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.

Uncertainties in landslide susceptibility prediction:Influence rule of different levels of errors in landslide spatial position

The accuracy of landslide susceptibility prediction(LSP)mainly depends on the precision of the landslide spatial position.However,the spatial position error of landslide survey is inevitable,resulting in considerable uncertainties in LSP modeling.To overcome this drawback,this study explores the influence of positional errors of landslide spatial position on LSP uncertainties,and then innovatively proposes a semi-supervised machine learning model to reduce the landslide spatial position error.This paper collected 16 environmental factors and 337 landslides with accurate spatial positions taking Shangyou County of China as an example.The 30e110 m error-based multilayer perceptron(MLP)and random forest(RF)models for LSP are established by randomly offsetting the original landslide by 30,50,70,90 and 110 m.The LSP uncertainties are analyzed by the LSP accuracy and distribution characteristics.Finally,a semi-supervised model is proposed to relieve the LSP uncertainties.Results show that:(1)The LSP accuracies of error-based RF/MLP models decrease with the increase of landslide position errors,and are lower than those of original data-based models;(2)70 m error-based models can still reflect the overall distribution characteristics of landslide susceptibility indices,thus original landslides with certain position errors are acceptable for LSP;(3)Semi-supervised machine learning model can efficiently reduce the landslide position errors and thus improve the LSP accuracies.

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.

Influence of positioning errors of optical shaping components for single emitter laser diode on beam shaping effects

Beam shaping is required for semiconductor lasers to achieve high optical fiber coupling efficiency in many applications.But the positioning errors on optics may reduce beam shaping effects,and then lead to low optical fiber coupling efficiency.In this work,the positioning errors models for the single emitter laser diode beam shaping system are established.Moreover,the relationships between the errors and the beam shaping effect of each shapers are analysed.Subsequently,the relationship between the errors and the optical fiber coupling efficiency is analysed.The result shows that position errors in the Z axis direction on the fast axis collimator have the greatest influence on the shaping effect,followed by the position errors in the Z axis direction on the converging lens,which should be strictly suppressed in actual operation.Besides,the position errors have a significant influence on the optical fiber coupling efficiency and need to be avoided.

Effects of laser beam divergence angle on airborne LIDAR positioning errors

The influence of laser beam divergence angle on the positioning accuracy of scanning airborne light detection and ranging （LIDAR） is analyzed and simulated. Based on the data process and positioning principle of airborne LIDAR, the errors from pulse broadening induced by laser beam di vergence angle are modeled and qualitatively analyzed for different terrain surfaces. Simulated results of positioning errors and suggestions to reduce them are given for the flat surface, the downhill of slope surface, and the uphill surface.

Laser Interferometer Based Measurement for Positioning Error Compensation in Cartesian Multi-Axis Systems

Accuracy is one of the most important key indices to evaluate multi-axis systems’ (MAS’s) characteristics and performances. The accuracy of MAS’s such as machine tools, measuring machines and robots is adversely affected by various error sources, including geometric imperfections, thermal deformations, load effects, and dynamic disturbances. The increasing demand for higher dimensional accuracy in various industrial applications has created the need to develop cost-effective methods for enhancing the overall performance of these mechanisms. Improving the accuracy of a MAS by upgrading the physical structure would lead to an exponential increase in manufacturing costs without totally eliminating geometrical deviations and thermal deformations of MAS components. Hence, the idea of reducing MAS’s error by a software-based alternative approach to provide real-time prediction and correction of geometric and thermally induced errors is considered a strategic step toward achieving the full potential of the MAS. This paper presents a structured approach designed to improve the accuracy of Cartesian MAS’s through software error compensation. Four steps are required to develop and implement this approach: (i) measurement of error components using a multidimensional laser interferometer system, (ii) tridimensional volumetric error mapping using rigid body kinematics, (iii) volumetric error prediction via an artificial neural network model, and finally (iv) implementation of the on-line error compensation. An illustrative example using a bridge type coordinate measuring machine is presented.

Cone beam computed tomography-guided differences among registration methods for lung cancer and the effects of tumor position,treatment model,and tumor size on positioning errors

Objective To explore the differences in three different registration methods of cone beam computed tomography(CBCT)-guided down-regulated intense radiation therapy for lung cancer as well as the effects of tumor location,treatment mode,and tumor size on registration.Methods This retrospective analysis included 80 lung cancer patients undergoing radiotherapy in our hospital from November 2017 to October 2019 and compared automatic bone registration,automatic grayscale(t+r)registration,and automatic grayscale(t)positioning error on the X-,Y-,and Z-axes under three types of registration methods.The patients were also grouped according to tumor position,treatment mode,and tumor size to compare positioning errors.Results On the X-,Y-,and Z-axes,automatic grayscale(t+r)and automatic grayscale(t)registration showed a better trend.Analysis of the different treatment modes showed differences in the three registration methods;however,these were not statistically significant.Analysis according to tumor sizes showed significant differences between the three registration methods(P<0.05).Analysis according to tumor positions showed differences in the X-and Y-axes that were not significant(P>0.05),while the autopsy registration in the Z-axis showed the largest difference in the mediastinal and hilar lymph nodes(P<0.05).Conclusion The treatment mode was not the main factor affecting registration error in lung cancer.Three registration methods are available for tumors in the upper and lower lungs measuring<3 cm;among these,automatic gray registration is recommended,while any gray registration method is recommended for tumors located in the mediastinal hilar site measuring<3 cm and in the upper and lower lungs≥3 cm.

A Radiotherapy Treatment Margin Formula When Systematic Positioning Errors are Relatively Small Compared to Random Positioning Errors: A First-Order Approximation

A radiotherapy treatment margin formula has been analytically derived when a standard deviation (SD) of systematic positioning errors &#425;is relatively small compared to an SD of random positioning errors &sigma;. The margin formula for 0 ≤ &#425;≤ &sigma;was calculated by linearly interpolating two boundaries at &#425;= 0 and &#425;= &sigma;, assuming that the van Herk margin approximation of k1&#425;+ k2&sigma;is valid at &#425;= &sigma;. It was shown that a margin formula for 0 ≤ &#425;≤ &sigma;may be approximated by k1&sigma;+ k2&#425;, leading to a more general form of k1 max(&#425;,&sigma;) + k2 min(&#425;,&sigma;) which is a piecewise linear approximation for any values of &#425;and &sigma;.

Far-Field Pattern Reconstruction from Positioning Errors Affected Near-Field Data Acquired via Helicoidal Scanning

In this paper, an effective technique to compensate the positioning errors in a near-field—far-field (NF-FF) transformation with helicoidal scanning for elongated antennas is presented and validated both numerically and experimentally. It relies on a nonredundant sampling representation of the voltage measured by the probe, obtained by considering the antenna as enclosed in a cylinder ended in two half-spheres. An iterative scheme is used to reconstruct the helicoidal NF data at the points fixed by the representation from the acquired irregularly spaced ones. Once the helicoidal data have been retrieved, those needed by a classical NF-FF transformation with cylindrical scanning are efficiently evaluated by using an optimal sampling interpolation algorithm. Some numerical tests, assessing the accuracy of the approach and its stability with respect to random errors affecting the data, are reported. Experimental tests performed at the Antenna Characterization Lab of the University of Salerno further confirm the validity of the proposed technique.

Calculation and correction of magnetic object positioning error caused by magnetic field gradient tensor measurement

Magnetic field gradient tensor measurement is an important technique to obtain position information of magnetic objects. When using magnetic field sensors to measure magnetic field gradient as the coefficients of tensor, field differentiation is generally approximated by field difference. As a result, magnetic objects positioning by magnetic field gradient tensor measurement always involves an inherent error caused by sensor sizes, leading to a reduction in detectable distance and detectable angle. In this paper, the inherent positioning error caused by magnetic field gradient tensor measurement is calculated and corrected by iterations based on the systematic position error distribution patterns. The results show that, the detectable distance range and the angle range of an ac magnetic object（2.44 Am^2@1 kHz） can be increased from（0.45 m, 0.75 m）,（0？, 25？） to（0.30 m, 0.80 m）,（0？,80？）, respectively.

Data-processing induced GPS-positioning error

Global Positioning System data processing is affected by many non-tectonic factors, including the common-mode errors （CME） in station-position time series. The characteristics and origins of CME are still not clear, due to uneven distribution of global GPS networks and the lack of reliable data of the position time series. In this work, data from 241 continuous GPS stations were reprocessed in a consistent way and the results were compared with those generated at Jet Propulsion Laboratory （JPL）. Improvements of residual positions were obtained for many low-quality stations, especially those located in Asia and Australia.

Geometric Error Identification of Gantry-Type CNC Machine Tool Based on Multi-Station Synchronization Laser Tracers

Laser tracers are a three-dimensional coordinate measurement system that are widely used in industrial measurement.We propose a geometric error identification method based on multi-station synchronization laser tracers to enable the rapid and high-precision measurement of geometric errors for gantry-type computer numerical control(CNC)machine tools.This method also improves on the existing measurement efficiency issues in the single-base station measurement method and multi-base station time-sharing measurement method.We consider a three-axis gantry-type CNC machine tool,and the geometric error mathematical model is derived and established based on the combination of screw theory and a topological analysis of the machine kinematic chain.The four-station laser tracers position and measurement points are realized based on the multi-point positioning principle.A self-calibration algorithm is proposed for the coordinate calibration process of a laser tracer using the Levenberg-Marquardt nonlinear least squares method,and the geometric error is solved using Taylor’s first-order linearization iteration.The experimental results show that the geometric error calculated based on this modeling method is comparable to the results from the Etalon laser tracer.For a volume of 800 mm×1000 mm×350 mm,the maximum differences of the linear,angular,and spatial position errors were 2.0μm,2.7μrad,and 12.0μm,respectively,which verifies the accuracy of the proposed algorithm.This research proposes a modeling method for the precise measurement of errors in machine tools,and the applied nature of this study also makes it relevant both to researchers and those in the industrial sector.

Using self-location to calibrate the errors of observer positions for source localization

The uncertainty of observers＇ positions can lead to significantly degrading in source localization accuracy. This pa-per proposes a method of using self-location for calibrating the positions of observer stations in source localization to reduce the errors of the observer positions and improve the accuracy of the source localization. The relative distance measurements of the two coordinative observers are used for the linear minimum mean square error （LMMSE） estimator. The results of computer si-mulations prove the feasibility and effectiveness of the proposed method. With the general estimation errors of observers＇ positions, the MSE of the source localization with self-location calibration, which is significantly lower than that without self-location calibra-tion, is approximating to the Cramer-Rao lower bound （CRLB）.

Real time remaining useful life prediction based on nonlinear Wiener based degradation processes with measurement errors

Real time remaining useful life(RUL) prediction based on condition monitoring is an essential part in condition based maintenance(CBM). In the current methods about the real time RUL prediction of the nonlinear degradation process, the measurement error is not considered and forecasting uncertainty is large. Therefore, an approximate analytical RUL distribution in a closed-form of a nonlinear Wiener based degradation process with measurement errors was proposed. The maximum likelihood estimation approach was used to estimate the unknown fixed parameters in the proposed model. When the newly observed data are available, the random parameter is updated by the Bayesian method to make the estimation adapt to the item's individual characteristic and reduce the uncertainty of the estimation. The simulation results show that considering measurement errors in the degradation process can significantly improve the accuracy of real time RUL prediction.

TDOA based assisted GNSS positioning algorithm

In order to improve the location performance of User Equipment (UE) , enhance the availability of satellites navigation systems, an assisted Global Navigation Satellite System (GNSS) positioning algorithm based on Time Difference of Arrival (TDOA) technology is proposed for only three visible satellites in this paper. Using the structure of assisted satellite position system, UE was guaranteed to acquire navigation information of the three visible satellites rapidly, and three satellite observation equation were acquired, then the arrival time difference between UE and two adjacent base stations was used as an auxiliary, and a full-rank equation was constructed to achieve positioning by least squares method. The results showed that the algorithm had good convergence ability and positioning accuracy, and the confidence of this method's positioning error, according to 3GPP request of assisted satellite navigation accuracy error within 50 m, reaches 94.56%, the average positioning accuracy was 16.8 m. The validity of this algorithm was demonstrated.

BP-LMS-based BDS-3 power system positioning method

The BeiDou-3 navigation satellite system(BDS-3)provides a full-domain high-precision positioning service for the power system to ensure safe and stable operation.However,BDS-3 power system positioning faces certain challenges,such as complex electromagnetic interference and incomplete error elimination.Herein,a back propagation neural network-improved least mean square(BP-LMS)adaptive filtering method is proposed for the BDS-3 full-domain and high-precision power system positioning,which utilizes the loss function to update the weight of the BP hidden layer,computes the pseudo compensation range,and eliminates the impact of electromagnetic interference to enhance the accuracy of power system positioning.Simulation results confirm the superior performance of BP-LMS in positioning accuracy and error elimination.Compared with LMS and normalized least mean square(NLMS),the filtering error of the proposed BP-LMS adaptive filtering method is decreased by 57.14%and 51.38%,respectively.

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.

Error Analysis on the Positioning Accuracy of a Pneumatic Vibration Isolator

A method of error analysis on the positioning accuracy of a pneumatic vibration isolator was proposed.First,the necessity of positioning accuracy was studied,in addition to the key factors associated with positioning accuracy.These analyses indicated that the positioning accuracy of the pneumatic vibration isolator was mainly attributed to the position error of the push button and the gap between the spindle and valve stem.Second,the error model of the positioning accuracy of the pneumatic vibration isolator was established through geometric simplification and geometric calculation.There are different methods used to calculate the position error of the push button for the different valves.Finally,an example analysis evaluating the impact of a specific two-position three-way valve on the positioning accuracy was given by means of error distribution.Experimental results validated the accuracy of the error model and the example analysis.This error model can be used to guide the structural parameter optimization design according to the requirements for positioning accuracy.

Understanding occupancy pattern and improving building energy efficiency through Wi-Fi based indoor positioning

Detailed visualisation and data analysis of occupancy patterns including spatial distribution and temporal variations are of great importance to delivering energy efficient and productive buildings. An experimental study comprising 24-h monitoring over 30 full days was conducted in a university library building.Occupancy profiles have been monitored and analysis has been carried out. Central to this monitoring study is the Wi-Fi based indoor positioning system based on the measured Wi-Fi devices' number and locations and data mining methods. Distinct from traditional occupancy and energy studies,more detailed informationrelated to the indoor positions and number of occupants has offered a better understanding of building user behaviour. The implication of the occupancy patterns for energy( e. g. lighting and other building services) efficiency is assessed,assisted with data from lighting sensors where needed. It is found occupancy patterns change dramatically with time. Also,the energy waste patterns have been identified through the method of data association rule mining. If the identified energy waste is removed,the total energy consumption can be reduced by 26. 1%. The indoor positioning information also has implications for optimizing space use,opening hours as well as staff deployment. The work could be extended to more rooms with diverse functions,other seasons and other types of non-domestic buildings for a more comprehensive understanding of building user behaviour and energy efficiency.

Endemic error correction model and quantitative analysis of precise point positioning

To identify the endemic error of the precise point positioning which cannot be weakened or eliminated in precise point positioning (PPP) zero-difference model, the 24 h observation data acquired from CHAN station on Oct 31st, 2010, were adopted for analyses, different correction models of various errors were discussed and their influences on traditional zero-difference model were analyzed. The results show that the errors cannot be ignored. They must be corrected with suitable models and estimated with auxiliary parameters. The influence magnitudes of all errors are defined, and the results have guiding significance to improve the accuracy of precise point positioning zero-difference model.