Collaborative positioning for swarms:A brief survey of vision,LiDAR and wireless sensors based methods

As positioning sensors,edge computation power,and communication technologies continue to develop,a moving agent can now sense its surroundings and communicate with other agents.By receiving spatial information from both its environment and other agents,an agent can use various methods and sensor types to localize itself.With its high flexibility and robustness,collaborative positioning has become a widely used method in both military and civilian applications.This paper introduces the basic fundamental concepts and applications of collaborative positioning,and reviews recent progress in the field based on camera,LiDAR(Light Detection and Ranging),wireless sensor,and their integration.The paper compares the current methods with respect to their sensor type,summarizes their main paradigms,and analyzes their evaluation experiments.Finally,the paper discusses the main challenges and open issues that require further research.

Wireless Positioning:Technologies,Applications,Challenges,and Future Development Trends

The development of the fifth-generation(5G)mobile communication systems has entered the commercialization stage.5G has a high data rate,low latency,and high reliability that can meet the basic demands of most industries and daily life,such as the Internet of Things(IoT),intelligent transportation systems,positioning,and navigation.The continuous progress and development of society have aroused wide concern.Positioning accuracy is the core demand for the applications,especially in complex environments such as airports,warehouses,supermarkets,and basements.However,many factors also affect the accuracy of positioning in those environments,for example,multipath effects,non-line-of-sight,and clock synchronization errors.This paper provides a comprehensive review of the existing works about positioning for the future wireless network and discusses its key techniques and algorithms,as well as the current development and future directions.We first outline the current traditional positioning technologies and algorithms,which are discussed and analyzed with the relevant literature.In addition,we also discuss application scenarios for wireless localization.By comparing different positioning systems,the challenges and future development directions of existing wireless positioning systems are prospected.

Hybrid pedestrian positioning system using wearable inertial sensors and ultrasonic ranging

Pedestrian positioning system(PPS)using wearable inertial sensors has wide applications towards various emerging fields such as smart healthcare,emergency rescue,soldier positioning,etc.The performance of traditional PPS is limited by the cumulative error of inertial sensors,complex motion modes of pedestrians,and the low robustness of the multi-sensor collaboration structure.This paper presents a hybrid pedestrian positioning system using the combination of wearable inertial sensors and ultrasonic ranging(H-PPS).A robust two nodes integration structure is developed to adaptively combine the motion data acquired from the single waist-mounted and foot-mounted node,and enhanced by a novel ellipsoid constraint model.In addition,a deep-learning-based walking speed estimator is proposed by considering all the motion features provided by different nodes,which effectively reduces the cumulative error originating from inertial sensors.Finally,a comprehensive data and model dual-driven model is presented to effectively combine the motion data provided by different sensor nodes and walking speed estimator,and multi-level constraints are extracted to further improve the performance of the overall system.Experimental results indicate that the proposed H-PPS significantly improves the performance of the single PPS and outperforms existing algorithms in accuracy index under complex indoor scenarios.

A Combined Antenna Array Deployment with High Positioning Accuracy and Low Angular Measurement Error

In this paper,an antenna array composed of circular array and orthogonal linear array is proposed by using the design of long and short baseline“orthogonal linear array”and the circular array ambiguity resolution design of multi-group baseline clustering.The effectiveness of the antenna array in this paper is verified by sufficient simulation and experiment.After the system deviation correction work,it is found that in the L/S/C/X frequency bands,the ambiguity resolution probability is high,and the phase difference system error between each channel is basically the same.The angle measurement error is less than 0.5°,and the positioning error is less than 2.5 km.Notably,as the center frequency increases,calibration consistency improves,and the calibration frequency points become applicable over a wider frequency range.At a center frequency of 11.5 GHz,the calibration frequency point bandwidth extends to 1200 MHz.This combined antenna array deployment holds significant promise for a wide range of applications in contemporary wireless communication systems.

WiFi Indoor Positioning and Tracking Algorithm Based on Compressive Sensing and Sage-Husa Adaptive Kalman Filter

Aiming at the problem that the positioning accuracy of WiFi indoor positioning technology based on location fingerprint has not reached the requirements of practical application, a WiFi indoor positioning and tracking algorithm combining adaptive affine propagation (AAPC), compressed sensing (CS) and Kalman filter is proposed. In the off-line phase, AAPC algorithm is used to generate clustering fingerprints with optimal clustering effect performance;In the online phase, CS and nearest neighbor algorithm are used for position estimation;Finally, the Kalman filter and physical constraints are combined to perform positioning and tracking. By collecting a large number of real experimental data, it is proved that the developed algorithm has higher positioning accuracy and more accurate trajectory tracking effect.

Market Positioning Analysis of CJ Brand Fitness Equipment

CJ Health Technology Co.has been an export-oriented supplier of fitness equipment,boasting leading technology innovation and manufacturing capabilities.However,in the process of expanding into the domestic market,the challenges of unclear market positioning and lack of brand awareness have emerged as major obstacles.To address these issues,a SWOT analysis was conducted to explore a suitable market positioning strategy for the CJ brand.The analysis reveals that the market demand for commercial fitness equipment is relatively saturated,with fierce competition.In contrast,the home fitness market represents a new blue ocean with promising development opportunities for the CJ brand.Leveraging excellent product quality,stringent quality control measures,and innovation-driven cutting-edge technology,it is recommended that CJ brand fitness equipment target young customers aged between 25 and 35 years old.Additionally,vigorously developing the home fitness product line is proposed to capitalize on this burgeoning market segment.

Deep Learning Based Automatic Charging Identification and Positioning Method for Electric Vehicle

Electric vehicle charging identification and positioning is critically important to achieving automatic charging.In terms of the problem of automatic charging for electric vehicles,a dual recognition and positioning method based on deep learning is proposed.The method is divided into two parts:global recognition and localization and local recognition and localization.In the specific implementation process,the collected pictures of electric vehicle charging attitude are classified and labeled.It is trained with the improved YOLOv4 networkmodel and the corresponding detectionmodel is obtained.The contour of the electric vehicle is extracted by the BiSeNet semantic segmentation algorithm.The minimum external rectangle is used for positioning of the electric vehicle.Based on the location relationship between the charging port and the electric vehicle,the rough location information of the charging port is obtained.The automatic charging equipment moves to the vicinity of the charging port,and the camera near the charging gun collects pictures of the charging port.The model is detected by the Hough circle,the KM algorithmis used for featurematching,and the homography matrix is used to solve the attitude.The results show that the dual identification and location method based on the improved YOLOv4 algorithm proposed in this paper can accurately locate the charging port.The accuracy of the charging connection can reach 80%.It provides an effective way to solve the problems of automatic charging identification and positioning of electric vehicles and has strong engineering practical value.

Research Status and Trends of Indoor Positioning and Navigation Technology in China

As an essential component of future comprehensive Positioning,Navigation,and Timing(PNT)system,indoor positioning technology has extensive application demands,making it a focal point of attention in both academia and industry.This article comprehensively reviews the research status of indoor positioning technology in China,with a focus on highlighting representative achievements and application validations from major research institutions in recent years.It addresses the challenges and issues faced in promotion and application of large-scale,high-precision indoor positioning.Furthermore,a universal and seamless indoor-outdoor positioning system architecture is proposed,along with a technical roadmap and key technologies to achieve this architecture.Finally,an analysis and outlook on future technological trends are presented.

基于改进LANDMARC定位算法的人员定位技术研究

在万物互联时代,通过定位系统完成人员定位监督成为了可能,同时该项技术也日益完善。当前,基于RFID无线视频技术的局域网人员定位被广泛应用于智慧园区员工管控、重点人员监管等方面。提出了一种基于RFID的局域网人员定位算法,通过优化LANDMARC算法,对采集到的信号分别引入高斯平滑滤波器和卡尔曼滤波器,去除影响信号强度的噪声,提升定位算法的稳定性;针对LANDMARC定位算法定位精度受K值影响较大的问题,引入Logistic回归模型,以提升算法定位的准确度,有效解决了RFID在有金属、水等障碍物情况下定位精度误差大的问题,降低了外界干扰,可为人员的精准定位提供技术手段。

High-Accuracy NLOS Identification Based on Random Forest and High-Precision Positioning on 60 GHz Millimeter Wave

60 GHz millimeter wave(mmWave)system provides extremely high time resolution and multipath components(MPC)separation and has great potential to achieve high precision in the indoor positioning.However,the ranging data is often contaminated by non-line-of-sight(NLOS)transmission.First,six features of 60GHz mm Wave signal under LOS and NLOS conditions are evaluated.Next,a classifier constructed by random forest(RF)algorithm is used to identify line-of-sight(LOS)or NLOS channel.The identification mechanism has excellent generalization performance and the classification accuracy is over 97%.Finally,based on the identification results,a residual weighted least squares positioning method is proposed.All ranging information including that under NLOS channels is fully utilized,positioning failure caused by insufficient LOS links can be avoided.Compared with the conventional least squares approach,the positioning error of the proposed algorithm is reduced by 49%.

基于自适应CKF的改进LANDMARC井下定位算法研究

在矿山井下进行人员定位时,为解决传统的LANDMARC算法受井下复杂环境影响出现的定位结果精度不高、波动大的问题,提出了一种基于自适应容积卡尔曼滤波(Volumentric Kalman Filtering,CKF)的改进LANDMARC井下定位算法。首先,该算法结合传统的LANDMARC定位算法建立井下三维空间模型并求解目标位置状态预估值;其次,利用BP神经网络的泛化映射能力,引入神经元参数对CKF算法进行优化,充分结合BP神经网络迭代式学习和CKF在强非线性系统中保持稳定的特点,提高定位算法的自适应能力;最后,将位置状态预估值作为观测量进行自适应CKF滤波处理,用优化后的结果作为目标位置坐标的真实值输出,提高了井下定位的精准性。试验结果表明:引入自适应CKF进行滤波处理可以大大提高传统LANDMARC定位算法的稳定性,定位偏差分布更为集中,偏差在1 m以下的占90%以上,所提算法的定位偏差在0.612 m以下的标签达到60%,可满足井下复杂动态环境的高稳定性要求,与传统的LANDMARC定位算法和经由HIF滤波的LANDMARC定位算法相比应用于井下定位具有更好的适用性。

A Review of Device-Free Indoor Positioning for Home-Based Care of the Aged:Techniques and Technologies

With the development of urbanization,the problem of neurological diseases brought about by population aging has gradually become a social problem of worldwide concern.Aging leads to gradual degeneration of the central nervous system,shrinkage of brain tissue,and decline in physical function in many elderlies,making them susceptible to neurological diseases such as Alzheimer’s disease(AD),stroke,Parkinson’s and major depressive disorder(MDD).Due to the influence of these neurological diseases,the elderly have troubles such as memory loss,inability to move,falling,and getting lost,which seriously affect their quality of life.Tracking and positioning of elderly with neurological diseases and keeping track of their location in real-time are necessary and crucial in order to detect and treat dangerous and unexpected situations in time.Considering that the elderly with neurological diseases forget to wear a positioning device or have mobility problems due to carrying a positioning device,device-free positioning as a passive positioning technology that detects device-free individuals is more suitable than traditional active positioning for the home-based care of the elderly with neurological diseases.This paper provides an extensive and in-depth survey of device-free indoor positioning technology for home-based care and an in-depth analysis of the main features of current positioning systems,as well as the techniques,technologies andmethods they employ,fromthe perspective of the needs of the elderly with neurological conditions.Moreover,evaluation criteria and possible solutions of positioning techniques for the home-based care of the elderly with neurological conditions are proposed.Finally,the opportunities and challenges for the development of indoor positioning technology in 6G mobile networks for home-based care of the elderly with neurological diseases are discussed.This review has provided comprehensive and effective tracking and positioning techniques,technologies and methods for the elderly,by which we can obtain the location information of the elderly in real-time and make home-based care more comfortable and safer for the elderly with neurological diseases.

An improved particle filter indoor fusion positioning approach based on Wi-Fi/PDR/geomagnetic field

The existing indoor fusion positioning methods based on Pedestrian Dead Reckoning(PDR)and geomagnetic technology have the problems of large initial position error,low sensor accuracy,and geomagnetic mismatch.In this study,a novel indoor fusion positioning approach based on the improved particle filter algorithm by geomagnetic iterative matching is proposed,where Wi-Fi,PDR,and geomagnetic signals are integrated to improve indoor positioning performances.One important contribution is that geomagnetic iterative matching is firstly proposed based on the particle filter algorithm.During the positioning process,an iterative window and a constraint window are introduced to limit the particle generation range and the geomagnetic matching range respectively.The position is corrected several times based on geomagnetic iterative matching in the location correction stage when the pedestrian movement is detected,which made up for the shortage of only one time of geomagnetic correction in the existing particle filter algorithm.In addition,this study also proposes a real-time step detection algorithm based on multi-threshold constraints to judge whether pedestrians are moving,which satisfies the real-time requirement of our fusion positioning approach.Through experimental verification,the average positioning accuracy of the proposed approach reaches 1.59 m,which improves 33.2%compared with the existing particle filter fusion positioning algorithms.

Wave-Particle Duality: Particle Always Remains Particle and Its Wave Function Always Remains Wave

On the question of wave-particle duality, from the historic Bohr-Einstein debates a century ago, to this day, the view expressed in Niels Bohr’s Complementarity Principle has become well established, confirmed by numerous experiments: If the observation is for wave nature, then the particle changes to wave, and if the observation is for particle nature, then the particle remains particle. However, recently this view has been challenged. With proof based on the definition of wave function, it has been shown that particle always remains particle and its wave function always remains wave, no mysterious change from particle to wave and vice versa.

Positioning and design by computed tomography imaging in neuroendoscopic surgery of patients with chronic subdural hematoma

BACKGROUND Neuroendoscopy is a very useful technique to Chronic Subdural Hematoma(CSH).But how to achieve the goal of treatment more minimally invasive?AIM To develop a simple,fast and accurate preoperative planning method in our way for endoscopic surgery of patients with CSH.METHODS From June 2018 to May 2020,forty-two patients with CSH,admitted to our hospital,were performed endoscopic minimally invasive surgery;computed tomography(CT)imaging was employed to locate the intracerebral hematoma and select the appropriate endoscopic approach before the endoscopic surgery.The clinical data and treatment efficacy were analyzed.RESULTS According to the learning of CT scanning images,the surgeon can accurately design the best minimally invasive neuroendoscopic surgical approach and realize the precise positioning and design of the drilling site of the skull and the size of the bone window,so as to provide the most effective operation space with the smallest bone window.In this group,the average operation time was only about 1 h,and the clearance rate of hematoma was about 95%.CONCLUSION Patients with CSH can achieve good therapeutic effect by using our way to positioning and design to assist the operation of CSH according to CT scan and image,and our way is very useful and necessary.

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.

Robot Positioning Based on Multiple Quick Response Code Landmarks

The scheme of robot positioning based on multiple quick response(QR)code landmarks is proposed.Firstly,the pose of the robot relative to the QR code landmarks is obtained by extracting the feature points of the QR code,combined with the visual computing technology.Then,the conversion of the absolute pose of the robot is completed based on the absolute position of the QR code landmark,and thus the real-time position of the robot is obtained.The proposed scheme makes full use of the QR code fault tolerance and multiple QR code landmarks to improve the calculation accuracy.It has good robustness and versatility,and it is easy to implement.It can help the robot to complete the positioning in the actual work,making robot navigation more accurate.

Monitoring of Coastal Subsidence Changes Based on GNSS Positioning and GNSS-IR

Coastal subsidence monitoring typically employs Global Navigation Satellite System(GNSS)positioning technology.This method provides information only about subsidence below the station base.Sediments in coastal areas tend to accumulate quickly,and subsidence can change significantly due to compaction and alluvium.Therefore,monitoring subsidence above the base is essential to obtain overall coastal subsidence.A new technology called GNSS-Interferometric Reflectometry(GNSS-IR)has been recently developed,which can utilize multipath effects to monitor reflector height.Since the base of the GNSS station is deep and the base length remains constant,the height changes measured by the GNSS-IR technology can reflect subsidence above the base.Accordingly,this paper employs GNSS-IR technology to measure subsidence changes above the base.Additionally,GNSS positioning technology is used to obtain subsidence changes below the base,and the overall subsidence change is then calculated using both GNSS-IR and GNSS positioning technology.The Mississippi River Delta,known for its significant sediment thickness,was selected as the study area,and data from FSHS,GRIS,and MSIN stations was analyzed.The results demonstrate that GNSS-IR can be used to measure the subsidence rate above the base,and the corrected overall subsidence rate is equivalent to the relative sea level rise rate.

Structural and Ferroelectric Transition in Few-Layer HfO_(2) Films by First Principles Calculations

The discovery of ferroelectricity in HfO_(2)-based materials with high dielectric constant has inspired tremendous research interest for next-generation electronic devices.Importantly,films structure and strain are key factors in exploration of ferroelectricity in fluorite-type oxide HfO_(2) films.Here we investigate the structures and straininduced ferroelectric transition in different phases of few-layer HfO_(2) films(layer number𝑁=1–5).It is found that HfO_(2) films for all phases are more stable with increasing films thickness.Among them,the Pmn2_(1)(110)-oriented film is most stable,and the films of𝑁=4,5 occur with a𝑃21 ferroelectric transition under tensile strain,resulting in polarization about 11.8μC/cm^(2) along in-plane𝑎-axis.The ferroelectric transition is caused by the strain,which induces the displacement of Hf and O atoms on the surface to non-centrosymmetric positions away from the original paraelectric positions,accompanied by the change of surface Hf–O bond lengths.More importantly,three new stable HfO_(2)2D structures are discovered,together with analyses of computed electronic structures,mechanical,and dielectric properties.This work provides guidance for theoretical and experimental study of the new structures and strain-tuned ferroelectricity in freestanding HfO_(2) films.

Influence of High-Pressure Induced Lattice Dislocations and Distortions on Thermoelectric Performance of Pristine SnTe

As a sister compound of PbTe, SnTe possesses the environmentally friendly elements. However, the pristine SnTe compounds suffer from the high carrier concentration, the large valence band offset between the L and Σpositions and high thermal conductivity. Using high-pressure and high-temperature technology, we synthesized the pristine SnTe samples at different pressures and systemically investigated their thermoelectric properties.High pressure induces rich microstructures, including the high-density dislocations and lattice distortions, which serve as the strong phonon scattering centers, thereby reducing the lattice thermal conductivity. For the electrical properties, pressure reduces the harmful high carrier concentration, due to the depression of Sn vacancies.Moreover, pressure induces the valence band convergence, reducing the energy separation between the L and Σpositions. The band convergence and suppressed carrier concentration increase the Seebeck coefficient. Thus, the power factors of pressure-sintered compounds do not deteriorate significantly under the condition of decreasing electrical conductivity. Ultimately, for a pristine SnTe compound synthesized at 5 GPa, a higher ZT value of 0.51 is achieved at 750 K, representing a 140% improvement compared to the value of 0.21 obtained using SPS. Therefore, the high-pressure and high-temperature technology is demonstrated as an effectively approach to optimize thermoelectric performance.