Hybrid Positioning Research Articles

TDOA and FDOA Hybrid Positioning of Mobile Radiation Source with Receiver Position Errors

TDOA and FDOA Hybrid Positioning of Mobile Radiation Source with Receiver Position Errors

Robust GNSS Spoofing Detection Against UE Maneuver in a GNSS-5G mmWave Hybrid Positioning System

Robust GNSS Spoofing Detection Against UE Maneuver in a GNSS-5G mmWave Hybrid Positioning System

Performance Analysis of GNSS + 5G Hybrid Positioning Algorithms for Smartphones in Urban Environments

Performance Analysis of GNSS + 5G Hybrid Positioning Algorithms for Smartphones in Urban Environments

5G Positioning: An Analysis of Early Datasets.

Global Navigation Satellite Systems (GNSSs) are nowadays the prevailing technology for positioning and navigation. However, with the roll-out of 5G technology, there is a shift towards 'hybrid positioning': indeed, 5G time-of-arrival (ToA) measurements can provide additional ranging for positioning, especially in environments where few GNSS satellites are visible. This work reports a preliminary analysis, the processing, and the results of field measurements collected as part of the GINTO5G project funded by ESA's EGEP programme. The data used in this project were shared by the European Space Agency (ESA) with the DICA of Politecnico di Milano as part of a collaboration within the ESALab@PoliMi research framework established in 2022 between the two organizations. The ToA data were collected during a real-world measurement campaign and they cover a wide range of user environments, such as indoor areas, outdoor open sky, and outdoor obstructed scenarios. Within the test area, eleven self-made replica 5G base stations were set up. A trolley, carrying a self-made 5G receiver and a data storage unit, was moved along predefined trajectories; the trolley's accurate trajectories were determined by a total station, which provided benchmark positions. In the present work, the 5G data are processed using the least squares method, testing and comparing different strategies. Therefore, the primary goal is to evaluate algorithms for position determination of a user based on 5G observations, and to empirically assess their accuracy. The results obtained are promising, with positional accuracy ranging from decimeters to a few meters in the worst cases.

Integrated positioning with double-differenced 5G and undifferenced/double-differenced GPS

As the demand for hybrid indoor and outdoor positioning has increased, the research trend in positioning technology has shifted to hybrid positioning technology suitable for complex indoor and outdoor environments. High-precision positioning technology combined with Global Navigation Satellite Systems (GNSS) and fifth-generation mobile communication technology (5G) has many applications in many industries. A double-differenced algorithm applicable to 5G was proposed to solve the impact of the 5G clock synchronization error on the positioning. Double-differenced observations were obtained by introducing reference terminals to eliminate the influence of clock errors on positioning accuracy between terminals and base stations and between base stations and base stations. Then, the dynamic positioning performance of different combined positioning models under different occluded environments was investigated by combining 5G double-differenced observations with undifferenced/double-differenced GPS observations and comparing the positioning results with GPS-only. The results showed that the combined positioning model can achieve more accurate positioning results than a single system in different positioning modes, and the advantages were more evident in the occluded environment. This study provides a reference for hybrid positioning techniques in complex indoor and outdoor environments and promotes further development of seamless indoor and outdoor positioning.

HY-PC: Enabling consistent positioning and communication using visible light

Visible light (VL) plays an important role in achieving high-precision positioning and low bit error radio (BER) data communication. However, most VL-based systems can not achieve positioning and communication, simultaneously. There are two problems: 1) the hybrid systems are difficult to extract distinguishable positioning beacon features without affecting communication performance, 2) in the hybrid systems, the lost data bits in the inter-frame gap (IFG) are hard to recover, which affects positioning and communication performance. Therefore, in this article, we propose a novel VL-based hybrid positioning and communication system, named HY-PC system, to solve the above problems. First, we propose the robust T-W mapping for recognizing specific Light Emitting Diodes (LEDs), which can provide stable LED recognition accuracy without adding extra beacon data and does not decrease the communication rate. Furthermore, we also propose the novel linear block coding and bit interleaving mechanism, which can recover the lost data bits in the IFG and improve data communication performance. Finally, we use commercial off-the-shelf devices to implement our HY-PC system, extensive experimental results show that our HY-PC system can achieve consistent high-precision positioning and low-BER data communication, simultaneously.

Indoor Positioning System Using a Single-Chip Millimeter Wave Radar

Estimation of indoor location is a key capability for indoor location-based services. Among various solutions, single-chip low-cost millimeter-wave (mmWave) radar as an emerging technology are getting more and more attention due to their inherent advantages such as penetration ability, low-power consumption. Currently, the vast majority of work is focused on hybrid positioning based on mmWave radar with other sensors, and there is a lack of research on single radar indoor positioning. In this article, we propose a novel indoor positioning system based on single-radar sensor, which determines the trajectory by estimating the velocity and heading of moving radar from sparse point clouds. Doppler velocity of detected object can be able to feedback the radar velocity, and for another hand, the proposed Cluster Center Association (CCA) method combined with normal distributions transform (NDT) can be used for heading estimation. In addition, we proposed the motion consistency constraints to enhance the robustness of the system. The experimental results show that the traditional NDT algorithm will fail due to the sparse point cloud and severe indoor multipath, and the proposed algorithm can provide the positioning accuracy within 1 m and the heading estimation error of 3°.

Indoor navigation and information sharing for collaborative fire emergency response with BIM and multi-user networking

Collaboration in indoor fire emergencies requires participants to share various information regarding individuals, fires, and resources. To facilitate response actions, this study develops a system to provide the necessary information, calculate route guidance for escape and rescue, track victim locations, and share resources with participants promptly. The system includes a pathfinding module using geometries of building information models, a positioning module fusing inertial sensor data and wireless signals via a particle filter, an information exchange module that delivers emergency-related properties, and an information sharing module that distributes information through a multi-user environment. Moreover, a two-stage pathfinding algorithm and a hybrid positioning approach are proposed to improve computational efficiency and localization accuracy. Through comparative evaluation, the system is validated to reduce the computational time by 89.29% and lessen the positioning error to 1.36 m. The study is expected to provide explicit insights into developing digital twins for collaborative emergency response.

산업현장에서의 실내외 연속측위를 위한 GNSS-UWB 하이브리드 측위 시스템

In this paper, we propose a GNSS-UWB hybrid positioning system for indoor and outdoor seamless positioning. Fusion of GNSS and inertial sensors has been widely used as a method for estimating positions in places where GNSS reception sensitivity is low, and UWB technology, which started as a short-range wireless communication technology, is widely used indoors where GNSS is completely blocked. This paper proposes a method of mutual correction and fusion of the location information collected through GNSS and the location information collected from the UWB indoor positioning system when indoor and outdoor work occurs continuously and repeatedly, such as in an industrial site.

Accurate Long‐Term Evolution/Wi‐Fi hybrid positioning technology for emergency rescue

AbstractIt is critical to estimate the location using only Long‐Term Evolution (LTE) and Wi‐Fi information gathered by the user's smartphone and deployable for emergency rescue, regardless of whether the Global Positioning System is received. In this research, we used a vehicle to gather LTE and Wi‐Fi wireless signals over a large area for an extended period of time. After that, we used the learning technique to create a positioning database that included both collection and noncollection points. We presented a two‐step positioning algorithm that utilizes coarse localization to discover a rough location in a wide area rapidly and fine localization to estimate a particular location based on the coarse position. We confirmed our technology utilizing different sorts of devices in four regional types that are generally encountered: dense urban, urban, suburban, and rural. Results presented that our algorithm can satisfactorily achieve the target accuracy necessary in emergency rescue circumstances.

Hybrid Positioning Technique Based Integration of GPS/INS for an Autonomous Vehicle Navigation

This paper presents a hybrid positioning technique combining both loosely and tightly coupled Kalman Filter (KF) algorithms for an autonomous multi-wheeled combat vehicle. The developed algorithm is able to provide accurate positioning information even if number of visible satellites falls below the minimum due to the harsh operation environments. Two modes of operation were considered which automatically switch between them according to the number of visible satellites in order to correct the INS drift. Furthermore, a performance comparison between fifteen and eighteen KFs states is conducted. A simulation of the developed algorithm is performed, using a SATNAV navigation toolbox and the collected data from real sensors mounted on a ground vehicle. The experimental results validated effectiveness of the developed algorithm.

Advanced Hybrid Positioning System of SEM and AFM for 2D Material Surface Metrology.

As the measurement scale shrinks, the reliability of nanoscale measurement is even more crucial for a variety of applications, including semiconductor electronics, optical metamaterials, and sensors. Specifically, it is difficult to measure the nanoscale morphology at the exact location though it is required for novel applications based on hybrid nanostructures combined with 2D materials. Here, we introduce an advanced hybrid positioning system to measure the region of interest with enhanced speed and high precision. A 5-axis positioning stage (XYZ, R, gripper) makes it possible to align the sample within a 10-μm field of view (FOV) in both the scanning electron microscope (SEM) and the atomic force microscope (AFM). The reproducibility of the sample position was investigated by comparing marker patterns and denting points between the SEM and AFM, revealing an accuracy of 6.5 ± 2.1 μm for the x-axis and 4.5 ± 1.7 μm for the y-axis after 12 repetitions. By applying a different measurement process according to the characteristics of 2D materials, various information such as height, length, or roughness about MoTe2 rods and MoS2 film was obtained in the same measurement area. As a consequence, overlaid two images can be obtained for detailed information about 2D materials.

A Novel Airspace Planning Algorithm for Cooperative Target Localization

With the development of modern electromagnetic stealth technology and ARM, traditional active radar detection cannot accomplish its detection mission, limited by its ability. Relying on such superior advantages such as imperceptibility, anti-electromagnetic interference and electromagnetic stealth, passive transducers are playing an indispensable and significant role in situation awareness. While, in addition to different passive transducer localization modes and solutions of target’s location, the reasonable planning and optimal layout of passive transducers’ location are other major factors affecting the precision of localization. Planning an optimal airspace for passive transducers is the key problem to improve the monitoring efficiency. This paper proposes the optimal layout algorithm for the cooperative platform in the space based on the geometrical relationship of cooperative localization. For example, the principle of direction location in traditional methods is simple: only two passive sensors can work, but the location accuracy of long-distance targets is low. At the same time, TDOA (Time Difference Of Arrival) location has high accuracy and good stability, but it needs at least three passive sensors to work together, which requires the most resources. In this paper, a platform optimization layout algorithm based on direction and TDOA hybrid positioning is proposed. Compared with direction positioning, it improves the long-distance positioning accuracy, reduces the number of sensors required for TDOA positioning, and reduces the resource occupancy rate. However, the TDOA positioning data mixed with direction positioning data inevitably leads to the decline of overall accuracy. In order to solve these difficulties, the weighted least square method is used to optimize the accuracy. The simulation shows that, within the designated target airspace, the optimal action airspace can be generated automatically based on the platforms’ cooperation mode. If there is no resource limitation, the airspace planning based on TDOA positioning has the highest accuracy for the target. However, in practical application, considering the resource limitation, the hybrid positioning of direction and TDOA can also meet the requirements of high accuracy and high stability. The average error is reduced by more than 45% compared with direction positioning, and the airspace occupancy is reduced by more than 30% compared with TDOA positioning. The goal of minimizing the scope of platform airspace planning is realized.

Indoor Positioning with CNN and Path-Loss Model Based on Multivariable Fingerprints in 5G Mobile Communication System.

Many application scenarios require indoor positioning in fifth generation (5G) mobile communication systems in recent years. However, non-line of sight and multipath propagation lead to poor accuracy in a traditionally received signal strength-based fingerprints positioning system. In this paper, we propose a positioning method employing multivariable fingerprints (MVF) composed of measurements based on secondary synchronization signals (SSS). In the fingerprint matching, we use MVF to train the convolutional neural network (CNN) location classification model. Moreover, we utilize MVF to train the path-loss model, which indicates the relationship between the distance and the measurement. Then, a hybrid positioning model combining CNN and path-loss model is proposed to optimize the overall positioning accuracy. Experimental results show that all three positioning algorithms based on machine learning with MVF achieve accuracy improvement compared with that of Reference Signal Receiving Power (RSRP)-only fingerprint. CNN achieves best performance among three positioning algorithms in two experimental environments. The average positioning error of hybrid positioning model is 1.47 m, which achieves 9.26% accuracy improvement compared with that of CNN alone.

The underground explosion point high precision measurement method based on multidimensional information fusion of vibration sensors

PurposeThe purpose of this paper is to solve the problem that the location of the initiation point cannot be measured accurately in the shallow underground space, this paper proposes a method, which is based on fusion of multidimensional vibration sensor information, to locate single shallow underground sources.Design/methodology/approachFirst, in this paper, using the characteristics of low multipath interference and good P-wave polarization in the near field, the adaptive covariance matrix algorithm is used to extract the polarization angle information of the P-wave and the short term averaging/long term averaging algorithm is used to extract the first break travel time information. Second, a hybrid positioning model based on travel time and polarization angle is constructed. Third, the positioning model is taken as the particle update fitness function of quantum-behaved particle swarm optimization and calculation is performed in the hybrid positioning model. Finally, the experiment verification is carried out in the field.FindingsThe experimental results show that, with root mean square error, spherical error probable and fitness value as evaluation indicators, the positioning performance of this method is better than that without speed prediction. And the positioning accuracy of this method has been improved by nearly 30%, giving all of the three tests a positioning error within 0.5 m and a fitness less than 1.Originality/valueThis method provides a new idea for high-precision positioning of shallow underground single source. It has a certain engineering application value in the fields of directional demolition of engineering blasting, water inrush and burst mud prediction, fuze position measurement, underground initiation point positioning of ammunition, mine blasting monitoring and so on.

Is brand globalness compatible with brand country-of-origin? An investigation of hybrid brand positioning strategies for emerging market brands

PurposeThe purpose of this study is to investigate hybrid brand positioning strategies for emerging market brands based on two positioning elements: brand country-of-origin (COO) and brand globalness.Design/methodology/approachResearchers conducted two studies. In Study 1, a survey of 128 brand managers of emerging market brands were used to examine whether asymmetric positioning strategies improve brand preference more than symmetric strategies, and if so, which type of asymmetric strategies improves brand preference more. In Study 2, a consumer experiment in the USA was conducted to identify the positioning strategy for emerging market brands that improve brand preference the most.FindingsFor emerging market brands, at any given value of COO or global elements, asymmetric strategies outperform symmetric strategies in terms of brand preference. On average, the best hybrid positioning strategy is the one that highlights brand COO and de-emphasizes brand globalness.Originality/valueA large body of branding literature examines COO and globalness separately without considering their co-presence in the same brand positioning strategy. Few studies that examine the joint influence of brand COO and globalness focus on established brands from developed markets and do not examine whether highlighting both brand COO and global elements equally is an effective positioning strategy for emerging market brands. This study introduces a framework to systematically examine the various combinations of COO and global elements in a brand’s positioning strategies for emerging market brands. By conducting two studies, the authors empirically test the influence of various combinations of COO and global elements on brand preference for emerging market brands from both firm and consumer perspectives.

An Optimal Geometry Configuration Algorithm of Hybrid Semi-Passive Location System Based on Mayfly Optimization Algorithm.

In view of the demand of location awareness in a special complex environment, for an unmanned aerial vehicle (UAV) airborne multi base-station semi-passive positioning system, the hybrid positioning solutions and optimized site layout in the positioning system can effectively improve the positioning accuracy for a specific region. In this paper, the geometric dilution of precision (GDOP) formula of a time difference of arrival (TDOA) and angles of arrival (AOA) hybrid location algorithm is deduced. Mayfly optimization algorithm (MOA) which is a new swarm intelligence optimization algorithm is introduced, and a method to find the optimal station of the UAV airborne multiple base station’s semi-passive positioning system using MOA is proposed. The simulation and analysis of the optimization of the different number of base stations, compared with other station layout methods, such as particle swarm optimization (PSO), genetic algorithm (GA), and artificial bee colony (ABC) algorithm. MOA is less likely to fall into local optimum, and the error of regional target positioning is reduced. By simulating the deployment of four base stations and five base stations in various situations, MOA can achieve a better deployment effect. The dynamic station configuration capability of the multi-station semi-passive positioning system has been improved with the UAV.

Positioning precision analysis of passive phased array radar localization for construction safety monitoring in a non-line-of-sight environment via heatmap

A positioning system for complex construction scenarios is necessary to apply due to the limitations of the traditional positioning system in a non-line-of-sight (NLOS) environment, in order to study the impact of obstacles on construction sites. A quantitative measurement experiment of positioning precision in an NLOS environment was conducted in a petrochemical construction site, and a large number of engineering data were obtained, which showed the feasibility of a Passive Phased Array Radar - Bluetooth Hybrid Positioning System (PPAR-B HPS). The novelty of this paper is to propose a simplified signal coverage model for rapid measurement via the analysis of on-site data of the petrochemical industry and analyze the factors affecting the positioning precision in NLOS environment via a positioning precision heatmap analysis method to promoting the development and application of positioning technology in construction sites. The effectiveness of these methods are proved by empirical and comparative research.

Point Positioning Capability of Compact, Low-Cost GNSS Modules: A Case Study

Global Navigation Satellite System (GNSS) provides precise Position, Velocity, and Timing (PVT) information. Various types of receivers of varying cost and complexity are used for collection and use of GNSS data. Currently, cost-effective, compact, low power consuming, multi-constellation enabled, single, or dual-frequency GNSS modules are being increasingly available having the capability of providing modest position solution accuracy. This paper presents the results of GPS, BeiDou, and GPS + BeiDou hybrid positioning capabilities of few commercially available modules based on systematic analysis from data collected during two time periods from two locations of India using geodetic and commercial patch antennas w.r.t. the reference points created through PPP (Precise Point Positioning). The results are compared with those provided a survey-grade GNSS receiver. It is witnessed that, selected single frequency module can provide 3-4m 2DRMS (Distance Root Means Square) precision and their dual frequency counterparts can provide 2DRMS solution precision around 3 m in GPS-only operation, around 7 m in BeiDou-only operation and around 3.5 m in case of GPS + BeiDou hybrid operation. The performance of the compact modules clearly presents the cost-performance benefit of the compact modules for real-time applications and the results of this study would help in understanding the capabilities of these modules for mass-market applications.

Hybrid Tightly-Coupled SINS/LBL for Underwater Navigation System

The application of long baseline aided strap-down inertial navigation system (SINS/LBL) has been demonstrated to be an effective solution for accumulative position errors of underwater vehicles (UVs). To address the inefficient positioning when available hydrophones are few in acoustic array, a hybrid tightly-coupled SINS/LBL is presented for underwater navigation system. The system is composed of SINS, LBL and pressure sensor (PS). The hybrid positioning model based on slant range, slant-range rate, slant-range difference and slant-range rate difference is established according to the location principle of time of arrival (TOA) and time difference of arrival (TDOA) when the number of available hydrophones is two. TDOA positioning model based on slant-range difference and slant-range rate difference is adopted when the number of available hydrophones is more than two. The two tightly-coupled SINS/LBL models could be switched with each other as the number of available hydrophones changes in acoustic array. This paper used experimental data obtained from an unmanned surface vehicle (USV) to validate the navigation performance. Compared with single tightly-coupled SINS/LBL model, the proposed method can provide faster error convergence and more accurate submerged position fixes.