-integrated” mode. On the other hand, in outdoor environments, all GNSS, Locata and INS measurements are available, and all useful information can be fused via a decentralised Federated Kalman filter. To evaluate the proposed system for seamless indoor-outdoor positioning, an indoor-outdoor test was conducted at a metal-clad warehouse. The test results confirmed that the proposed navigation system can provide continuous and reliable position and attitude solutions, with the positioning accuracy being better than five centimetres.
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Mautz, Rainer. "Indoor Positioning - An Ad-Hoc Positioning System." Geodesy and Cartography 34, no. 2 (June 1, 2008): 66–70. http://dx.doi.org/10.3846/1392-1541.2008.34.66-70.
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Zhu, Ruihui, Yunjia Wang, Hongji Cao, Baoguo Yu, Xingli Gan, Lu Huang, Heng Zhang, Shuang Li, Haonan Jia, and Jianqiang Chen. "RTK/Pseudolite/LAHDE/IMU-PDR Integrated Pedestrian Navigation System for Urban and Indoor Environments." Sensors 20, no. 6 (March 24, 2020): 1791. http://dx.doi.org/10.3390/s20061791.
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This paper presents an evaluation of real-time kinematic (RTK)/Pseudolite/landmarks assistance heuristic drift elimination (LAHDE)/inertial measurement unit-based personal dead reckoning systems (IMU-PDR) integrated pedestrian navigation system for urban and indoor environments. Real-time kinematic (RTK) technique is widely used for high-precision positioning and can provide periodic correction to inertial measurement unit (IMU)-based personal dead reckoning systems (PDR) outdoors. However, indoors, where global positioning system (GPS) signals are not available, RTK fails to achieve high-precision positioning. Pseudolite can provide satellite-like navigation signals for user receivers to achieve positioning in indoor environments. However, there are some problems in pseudolite positioning field, such as complex multipath effect in indoor environments and integer ambiguity of carrier phase. In order to avoid the limitation of these factors, a local search method based on carrier phase difference with the assistance of IMU-PDR is proposed in this paper, which can achieve higher positioning accuracy. Besides, heuristic drift elimination algorithm with the assistance of manmade landmarks (LAHDE) is introduced to eliminate the accumulated error in headings derived by IMU-PDR in indoor corridors. An algorithm verification system was developed to carry out real experiments in a cooperation scene. Results show that, although the proposed pedestrian navigation system has to use human behavior to switch the positioning algorithm according to different scenarios, it is still effective in controlling the IMU-PDR drift error in multiscenarios including outdoor, indoor corridor, and indoor room for different people.
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Mo, John P. T., and Jason J. S. Lee. "RFID-based indoor positioning system." International Journal of Radio Frequency Identification Technology and Applications 3, no. 1/2 (2011): 141. http://dx.doi.org/10.1504/ijrfita.2011.039788.
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Li, Shuo, and Rashid Rashidzadeh. "Hybrid indoor location positioning system." IET Wireless Sensor Systems 9, no. 5 (October 1, 2019): 257–64. http://dx.doi.org/10.1049/iet-wss.2018.5237.
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Wang, Changqiang, Aigong Xu, Xin Sui, Yushi Hao, Zhengxu Shi, and Zhijian Chen. "A Seamless Navigation System and Applications for Autonomous Vehicles Using a Tightly Coupled GNSS/UWB/INS/Map Integration Scheme." Remote Sensing 14, no. 1 (December 22, 2021): 27. http://dx.doi.org/10.3390/rs14010027.
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Seamless positioning systems for complex environments have been a popular focus of research on positioning safety for autonomous vehicles (AVs). In particular, the seamless high-precision positioning of AVs indoors and outdoors still poses considerable challenges and requires continuous, reliable, and high-precision positioning information to guarantee the safety of driving. To obtain effective positioning information, multiconstellation global navigation satellite system (multi-GNSS) real-time kinematics (RTK) and an inertial navigation system (INS) have been widely integrated into AVs. However, integrated multi-GNSS and INS applications cannot provide effective and seamless positioning results for AVs in indoor and outdoor environments due to limited satellite availability, multipath effects, frequent signal blockages, and the lack of GNSS signals indoors. In this contribution, multi-GNSS-tightly coupled (TC) RTK/INS technology is developed to solve the positioning problem for a challenging urban outdoor environment. In addition, ultrawideband (UWB)/INS technology is developed to provide accurate and continuous positioning results in indoor environments, and INS and map information are used to identify and eliminate UWB non-line-of-sight (NLOS) errors. Finally, an improved adaptive robust extended Kalman filter (AREKF) algorithm based on a TC integrated single-frequency multi-GNSS-TC RTK/UWB/INS/map system is studied to provide continuous, reliable, high-precision positioning information to AVs in indoor and outdoor environments. Experimental results show that the proposed scheme is capable of seamlessly guaranteeing the positioning accuracy of AVs in complex indoor and outdoor environments involving many measurement outliers and environmental interference effects.
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Feng, Pan, Danyang Qin, Min Zhao, Ruolin Guo, and Teklu Berhane. "Unsupervised Indoor Positioning System Based on Environmental Signatures." Entropy 21, no. 3 (March 26, 2019): 327. http://dx.doi.org/10.3390/e21030327.
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Mobile sensors are widely used in indoor positioning in recent years, but most methods require cumbersome calibration for precise positioning results, thus the paper proposes a new unsupervised indoor positioning (UIP) without cumbersome calibration. UIP takes advantage of environment features in indoor environments, as some indoor locations have their signatures. UIP considers these signatures as the landmarks, and combines dead reckoning with them in a simultaneous localization and mapping (SLAM) frame to reduce positioning errors and convergence time. The test results prove that the system can achieve accurate indoor positioning, which highlights its prospect as an unconventional method of indoor positioning.
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Atia, M. M., M. J. Korenberg, and A. Noureldin. "Particle-Filter-Based WiFi-Aided Reduced Inertial Sensors Navigation System for Indoor and GPS-Denied Environments." International Journal of Navigation and Observation 2012 (June 25, 2012): 1–12. http://dx.doi.org/10.1155/2012/753206.
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Indoor navigation is challenging due to unavailability of satellites-based signals indoors. Inertial Navigation Systems (INSs) may be used as standalone navigation indoors. However, INS suffers from growing drifts without bounds due to error accumulation. On the other side, the IEEE 802.11 WLAN (WiFi) is widely adopted which prompted many researchers to use it to provide positioning indoors using fingerprinting. However, due to WiFi signal noise and multipath errors indoors, WiFi positioning is scattered and noisy. To benefit from both WiFi and inertial systems, in this paper, two major techniques are applied. First, a low-cost Reduced Inertial Sensors System (RISS) is integrated with WiFi to smooth the noisy scattered WiFi positioning and reduce RISS drifts. Second, a fast feature reduction technique is applied to fingerprinting to identify the WiFi access points with highest discrepancy power to be used for positioning. The RISS/WiFi system is implemented using a fast version of Mixture Particle Filter for state estimation as nonlinear non-Gaussian filtering algorithm. Real experiments showed that drifts of RISS are greatly reduced and the scattered noisy WiFi positioning is significantly smoothed. The proposed system provides smooth indoor positioning of 1 m accuracy 70% of the time outperforming each system individually.
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Ozsoy, Kerem, Ayhan Bozkurt, and Ibrahim Tekin. "Indoor positioning based on global positioning system signals." Microwave and Optical Technology Letters 55, no. 5 (March 23, 2013): 1091–97. http://dx.doi.org/10.1002/mop.27520.
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Lou, Ping, Qi Zhao, Xiaomei Zhang, Da Li, and Jiwei Hu. "Indoor Positioning System with UWB Based on a Digital Twin." Sensors 22, no. 16 (August 9, 2022): 5936. http://dx.doi.org/10.3390/s22165936.
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Ultra-wideband (UWB) technology is used for indoor positioning, but its positioning accuracy is usually degenerated by various obstacles in the indoor environment because of non-line-of-sight (NLOS). Facing the complex and changeable indoor environment, an indoor positioning system with UWB based on a digital twin is presented in this paper. The indoor positioning accuracy is improved with a perception–prediction feedback of cyber-physics space in this indoor positioning system. In addition, an anchor layout method with virtuality–reality interaction and an error mitigation method based on neural networks is put forward in this system. Finally, a case study is presented to validate this indoor positioning system with a significant improvement in positioning accuracy.
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Jumaah, Al-Nussairi Ahmed Kateb. "Enhanced Least Square Method for Indoor Positioning System Using UWB Technology." Webology 19, no. 1 (January 20, 2022): 3815–34. http://dx.doi.org/10.14704/web/v19i1/web19251.
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One of the main radio technologies that could be used for indoor localization is Ultra-wideband, (UWB). It is a short-range RF technology for wireless communication that can be leveraged to detect the location of people, devices, and assets with significant precision. But, it has a major limitation which is the need for a non-line-of-sight (NLOS) identification and mitigation approach to precise location a target in a hard indoor environment. The NLOS approach will complicate the positioning approach. The goals of this work are; i- for saving cost and time of installation of anchor nodes, the minimum required number of anchor nodes have been installed, ii- the accuracy of the created system should be compatible with most various indoor environments. In this work, we create a novel algorithm of Indoor positioning system named Enhanced Linearized Least Square (ELLS) using UWB technology without using an NLOS identification approach. We evaluate and validate the created system by implementing real experiments. The created system has an average positioning accuracy reaching about 0.45 𝑚2of mean square error in a hard environment. It outperforms most indoor positioning systems in the market with less complexity, cost, and more accuracy.
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Wu, Pengtao. "Comparison between the Ultra-wide Band based indoor positioning technology and other technologies." Journal of Physics: Conference Series 2187, no. 1 (February 1, 2022): 012010. http://dx.doi.org/10.1088/1742-6596/2187/1/012010.
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Abstract In recent decades, there have been many applications of positioning and navigation systems, the most representative of which is GPS (Global Positioning System). This technique is very accurate for outdoor navigation, but it cannot provide reliable positioning data indoors. This paper firstly compares the different indoor positioning technologies and analyses their bottleneck. Then the suitable algorithm of UWB based on indoor positioning technology (IPT) is discussed including Angle of arrival (AoA), Time of arrival (ToA), Time difference of arrival (TDoA), and Received Signal Strength (RSS). Eventually, the paper finds that although UWB-based indoor positioning technology still has many problems such as high deployment equipment costs to be solved, it is suitable for widespread applications due to its special advantages such as strong resistance to multipath effects.
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Li, Ningbo, Lianwu Guan, Yanbin Gao, Shitong Du, Menghao Wu, Xingxing Guang, and Xiaodan Cong. "Indoor and Outdoor Low-Cost Seamless Integrated Navigation System Based on the Integration of INS/GNSS/LIDAR System." Remote Sensing 12, no. 19 (October 8, 2020): 3271. http://dx.doi.org/10.3390/rs12193271.
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Global Navigation Satellite System (GNSS) provides accurate positioning data for vehicular navigation in open outdoor environment. In an indoor environment, Light Detection and Ranging (LIDAR) Simultaneous Localization and Mapping (SLAM) establishes a two-dimensional map and provides positioning data. However, LIDAR can only provide relative positioning data and it cannot directly provide the latitude and longitude of the current position. As a consequence, GNSS/Inertial Navigation System (INS) integrated navigation could be employed in outdoors, while the indoors part makes use of INS/LIDAR integrated navigation and the corresponding switching navigation will make the indoor and outdoor positioning consistent. In addition, when the vehicle enters the garage, the GNSS signal will be blurred for a while and then disappeared. Ambiguous GNSS satellite signals will lead to the continuous distortion or overall drift of the positioning trajectory in the indoor condition. Therefore, an INS/LIDAR seamless integrated navigation algorithm and a switching algorithm based on vehicle navigation system are designed. According to the experimental data, the positioning accuracy of the INS/LIDAR navigation algorithm in the simulated environmental experiment is 50% higher than that of the Dead Reckoning (DR) algorithm. Besides, the switching algorithm developed based on the INS/LIDAR integrated navigation algorithm can achieve 80% success rate in navigation mode switching.
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Kim Geok, Tan, Khaing Zar Aung, Moe Sandar Aung, Min Thu Soe, Azlan Abdaziz, Chia Pao Liew, Ferdous Hossain, Chih P. Tso, and Wong Hin Yong. "Review of Indoor Positioning: Radio Wave Technology." Applied Sciences 11, no. 1 (December 30, 2020): 279. http://dx.doi.org/10.3390/app11010279.
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The indoor positioning system (IPS) is becoming increasing important in accurately determining the locations of objects by the utilization of micro-electro-mechanical-systems (MEMS) involving smartphone sensors, embedded sources, mapping localizations, and wireless communication networks. Generally, a global positioning system (GPS) may not be effective in servicing the reality of a complex indoor environment, due to the limitations of the line-of-sight (LoS) path from the satellite. Different techniques have been used in indoor localization services (ILSs) in order to solve particular issues, such as multipath environments, the energy inefficiency of long-term battery usage, intensive labour and the resources of offline information collection and the estimation of accumulated positioning errors. Moreover, advanced algorithms, machine learning, and valuable algorithms have given rise to effective ways in determining indoor locations. This paper presents a comprehensive review on the positioning algorithms for indoors, based on advances reported in radio wave, infrared, visible light, sound, and magnetic field technologies. The traditional ranging parameters in addition to advanced parameters such as channel state information (CSI), reference signal received power (RSRP), and reference signal received quality (RSRQ) are also presented for distance estimation in localization systems. In summary, the recent advanced algorithms can offer precise positioning behaviour for an unknown environment in indoor locations.
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Luo, Heng, Xiaobo Niu, Junchen Li, Jianping Chen, Youmin Zou, and Yunmeng Shen. "Research on an Adaptive Algorithm for Indoor Bluetooth Positioning." International Journal of Pattern Recognition and Artificial Intelligence 32, no. 06 (February 21, 2018): 1854014. http://dx.doi.org/10.1142/s0218001418540149.
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Building structure and other factors lead to the performance deterioration of global postioning system (GPS) positioning systems indoors. An adaptive model for Bluetooth-based indoor positioning is proposed in this paper, targeting at the complex indoor environment, to improve the performance of Bluetooth-oriented indoor positioning systems. More accurate Received Signal Strength Indicator (RSSI) calibration which is optimized via Gaussian filtering, together with the environment-dependent attenuation coefficient optimization, results in a more precise hybrid model in the complicated indoor environment. Experiment results show that the difference between the estimated results and the measured samples is less than 0.25[Formula: see text]m as the target node and reference node is less than 1.5[Formula: see text]m far from each other. As the distance increases to more than 1.5[Formula: see text]m, the relative difference between the estimated values and the measured ones decreases to 7.8% at most, satisfying the requirements for indoor positioning applications.
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Xi, Liang, Ming Yan Jiang, and Chuan Zhu Liao. "Indoor Positioning System Based on RFID." Applied Mechanics and Materials 543-547 (March 2014): 2627–31. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.2627.
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This paper presents an indoor positioning system based on RFID, which introduces electronic tag assisted positioning, according to the plurality of the electronic tags which are arranged in the target area as equilateral triangle, and the reader reads the information and Received Signal Strength Indication (RSSI) within its reading range. Sampling and calculation of the positioning result is controlled by the core circuit. Experimental results show that the indoor positioning system has excellent positioning accuracy, with high efficiency and low cost.
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Ruan, Ling, Ling Zhang, Yi Long, and Fei Cheng. "Coordinate references for the indoor/outdoor seamless positioning." Proceedings of the ICA 1 (May 16, 2018): 1–7. http://dx.doi.org/10.5194/ica-proc-1-97-2018.
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Indoor positioning technologies are being developed rapidly, and seamless positioning which connected indoor and outdoor space is a new trend. The indoor and outdoor positioning are not applying the same coordinate system and different indoor positioning scenes uses different indoor local coordinate reference systems. A specific and unified coordinate reference frame is needed as the space basis and premise in seamless positioning application. Trajectory analysis of indoor and outdoor integration also requires a uniform coordinate reference. However, the coordinate reference frame in seamless positioning which can applied to various complex scenarios is lacking of research for a long time. In this paper, we proposed a universal coordinate reference frame in indoor/outdoor seamless positioning. The research focus on analysis and classify the indoor positioning scenes and put forward the coordinate reference system establishment and coordinate transformation methods in each scene. And, through some experiments, the calibration method feasibility was verified.
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CIL, IBRAHIM, FAHRI ARISOY, AHMET YUNUS CIL, and Hilal Kilinc. "A COMPARATIVE ANALYSIS OF INDOOR POSITIONING TECHNOLOGIES IN SHIPYARD DIGITALIZATION CONTEXT." Journal of Marine Technology and Environment 2022, no. 1 (April 1, 2022): 15–25. http://dx.doi.org/10.53464/jmte.01.2022.03.
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Purpose: In the last few decades, there has been an increasing growth in research into the use of positioning technologies in open environments. Most of the technologies developed for outdoor environments are used successfully, however, they cannot be considered as fully successful indoors. In this context, various technologies based on Radio Frequency, Infrared, Ultrasound, Magnetic, Optical, and computer vision are proposed to improve positioning indoors. In addition to their individual use, it is also seen in hybrid applications. In particular, Radio Frequency based technologies have potential use in shipyard environments. For this purpose, technologies such as Bluetooth, Ultra broadband, Wireless Sensor Network, Wireless Local Area Network, Radio Frequency Recognition and Near Field Communication are seen as suitable technology options for shipyards. The indoor positioning system is a technology that has the potential to significantly improve work efficiency and safety in the shipyard area. It is difficult to achieve a successful digital transformation of the complex shipyard environment without identifying an Indoor positioning technology for the shipyard. In this study, it is aimed to design a positioning technology that will be most appropriate for the shipyard. Methodology: This paper analyses the challenges for the selection of Indoor positioning system for shipyards in evaluating Indoor-positioning technologies. The methodology followed in this study is a comprehensive comparative analysis of existing IPS technologies on how to digitize shipyards. This article provides an advanced assessment of indoor positioning technologies and their use in the challenging shipyard site. In this context, it provides an evaluation framework for different positioning measures such as accuracy, coverage, scalability, cost, privacy and usability of technologies that can be used within the scope of IPS. Results: The work carried out here on indoor positioning systems and components makes a significant contribution to the shipyard industry. Because it has a great impact on the suitability of technologies, especially in relation to the shipyard environment. Both the evaluation model and solution method, and the Bluetooth-based positioning technology, which stands out at the end of the evaluation, are important contributions of the study. Conclusion: To determine which indoor positioning systems are more suitable for the shipyard environment, both a detailed analysis of the shipyard environment and an evaluation were made to select the most suitable technology. The comparison was made based on observations of the shipyard site and the available literature on the field. This article makes important contributions to future shipyards' application of positioning technologies.
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Gang, Hui-Seon, and Jae-Young Pyun. "A Smartphone Indoor Positioning System Using Hybrid Localization Technology." Energies 12, no. 19 (September 27, 2019): 3702. http://dx.doi.org/10.3390/en12193702.
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As smartphone built-in sensors, wireless technologies, and processor computing power become more advanced and global positioning system (GPS)-based positioning technologies are improving, location-based services (LBS) have become a part of our daily lives. At the same time, demand has grown for LBS applications in indoor environments, such as indoor path finding and navigation, marketing, entertainment, and location-based information retrieval. In this paper, we demonstrate the design and implementation of a smartphone-based indoor LBS system for location services consisting of smartphone applications and a server. The proposed indoor LBS system uses hybrid indoor positioning methods based on Bluetooth beacons, Geomagnetic field, Inertial Measurement Unit (IMU) sensors, and smartphone cameras and can be used for three types of indoor LBS applications. The performance of each positioning method demonstrates that our system retains the desired accuracy under experimental conditions. As these results illustrate that our system can maintain positioning accuracy to within 2 m 80% of the time, we believe our system can be a real solution for various indoor positioning service needs.
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William, David. "Cloud-Based Indoor Positioning Service for Indoor Navigation System." International Journal of Advanced Trends in Computer Science and Engineering 9, no. 2 (April 25, 2020): 1774–81. http://dx.doi.org/10.30534/ijatcse/2020/133922020.
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Morohin, D. V. "Indoor ultrasonic positioning system transceiver modules." IOP Conference Series: Materials Science and Engineering 862 (May 28, 2020): 052036. http://dx.doi.org/10.1088/1757-899x/862/5/052036.
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De Angelis, Guido, Valter Pasku, Alessio De Angelis, Marco Dionigi, Mauro Mongiardo, Antonio Moschitta, and Paolo Carbone. "An Indoor AC Magnetic Positioning System." IEEE Transactions on Instrumentation and Measurement 64, no. 5 (May 2015): 1267–75. http://dx.doi.org/10.1109/tim.2014.2381353.
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Tian, Ye, Lejie Zhou, and Xu Ji. "Analysis of Integrated Navigation Technology Based on GNSS/UWB." Journal of Physics: Conference Series 2410, no. 1 (December 1, 2022): 012016. http://dx.doi.org/10.1088/1742-6596/2410/1/012016.
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Abstract Aiming at the problem that a single positioning system cannot meet the indoor and outdoor high-precision positioning, GNSS/UWB integrated navigation system is proposed. Firstly, this paper introduces the development and research status of the global satellite navigation system; Secondly, The UWB positioning technology in indoor positioning technology is introduced; Finally, the development and research status of GNSS/UWB integrated navigation are introduced. The advantages and disadvantages of the single outdoor or indoor positioning system in the indoor and outdoor integrated navigation system are compared and analyzed. The results show that a single outdoor or indoor positioning system cannot meet the indoor and outdoor high-precision positioning, an effective method of GNSS/UWB fusion positioning is to improve the positioning accuracy and robustness, which can enhance the real-time in time, continuity in space and reliability in accuracy.
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Zhang, Xiaona, Shufang Zhang, Chao Wang, and Shujing Sun. "Regional Double-Layer, High-Precision Indoor Positioning System Based on iBeacon Network." Mathematical Problems in Engineering 2022 (March 27, 2022): 1–12. http://dx.doi.org/10.1155/2022/8673083.
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With the development of modern society, the demand for indoor positioning technology is higher and higher. The existing indoor positioning technology is difficult to really solve the problem of accuracy and achieve high-performance indoor positioning system design. Based on iBeacon equipment, this paper proposes a method to optimize received signal strength indication indoor positioning algorithm by using the Gaussian filtering method so as to reduce the adverse impact of multipath fading in indoor environment. In order to further improve the accuracy of indoor positioning algorithm, the stack automatic encoder in the deep neural network algorithm is introduced. Through the deep learning method, the high-dimensional information of the fingerprint database collected by the system can be extracted and the adverse impact of data noise on the database is also reduced. Through the simulation test of the system, it can be seen that the error of received signal strength indication indoor positioning algorithm based on extended Gaussian filter is small. Compared with the traditional iBeacon algorithm, the improved algorithm can achieve better data classification. The maximum error of the whole system is 1.02 M. Comprehensive analysis shows that the proposed indoor positioning system has a certain practical value and can be applied to the indoor positioning needs in a certain range of environment.
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Keluža, Marin, Kristina Beg, and Bernard Vukelić. "Analysis of an indoor positioning systems." Zbornik Veleučilišta u Rijeci 5, no. 1 (2017): 13–32. http://dx.doi.org/10.31784/zvr.5.1.2.
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Recently, due to advances in the development of various technologies which can be used for locating, it is possible to develop systems which include software solutions for the user locationing and guidance in the interior, closed or covered areas where the existing location technologies and systems for locating and guidance applicable at open, outdoor areas cannot be used. This paper analyses the available hardware, software and network technologies which can be used for creating a positioning system for interior, closed or covered area. The paper analyses technologies which can be used in such distributed systems for the implementation of functionalities that are needed or required in the Indoor Positioning System (IPS). The paper describes the concept of the IPS system. It presents the IPS systems available on the market. It shows the technologies that can be used to implement the IPS system and the analyses of categories which affect the IPS system implementation. The paper demonstrates that none of the technologies analysed meet all of the observed categories while the BLE technology achieves the most favourable results in individual categories.
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Adeyeye Oshin, Michael, and Nobaene Sehloho. "An Indoor Positioning System Using Multiple Methods and Tools." International Journal of Information, Communication Technology and Applications 4, no. 1 (May 1, 2018): 11–22. http://dx.doi.org/10.17972/ijicta20184134.
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With many different studies showing a growing demand for the development of indoor positioning systems, numerous positioning and tracking methods and tools are available for which can be used for mobile devices. Therefore, an interest is more on development of indoor positioning and tracking systems that are accurate and effective. Presented and proposed in this work, is an indoor positioning system. As opposed to an Ad-hoc Positioning System (APS), it uses a Wireless Mesh Network (WMN). The system makes use of an already existing Wi-Fi infrastructure technology. Moreover, the approach tests the positioning of a node with its neighbours in a mesh network using multi-hopping functionality. The positioning measurements used were the ICMP echos, RSSI and RTS/CTS requests and responses. The positioning method used was the trilateral technique, in combination with the idea of the fingerprinting method. Through research and experimentation, this study developed a system which shows potential as a positioning system with an error of about 2 m to 3 m. The hybridisation of the method proves an enhancement in the system though improvements are still required.
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Lukito, Yuan. "Multi Layer Perceptron Model for Indoor Positioning System Based on Wi-Fi." Jurnal Teknologi dan Sistem Komputer 5, no. 3 (July 31, 2017): 123–28. http://dx.doi.org/10.14710/jtsiskom.5.3.2017.123-128.
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Indoor positioning system issue is an open problem that still needs some improvements. This research explores the utilization of multilayer perceptron in determining someone’s position inside a building or a room, which generally known as Indoor Positioning System. The research was conducted in some steps: dataset normalization, multilayer perceptron implementation, training process of multilayer perceptron, evaluation, and analysis. The training process has been conducted many times to find the best parameters that produce the best accuracy rate. The experiment produces 79,16% as the highest accuracy rate. Compared to previous research, this result is comparably lower and needs some parameters tweaking or changing the neural networks architectures.
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Md Din, Marina, Norziana Jamil, Jacentha Maniam, and Mohamad Afendee Mohamed. "Indoor positioning: technology comparison analysis." International Journal of Engineering & Technology 7, no. 2.14 (April 6, 2018): 133. http://dx.doi.org/10.14419/ijet.v7i2.14.12813.
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A system that allows users to find and track a specific position is known as positioning system. Global Positioning System (GPS) is one of top known position tracking system that commonly used to find position and location of object outdoor. Tracking an object indoor using GPS is not highly recommended because the signals transmitted through a satellite to a device indoor gets blocked and resulted in weak signals. Thus, an indoor positioning system (IPS) that tracks and positions object indoor has been implemented to overcome the issues of signals multipath that resulted from GPS. The aim of this paper is to provide up to date indoor positioning technologies and compares the technologies according to its technical perspectives.
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Torres, Juan, Aitor Montes, Sandra Mendoza, Pedro Fernández, Juan Betancourt, Lorena Escandell, Carlos del Valle, and José Sánchez-Pena. "A Low-Cost Visible Light Positioning System for Indoor Positioning." Sensors 20, no. 18 (September 9, 2020): 5145. http://dx.doi.org/10.3390/s20185145.
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Currently, a high percentage of the world’s population lives in urban areas, and this proportion will increase in the coming decades. In this context, indoor positioning systems (IPSs) have been a topic of great interest for researchers. On the other hand, Visible Light Communication (VLC) systems have advantages over RF technologies; for instance, they do not need satellite signals or the absence of electromagnetic interference to achieve positioning. Nowadays, in the context of Indoor Positioning (IPS), Visible Light Positioning (VLP) systems have become a strong alternative to RF-based systems, allowing the reduction in costs and time to market. This paper shows a low cost VLP solution for indoor systems. This includes multiple programmable beacons and a receiver which can be plugged to a smartphone running a specific app. The position information will be quickly and securely available through the interchange between the receiver and any configurable LED-beacon which is strategically disposed in an area. The implementation is simple, inexpensive, and no direct communication with any data server is required.
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Li, Jian, Guangjie Han, Chunsheng Zhu, and Guiqing Sun. "An Indoor Ultrasonic Positioning System Based on TOA for Internet of Things." Mobile Information Systems 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/4502867.
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With the development of Internet of Things, the position information of indoor objects becomes more important for most application scenarios. This paper presents an ultrasonic indoor positioning system, which can achieve centimeter-level precise positioning of objects moving indoors. Transmitting nodes, receiving nodes, and display control terminal are needed to constitute the entire system. The system is based on long-baseline positioning technology that uses code division multiplexing access mechanism. There is no limit to the number of receiving nodes as the system works in the up-transmit-down-receive mode. Positioning of a receiving node is found based on ultrasonic Time of Arrival ranging technology. To accurately determine the positioning, there must be at least four or five transmitting nodes. The working radius will not be less than 5 meters when the height is larger than 3 meters. The system uses wideband pseudorandom noise signal called Gold sequences for multiuser identification and slant range measurement. The paper first gives a brief introduction of popular indoor ultrasonic positioning methods and then describes the theory of proposed algorithm and provides the simulation results. To examine the correctness of the approach and its practicality, the practical implementation and experimental results are provided also in the paper.
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Qin, Feng, Tao Zuo, and Xing Wang. "CCpos: WiFi Fingerprint Indoor Positioning System Based on CDAE-CNN." Sensors 21, no. 4 (February 5, 2021): 1114. http://dx.doi.org/10.3390/s21041114.
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WiFi is widely used for indoor positioning because of its advantages such as long transmission distance and ease of use indoors. To improve the accuracy and robustness of indoor WiFi fingerprint localization technology, this paper proposes a positioning system CCPos (CADE-CNN Positioning), which is based on a convolutional denoising autoencoder (CDAE) and a convolutional neural network (CNN). In the offline stage, this system applies the K-means algorithm to extract the validation set from the all-training set. In the online stage, the RSSI is first denoised and key features are extracted by the CDAE. Then the location estimation is output by the CNN. In this paper, the Alcala Tutorial 2017 dataset and UJIIndoorLoc are adopted to verify the performance of the CCpos system. The experimental results show that our system has excellent noise immunity and generalization performance. The mean positioning errors on the Alcala Tutorial 2017 dataset and the UJIIndoorLoc are 1.05 m and 12.4 m, respectively.
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Bozkurt Keser, Sinem, Ahmet Yazici, and Serkan Gunal. "An F-Score-Weighted Indoor Positioning Algorithm Integrating WiFi and Magnetic Field Fingerprints." Mobile Information Systems 2018 (2018): 1–8. http://dx.doi.org/10.1155/2018/7950985.
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Indoor positioning systems have attracted much attention with the recent development of location-based services. Although global positioning system (GPS) is a widely accepted and accurate outdoor localization system, there is no such a solution for indoor areas. Therefore, various systems are proposed for the indoor positioning problem. Fingerprint-based positioning is one of the widely used methods in this area. WiFi-received signal strength (RSS) is a frequently used signal type for the fingerprint-based positioning system. Since WiFi signal distribution is nonstationary, accuracy is insufficient. Therefore, the performance of indoor positioning systems can be enhanced using multiple signal types. However, the positioning performance of each signal type varies depending on the characteristics of the environment. Considering the variability of the performances of different signal types, an F-score-weighted indoor positioning algorithm, which integrates WiFi-RSS and MF fingerprints, is proposed in this study. In the proposed approach, the positioning is first performed by maximum likelihood estimation for both WiFi-RSS and magnetic field signal values to calculate the F-score of each signal type. Then, each signal type is combined using F-score values as a weight to estimate a position. The experiments are performed using a publicly available dataset that contains real-world data. Experimental results reveal that the proposed algorithm is efficient in achieving accurate indoor positioning and consolidates the system performance compared to using a single type of signal.
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Weiqing, Huang, Ding Chang, and Wang Siye. "A comprehensive method to combine RFID indoor targets positioning with real geographic environment." Computer Science and Information Systems 12, no. 4 (2015): 1149–69. http://dx.doi.org/10.2298/csis141114048w.
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Nowadays RFID indoor targets positioning results display methods are simplified. The positioning results visual effect is also unsatisfied. To solve this problem, we design and realize a comprehensive method to implement RFID indoor localization algorithms in a geographic information system. In our method, the RFID indoor targets positioning results can display in the real geographic environment, which can improve the application value of the results. First, we establish the geographic environment using geographic information system in order to combine RFID indoor positioning results with the real environment. Then we design a distributed system architecture to filter the useless data and implement the positioning algorithm. In this way, indoor targets real-time positioning and the results visualization display are realized. And the positioning results can also be combined with the real geographic information environment. System test results indicate that this method achieves ideal indoor positioning data display effect under well indoor-positioning precision.
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Hwangbo, Hyunwoo, Jonghyuk Kim, Zoonky Lee, and Soyean Kim. "Store layout optimization using indoor positioning system." International Journal of Distributed Sensor Networks 13, no. 2 (February 2017): 155014771769258. http://dx.doi.org/10.1177/1550147717692585.
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Indoor positioning systems have attracted considerable attention from practitioners and firms seeking to optimize the consumer shopping experience with the goal of attaining increased revenue and profitability. Acknowledging the importance of indoor positioning systems in store layout optimization, we conducted a field experiment for 11 months in order to develop algorithms for connecting indoor positioning data with customer transaction data. Using fingerprinting as a primary data collection technique, we compared positioning and transaction data before and after critical store layout optimization decisions in order to identify which customer movement patterns generated the highest sales. In contrast to previous works on indoor positioning systems, which focused solely on developing algorithms or techniques to increase accuracy rates, our algorithms in principle integrate computing and marketing perspectives. Our findings can be applied to store layout optimization and personalized marketing.
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Zhang, Wei, Xianghong Hua, Kegen Yu, Weining Qiu, Shoujian Zhang, and Xiaoxing He. "A novel WiFi indoor positioning strategy based on weighted squared Euclidean distance and local principal gradient direction." Sensor Review 39, no. 1 (January 21, 2019): 99–106. http://dx.doi.org/10.1108/sr-06-2017-0109.
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Purpose This paper aims to introduce the weighted squared Euclidean distance between points in signal space, to improve the performance of the Wi-Fi indoor positioning. Nowadays, the received signal strength-based Wi-Fi indoor positioning, a low-cost indoor positioning approach, has attracted a significant attention from both academia and industry. Design/methodology/approach The local principal gradient direction is introduced and used to define the weighting function and an average algorithm based on k-means algorithm is used to estimate the local principal gradient direction of each access point. Then, correlation distance is used in the new method to find the k nearest calibration points. The weighted squared Euclidean distance between the nearest calibration point and target point is calculated and used to estimate the position of target point. Findings Experiments are conducted and the results indicate that the proposed Wi-Fi indoor positioning approach considerably outperforms the weighted k nearest neighbor method. The new method also outperforms support vector regression and extreme learning machine algorithms in the absence of sufficient fingerprints. Research limitations/implications Weighted k nearest neighbor approach, support vector regression algorithm and extreme learning machine algorithm are the three classic strategies for location determination using Wi-Fi fingerprinting. However, weighted k nearest neighbor suffers from dramatic performance degradation in the presence of multipath signal attenuation and environmental changes. More fingerprints are required for support vector regression algorithm to ensure the desirable performance; and labeling Wi-Fi fingerprints is labor-intensive. The performance of extreme learning machine algorithm may not be stable. Practical implications The new weighted squared Euclidean distance-based Wi-Fi indoor positioning strategy can improve the performance of Wi-Fi indoor positioning system. Social implications The received signal strength-based effective Wi-Fi indoor positioning system can substitute for global positioning system that does not work indoors. This effective and low-cost positioning approach would be promising for many indoor-based location services. Originality/value A novel Wi-Fi indoor positioning strategy based on the weighted squared Euclidean distance is proposed in this paper to improve the performance of the Wi-Fi indoor positioning, and the local principal gradient direction is introduced and used to define the weighting function.
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Wang, Haixia, Junliang Li, Wei Cui, Xiao Lu, Zhiguo Zhang, Chunyang Sheng, and Qingde Liu. "Mobile Robot Indoor Positioning System Based on K-ELM." Journal of Sensors 2019 (February 14, 2019): 1–11. http://dx.doi.org/10.1155/2019/7547648.
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Mobile Robot Indoor Positioning System has wide application in the industry and home automation field. Unfortunately, existing mobile robot indoor positioning methods often suffer from poor positioning accuracy, system instability, and need for extra installation efforts. In this paper, we propose a novel positioning system which applies the centralized positioning method into the mobile robot, in which real-time positioning is achieved via interactions between ARM and computer. We apply the Kernel extreme learning machine (K-ELM) algorithm as our positioning algorithm after comparing four different algorithms in simulation experiments. Real-world indoor localization experiments are conducted, and the results demonstrate that the proposed system can not only improve positioning accuracy but also greatly reduce the installation efforts since our system solely relies on Wi-Fi devices.
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Poulose, Alwin, and Dong Seog Han. "Hybrid Deep Learning Model Based Indoor Positioning Using Wi-Fi RSSI Heat Maps for Autonomous Applications." Electronics 10, no. 1 (December 22, 2020): 2. http://dx.doi.org/10.3390/electronics10010002.
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Positioning using Wi-Fi received signal strength indication (RSSI) signals is an effective method for identifying the user positions in an indoor scenario. Wi-Fi RSSI signals in an autonomous system can be easily used for vehicle tracking in underground parking. In Wi-Fi RSSI signal based positioning, the positioning system estimates the signal strength of the access points (APs) to the receiver and identifies the user’s indoor positions. The existing Wi-Fi RSSI based positioning systems use raw RSSI signals obtained from APs and estimate the user positions. These raw RSSI signals can easily fluctuate and be interfered with by the indoor channel conditions. This signal interference in the indoor channel condition reduces localization performance of these existing Wi-Fi RSSI signal based positioning systems. To enhance their performance and reduce the positioning error, we propose a hybrid deep learning model (HDLM) based indoor positioning system. The proposed HDLM based positioning system uses RSSI heat maps instead of raw RSSI signals from APs. This results in better localization performance for Wi-Fi RSSI signal based positioning systems. When compared to the existing Wi-Fi RSSI based positioning technologies such as fingerprint, trilateration, and Wi-Fi fusion approaches, the proposed approach achieves reasonably better positioning results for indoor localization. The experiment results show that a combination of convolutional neural network and long short-term memory network (CNN-LSTM) used in the proposed HDLM outperforms other deep learning models and gives a smaller localization error than conventional Wi-Fi RSSI signal based localization approaches. From the experiment result analysis, the proposed system can be easily implemented for autonomous applications.
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Gan, Yu, Huang, Jia, Zhang, Sheng, Fan, and Wang. "Doppler Differential Positioning Technology Using the BDS/GPS Indoor Array Pseudolite System." Sensors 19, no. 20 (October 21, 2019): 4580. http://dx.doi.org/10.3390/s19204580.
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A Global Satellite Navigation System (GNSS) cannot provide normal location services in an indoor environment because the signals are blocked by buildings. The Beidou satellite navigation system (BDS)/GPS indoor array pseudolite system is proposed to overcome the problems of indoor positioning with conventional pseudolite, such as time synchronization, ambiguity resolution and base stations. At the same time, an algorithm for Doppler differential positioning is proposed to improve the indoor positioning accuracy and the positioning coverage of the system, which uses the Doppler difference equation and Known Point Initialization (KPI) to determinate the velocity and position of the receiver. Experiments were conducted to verify the proposed system under different conditions; the average positioning error of the Doppler differential positioning algorithm was 7.86 mm in the kinematic test and 2.9 mm in the static test. The results show that BDS/GPS indoor array pseudolite system has the potential to make indoor positioning achieve sub-centimeter precision. Finally, the positioning error of the proposed algorithm is also analyzed, and the data tests show that the dilution of precision (DOP) and cycle- slips have a significant impact on the indoor positioning accuracy; a cycle-slip of a half-wavelength can cause positioning errors of tens of millimeters. Therefore, the Doppler-aided cycle-slip detection method (DACS) is proposed to detect cycle-slips of one cycle or greater than one, and the carrier phase double difference cycle-slip detection method (CPDD) is used to detect cycle slips of a half-wavelength.
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Qiu, Jiandong, Yang Zhang, Minan Tang, Panpan Ma, and Jiajia Ran. "Research on AGV positioning method combined with IMU and UWB." Archives of Transport 64, no. 4 (December 31, 2022): 107–17. http://dx.doi.org/10.5604/01.3001.0016.1229.
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Aiming at the problem that automated guided vehicle (AGV) is difficult to locate accurately due to the influence of environment and time drift when it works in the indoor intelligent storage system. In this paper, an extended kalman filtering (EKF) framework is designed. In order to make full use of the original ranging values of ultra wideband (UWB) and inertial measurement unit (IMU), the framework realizes the fusion positioning between UWB module and IMU module in a tight coupling manner, so as to ensure that the system can still work when the available base station signal is inaccurate. Firstly, for the problem that the traditional UWB positioning method is easily affected by the non-line of sight (NLOS) error indoors, the calculated positioning coordinate value is unstable. With the help of different NLOS probability distribution curves of different obstacles, the weighted least square method is applied to the UWB positioning method to determine the positioning coordinate value of UWB, which improves the sudden change of AGV positioning coordinate in the static environment. Then the data fusion algorithm is optimized, and the error value of IMU and UWB coordinate is taken as the observation value of EKF, which reduces the influence of cumulative error on IMU positioning results, provides the global optimal estimation of the system optimal state, and improves the fusion positioning accuracy. Finally, the measured data of UWB and IMU systems in indoor complex environment are simulated in MATLAB. The experimental results show that when NLOS signal seriously affects the positioning effect, the UWB and IMU combined positioning system can provide more reliable positioning results than the single IMU positioning system. It improves the positioning accuracy of AGV and provides a new idea for indoor positioning mode.
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Duru, A., and I. R. Karas. "IOT ENABLED INDOOR NAVIGATION SYSTEM DESIGN FOR EMERGENCIES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W12 (February 21, 2019): 61–64. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w12-61-2019.
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<p><strong>Abstract.</strong> Global Navigation Satellite System is widely accepted and it has good positioning accuracy for outdoor applications. However, it does not provide sufficient positioning accuracy for inside of buildings. Signals are attenuated inside of buildings or dense high building areas because various materials between satellites and receiver create interference to the signal propagation. Thus, indoor positioning technologies have emerged to cover the problem. In this paper, indoor positioning technologies have been investigated and UWB based indoor positioning technology has been chosen between them. In addition to indoor positioning, accelerometer and Wi-Fi connection has been added to the system for mobility. The accelerometer detects emergency cases and alerts relatives of an intended person by using web service. Hereby, remote navigation system design is presented for first aid of the user. The system can detect emergencies, especially falls using the accelerometer and it can locate patients anywhere in the world. The designed system showed that it is possible to detect emergencies and transfer to the web with a 24.17&thinsp;cm average positioning error. Also, it is an assuring system for future remote positioning applications.</p>
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Li, Zhonghan, and Yongbo Zhang. "Constrained ESKF for UAV Positioning in Indoor Corridor Environment Based on IMU and WiFi." Sensors 22, no. 1 (January 5, 2022): 391. http://dx.doi.org/10.3390/s22010391.
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The indoor autonomous navigation of unmanned aerial vehicles (UAVs) is the current research hotspot. Unlike the outdoor broad environment, the indoor environment is unknown and complicated. Global Navigation Satellite System (GNSS) signals are easily blocked and reflected because of complex indoor spatial features, which make it impossible to achieve positioning and navigation indoors relying on GNSS. This article proposes a set of indoor corridor environment positioning methods based on the integration of WiFi and IMU. The zone partition-based Weighted K Nearest Neighbors (WKNN) algorithm is used to achieve higher WiFi-based positioning accuracy. On the basis of the Error-State Kalman Filter (ESKF) algorithm, WiFi-based and IMU-based methods are fused together and realize higher positioning accuracy. The probability-based optimization method is used for further accuracy improvement. After data fusion, the positioning accuracy increased by 51.09% compared to the IMU-based algorithm and by 66.16% compared to the WiFi-based algorithm. After optimization, the positioning accuracy increased by 20.9% compared to the ESKF-based data fusion algorithm. All of the above results prove that methods based on WiFi and IMU (low-cost sensors) are very capable of obtaining high indoor positioning accuracy.
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Li, Yi. "Research and Implementation of Indoor 3D Positioning Algorithm Based on LED Visible Light Communication and Corresponding Parameter Estimation." Computational Intelligence and Neuroscience 2022 (September 13, 2022): 1–11. http://dx.doi.org/10.1155/2022/2940558.
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In the era of mobile Internet, the application of various positioning-based location service systems is becoming more and more common. In addition, the traditional radio positioning system is limited in the use of special environments such as mines, hospitals, and gas stations, and long-term electromagnetic radiation can cause potential damage to the human body. Compared with the traditional wireless positioning technology, VLC-based positioning technology has a good application prospect in the field of indoor wireless positioning. Compared with traditional radio positioning technology, the use of VLC technology to achieve indoor positioning is different in that the system design and layout need to consider the basic needs of indoor lighting; that is, the layout of multiple visible light sources in the room should meet the minimum illumination requirements of any area of the room. Since the layout structure of the light source that only considers the lighting requirements or only considers the positioning accuracy requirements is not the same, in the design process of the indoor visible light wireless positioning system, it is necessary to consider the overall optimization layout of multiple indoor visible light sources under the conditions of lighting and positioning constraints. This paper mainly optimizes indoor positioning from the aspects of light source layout, reflected light intensity distribution, and noise model.
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Cheng, Chia-Hsin, and Yi Yan. "Indoor positioning system for wireless sensor networks based on two-stage fuzzy inference." International Journal of Distributed Sensor Networks 14, no. 5 (May 2018): 155014771878064. http://dx.doi.org/10.1177/1550147718780649.
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Wireless indoor positioning systems are susceptible to environmental distortion and attenuation of the signal, which can affect positioning accuracy. In this article, we present a two-stage indoor positioning scheme using a fuzzy-based algorithm aimed at minimizing uncertainty in received signal strength indicator measures from reference nodes in wireless sensor networks. In the first stage, the indoor space is divided into several zones and a fuzzy-based indoor zone-positioning scheme is used to identify the zone in which the target node is located via zone splitting. In the second stage, adaptive trilateration is used to position the target node within the zone identified in the first stage. Simulation results demonstrate that the proposed two-stage fuzzy rectangular splitting outperforms non-fuzzy-based algorithms, including K-Nearest Neighbors–based localization, and traditional triangular splitting schemes. We also developed an expanded positioning scheme to facilitate the selection of a positioning map for large indoor spaces, thereby overcoming the limitations imposed by the size of the positioning area while maintaining high positioning resolution.
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Papliatseyeu, Andrei, Venet Osmani, and Oscar Mayora. "Indoor Positioning Using FM Radio." International Journal of Handheld Computing Research 1, no. 3 (July 2010): 19–31. http://dx.doi.org/10.4018/jhcr.2010070102.
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This paper presents an indoor positioning system based on FM radio. The system is built on commercially available short-range FM transmitters. This is the first experimental study of FM performance for indoor localisation. FM radio possesses a number of features, which make it distinct from other localisation technologies. Despite the low cost and off-the-shelf components, this FM positioning system reaches a high performance, comparable to other positioning technologies such as Wi-Fi. The authors’ experiments have yielded a median accuracy of 1.0 m and in 95% of cases the error is below 5 m.
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Mazlan, Aqilah Binti, Yin Hoe Ng, and Chee Keong Tan. "Teacher-Assistant Knowledge Distillation Based Indoor Positioning System." Sustainability 14, no. 21 (November 7, 2022): 14652. http://dx.doi.org/10.3390/su142114652.
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Indoor positioning systems have been of great importance, especially for applications that require the precise location of objects and users. Convolutional neural network-based indoor positioning systems (IPS) have garnered much interest in recent years due to their ability to achieve high positioning accuracy and low positioning error, regardless of signal fluctuation. Nevertheless, a powerful CNN framework comes with a high computational cost. Hence, there will be difficulty in deploying such a system on a computationally restricted device. Knowledge distillation has been an excellent solution which allows smaller networks to imitate the performance of larger networks. However, problems such as degradation in the student’s positioning performance, occur when a far more complex CNN is used to train a small CNN, because the small CNN does not have the ability to fully capture the knowledge that has been passed down. In this paper, we implemented the teacher-assistant framework to allow a simple CNN indoor positioning system to closely imitate a superior indoor positioning scheme. The framework involves transferring knowledge from a large pre-trained network to a small network by passing through an intermediate network. Based on our observation, the positioning error of a small network can be reduced to up to 38.79% by implementing the teacher-assistant knowledge distillation framework, while a typical knowledge distillation framework can only reduce the error to 30.18%.