A GPS/BDS dual-mode positioning algorithm for a train based on CIPSO_EKF

When using global positioning system/BeiDou navigation satellite(GPS/BDS)dual-mode navigation system to locate a train,Kalman filter that is used to calculate train position has to be adjusted according to the features of the dual-mode observation.Due to multipath effect,positioning accuracy of present Kalman filter algorithm is really low.To solve this problem,a chaotic immune-vaccine particle swarm optimization_extended Kalman filter(CIPSO_EKF)algorithm is proposed to improve the output accuracy of the Kalman filter.By chaotic mapping and immunization,the particle swarm algorithm is first optimized,and then the optimized particle swarm algorithm is used to optimize the observation error covariance matrix.The optimal parameters are provided to the EKF,which can effectively reduce the impact of the observation value oscillation caused by multipath effect on positioning accuracy.At the same time,the train positioning results of EKF and CIPSO_EKF algorithms are compared.The eastward position errors and velocity errors show that CIPSO_EKF algorithm has faster convergence speed and higher real-time performance,which can effectively suppress interference and improve positioning accuracy.

One stone two birds:electrochemical and colorimetric dual-mode biosensor based on copper peroxide/covalent organic framework nanocomposite for ultrasensentive norovirus detection

Norovirus(NoV)is regarded as one of the most common causes of foodborne diarrhea in the world.It is urgent to identify the pathogenic microorganism of the diarrhea in short time.In this work,we developed an electrochemical and colorimetric dual-mode detection for NoV based on the excellent dual catalytic properties of copper peroxide/COF-NH_(2)nanocomposite(CuO_(2)@COF-NH_(2)).For the colorimetric detection,NoV can be directly detected by the naked eye based on CuO_(2)@COF-NH_(2)as a laccase-like nonazyme using“peptide-NoV-antibody”recognition mode.The colorimetric assay displayed a wide and quality linear detection range from 1 copy/mL to 5000 copies/mL of NoV with a low limit of detection(LOD)of 0.125 copy/mL.For the electrochemical detection of NoV,CuO_(2)@COF-NH_(2)showed an oxidation peak of copper ion from Cu^(+)to Cu^(2+)using“peptide-NoV-antibody”recognition mode.The electrochemical assay showed a linear detection range was 1-5000 copies/mL with a LOD of 0.152 copy/mL.It's worthy to note that this assay does not need other electrical signal molecule,which provide the stable and sensitive electrochemial detection for NoV.The electrochemical and colorimetric dual-mode detection was used to detect NoV in foods and faceal samples,which has the potential for improving food safety and diagnosing of NoV-infected diarrhea.

A crosstalk-free dual-mode sweat sensing system for naked-eye sweat loss quantification via changes in structural reflectance

Sweat loss monitoring is important for understanding the body’s thermoregulation and hydration status,as well as for comprehensive sweat analysis.Despite recent advances,developing a low-cost,scalable,and universal method for the fabrication of colorimetric microfluidics designed for sweat loss monitoring remains challenging.In this study,we propose a novel laserengraved surface roughening strategy for various flexible substrates.This process permits the construction of microchannels that show distinct structural reflectance changes before and after sweat filling.By leveraging these unique optical properties,we have developed a fully laser-engraved microfluidic device for the quantification of naked-eye sweat loss.This sweat loss sensor is capable of a volume resolution of 0.5µL and a total volume capacity of 11µL,and can be customized to meet different performance requirements.Moreover,we report the development of a crosstalk-free dual-mode sweat microfluidic system that integrates an Ag/AgCl chloride sensor and a matching wireless measurement flexible printed circuit board.This integrated system enables the real-time monitoring of colorimetric sweat loss signals and potential ion concentration signals without crosstalk.Finally,we demonstrate the potential practical use of this microfluidic sweat loss sensor and its integrated system for sports medicine via on-body studies.

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.

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.

A utility and easily fabricated dual-mode fiber film for efficient and comfortable thermal management

Nowadays, the global climate is constantly being destroyed and the fluctuations in ambient temperature are becoming more frequent. However, conventional single-mode thermal management strategies(heating or cooling) failed to resolve such dynamic temperature changes. Moreover, developing thermal management devices capable of accommodating these temperature variations while remaining simple to fabricate and durable has remained a formidable obstacle. To address these bottlenecks, we design and successfully fabricate a novel dual-mode hierarchical(DMH) composite film featuring a micronanofiber network structure, achieved through a straightforward two-step continuous electrospinning process. In cooling mode, it presents a high solar reflectivity of up to 97.7% and an excellent atmospheric transparent window(ATW) infrared emissivity of up to 98.9%. Noted that this DMH film could realize a cooling of 8.1 ℃ compared to the ambient temperature outdoors. In heating mode, it also exhibits a high solar absorptivity of 94.7% and heats up to 11.9 ℃ higher than black cotton fabric when utilized by individuals. In practical application scenarios, a seamless transition between efficient cooling and heating is achieved by simply flipping the film. More importantly, the DMH film combining the benefits of composites demonstrates portability, durability, and easy-cleaning, promising to achieve large-scale production and use of thermally managed textiles in the future. The energy savings offered by film applications provide a viable solution for the early realization of carbon neutrality.

Adaptive H_(∞)Filtering Algorithm for Train Positioning Based on Prior Combination Constraints

To solve the problem of data fusion for prior information such as track information and train status in train positioning,an adaptive H∞filtering algorithm with combination constraint is proposed,which fuses prior information with other sensor information in the form of constraints.Firstly,the train precise track constraint method of the train is proposed,and the plane position constraint and train motion state constraints are analysed.A model for combining prior information with constraints is established.Then an adaptive H∞filter with combination constraints is derived based on the adaptive adjustment method of the robustness factor.Finally,the positioning effect of the proposed algorithm is simulated and analysed under the conditions of a straight track and a curved track.The results show that the positioning accuracy of the algorithm with constrained filtering is significantly better than that of the algorithm without constrained filtering and that the algorithm with constrained filtering can achieve better performance when combined with track and condition information,which can significantly reduce the train positioning error.The effectiveness of the proposed algorithm is verified.

A semantic vector map-based approach for aircraft positioning in GNSS/GPS denied large-scale environment

Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework for aircraft geo-localization in a large range that only requires a downward-facing monocular camera,an altimeter,a compass,and an open-source Vector Map(VMAP).The algorithm combines the matching and particle filter methods.Shape vector and correlation between two building contour vectors are defined,and a coarse-to-fine building vector matching(CFBVM)method is proposed in the matching stage,for which the original matching results are described by the Gaussian mixture model(GMM).Subsequently,an improved resampling strategy is designed to reduce computing expenses with a huge number of initial particles,and a credibility indicator is designed to avoid location mistakes in the particle filter stage.An experimental evaluation of the approach based on flight data is provided.On a flight at a height of 0.2 km over a flight distance of 2 km,the aircraft is geo-localized in a reference map of 11,025 km~2using 0.09 km~2aerial images without any prior information.The absolute localization error is less than 10 m.

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.

Synthetic Aperture Positioning: A Review

Obtaining precise position of interested emitters passively has wide applications in both civilian and military fields.Different from traditional parameter measurement and direct position determination(DPD)method,recently a new passive localization method based on synthetic aper-ture technique,named synthetic aperture positioning(SAP),has been proposed.The method com-pensates for the nonlinear phase produced by relative motion between the moving platform and the emitter,achieving coherent summation of intercepted signals.The SAP can obtain high-resolution and high-precision localization results at a low signal-to-noise ratio.This paper summarizes the research progress of SAP,including localization principles,spaceborne applications,and application scope analysis.Besides,the possible future outlook of SAP is considered.

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.

System error iterative identification for underwater positioning based on spectral clustering

The observation error model of the underwater acous-tic positioning system is an important factor to influence the positioning accuracy of the underwater target.For the position inconsistency error caused by considering the underwater tar-get as a mass point,as well as the observation system error,the traditional error model best estimation trajectory(EMBET)with little observed data and too many parameters can lead to the ill-condition of the parameter model.In this paper,a multi-station fusion system error model based on the optimal polynomial con-straint is constructed,and the corresponding observation sys-tem error identification based on improved spectral clustering is designed.Firstly,the reduced parameter unified modeling for the underwater target position parameters and the system error is achieved through the polynomial optimization.Then a multi-sta-tion non-oriented graph network is established,which can address the problem of the inaccurate identification for the sys-tem errors.Moreover,the similarity matrix of the spectral cluster-ing is improved,and the iterative identification for the system errors based on the improved spectral clustering is proposed.Finally,the comprehensive measured data of long baseline lake test and sea test show that the proposed method can accu-rately identify the system errors,and moreover can improve the positioning accuracy for the underwater target positioning.

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.

Accurate Source-Receiver Positioning Method for a High-Resolution Deep-Towed Multichannel Seismic Exploration System

The near-seabed multichannel seismic exploration systems have yielded remarkable successes in marine geological disaster assessment,marine gas hydrate investigation,and deep-sea mineral exploration owing to their high vertical and horizontal resolution.However,the quality of deep-towed seismic imaging hinges on accurate source-receiver positioning information.In light of existing technical problems,we propose a novel array geometry inversion method tailored for high-resolution deep-towed multichannel seismic exploration systems.This method is independent of the attitude and depth sensors along a deep-towed seismic streamer,accounting for variations in seawater velocity and seabed slope angle.Our approach decomposes the towed line array into multiline segments and characterizes its geometric shape using the line segment distance and pitch angle.Introducing optimization parameters for seawater velocity and seabed slope angle,we establish an objective function based on the model,yielding results that align with objective reality.Employing the particle swarm optimization algorithm enables synchronous acquisition of optimized inversion results for array geometry and seawater velocity.Experimental validation using theoretical models and practical data verifies that our approach effectively enhances source and receiver positioning inversion accuracy.The algorithm exhibits robust stability and reliability,addressing uncertainties in seismic traveltime picking and complex seabed topography conditions.

An improved positioning model of deep-seafloor datum point at large incidence angle

The inhomogeneous sound speed in seawater causes refraction of sound waves,and the elimination of the refraction effect is essential to the accuracy of underwater acoustic positioning.The raytracing method is an indispensable tool for effectively handling problems.However,this method has a conflict between localization accuracy and computational quantity.The equivalent sound speed profile(ESSP)method uses a simple sound speed profile(SSP)instead of the actual complex SSP,which can improve positioning precision but with residual error.The residual error is especially non-negligible in deep water and at large beam incidence angles.By analyzing the residual error of the ESSP method through a simulation,an empirical formula of error is presented.The data collected in the sailing circle mode(large incidence angle)of the South China Sea are used for verification.The experiments show that compared to the ESSP method,the improved algorithm has higher positioning precision and is more efficient than the ray-tracing method.

Performance Evaluation of Low-Cost Dual-Frequency GNSS Receivers for Precise Positioning in Senegal: Issues and Challenges

The development of this technology has favored the advances noted in recent years in the field of precise positioning. It has also paved the way for a wide range of research into the evaluation of their performance and reliability, their potential use in different fields, the improvement of performance and combined systems, etc. Single-frequency GNSS receivers, which for a long time remained the only category of low-cost GNSS receivers, often limited by their level of accuracy (metric) mainly due to their single-frequency nature, have been joined in the last decade by dual-frequency GNSS receivers developed by certain manufacturers of positioning equipment. These receivers now offer possible alternatives to the relatively expensive conventional (topographic quality) or geodetic receivers and. In this study, the performance of these low-cost dual-frequency receivers was evaluated in static and real-time kinematic GNSS positioning modes. Static positioning was carried out on three points with sessions of 2 h and 4 h over three days with antenna swapping (CHC i50, Leica GS14 and Emlid Reach RS2+). Real-time observations were carried out on eleven (11) points in open, poorly open and not at all open environments, in order to assess not only performance but also receiver sensitivity in environments with a high risk of multipath. The results obtained showed an average agreement of 2 cm in planimetry between the low-cost Emlid RS2+ receiver and the Leica GS14 and CHC i50 receivers. The differences in altimetry are nevertheless greater (sometimes up to decimetres for certain points). Real-time positioning results provided an average convergence of around 1 cm on the E, N and H components with the results from the low-cost Emlid Reach RS2+ and Ublox ZED-F9P receivers and the CHC i50 receiver. Analysis of the results obtained has enabled us to highlight the various issues and challenges associated with this new generation of GNSS receivers, with a view to enhancing their appropriation and optimal integration in the professional and research worlds.

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.

Identity Study of English for Specific Purposes Teachers in the Context of Shifts in Public English Teaching Positioning

This study investigates the identity of English for Specific Purposes(ESP)teachers within the dynamic landscape of shifts in public English teaching positioning.Adopting a mixed-methods approach,qualitative and quantitative analyses were employed to explore the complexities of ESP teacher identity construction and adaptation.Qualitative findings revealed key themes including strong professional identity grounded in specialized expertise,the impact of changing educational policies and curriculum reforms,and the importance of cultural competence and intercultural communication.Quantitative analysis of survey data indicated high levels of job satisfaction among ESP teachers,with significant correlations between variables such as professional development participation,perceived efficacy in technology integration,and self-perceptions of identity as ESP educators.

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.