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.

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.

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.

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.

Application of Lightning Monitoring and Positioning Data in Investigation and Identification of Lightning Disaster in Inner Mongolia

The lightning current magnitude and other characteristics are important basic data of the lightning disaster investigation and identification. The characteristics of lightning monitoring and positioning system in Inner Mongolia were introduced and studied in the lightning accident analysis based on the lightning monitoring and positioning data of the lightning stroke accidents. The positioning error of lightning monitoring and positioning system was analyzed. The results showed that lightning current intensity and the position precision were very important data in the lightning disaster investigation. Finally, a variety of meteorological data should be applied in the lightning disaster investigation and identification.

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）.

Enhanced Fingerprinting Based Indoor Positioning Using Machine Learning

Due to the inability of the Global Positioning System(GPS)signals to penetrate through surfaces like roofs,walls,and other objects in indoor environments,numerous alternative methods for user positioning have been presented.Amongst those,the Wi-Fi fingerprinting method has gained considerable interest in Indoor Positioning Systems(IPS)as the need for lineof-sight measurements is minimal,and it achieves better efficiency in even complex indoor environments.Offline and online are the two phases of the fingerprinting method.Many researchers have highlighted the problems in the offline phase as it deals with huge datasets and validation of Fingerprints without pre-processing of data becomes a concern.Machine learning is used for the model training in the offline phase while the locations are estimated in the online phase.Many researchers have considered the concerns in the offline phase as it deals with huge datasets and validation of Fingerprints becomes an issue.Machine learning algorithms are a natural solution for winnowing through large datasets and determining the significant fragments of information for localization,creating precise models to predict an indoor location.Large training sets are a key for obtaining better results in machine learning problems.Therefore,an existing WLAN fingerprinting-based multistory building location database has been used with 21049 samples including 19938 training and 1111 testing samples.The proposed model consists of mean and median filtering as pre-processing techniques applied to the database for enhancing the accuracy by mitigating the impact of environmental dispersion and investigated machine learning algorithms(kNN,WkNN,FSkNN,and SVM)for estimating the location.The proposed SVM with median filtering algorithm gives a reduced mean positioning error of 0.7959 m and an improved efficiency of 92.84%as compared to all variants of the proposed method for 108703 m^(2) area.

Research on Positioning Error Compensation for Micro Milling Machine Tool

Micro milling has many advantages in fabricating three-dimensional(3D) structure in micrometer scale. The micro milling machine tool with high positioning accuracy is of great importance for getting micro structure with high profile precision and good surface quality. Meanwhile, the method of position error compensation is a good way to improve the accuracy of the micro milling machine tools. In this paper,a software method is adopted to compensate the positioning error and improve the positioning accuracy. According to error cancellation theory,the compensation values are generated and compensation tables are built to adjust the positioning error in the NC system based on Industrial Motion and Automation Control( IMAC). The positioning accuracy of linear motor is ± 0. 3 μm without backlash after compensation. In order to verify the effectiveness of compensation on the machining performance,concave spherical surfaces are processed on the micro milling machine tool. The experimental results show that the profile radius error of the spherical surface machined with compensation decreases more than 60%.

Kinematics and Path Following Control of an Articulated Drum Roller

Automatic navigation of an articulated drum roller, which is an articulated steering type vehicle widely used in the construction industry, is highly expected for operation cost reduction and improvement of work effi- ciency. In order to achieve the path following control, considering that its steering system is articulated steering and two frames are articulated by an active revolute joint, a kinematic model and an error dynamic state-space equation of an articulated drum roller are proposed. Besides, a state- feedback control law based on Lyapunov stability theory is also designed, which can be proved to achieve the purpose of control by the analysis of stability. What＇s more, to evaluate the performance of the proposed method, simu- lation under the MATLAB/Simulink and experiments using positioning algorithm and errors correction at the uneven construction site are performed, with initial dis- placement error （-1.5 m）, heading error （-0.11 tad） and steering angle （-0.19 rad）. Finally, simulation and exper- imental results show that the errors and steering angle can decrease gradually, and converge to zero with time. Meanwhile, the control input is not saturated. An articu- lated drum roller can lock into a desired path with the proposed method in uneven fields.

Engineering vibration monitoring by GPS:long duration records

Monitoring the performance of any structure requires real-time measurements of the change of position of critical points. Different techniques can be used for this purpose, each one offering advantages and disadvantages. The technique based on satellite positioning systems （GPS, GLONASS and the future GALILEO） seems to be very promising at least for long period structures. The GPS in particular provides sampling rates that are able to track dynamic displacements with high accuracy. Its service ability is independent of atmospheric conditions, temperature variations and visibility of the monitored object. This paper investigates the reliability and accuracy of the measurements of dual frequency GPS receivers. A linear electromagnetic motor moves an object along a given direction. The changes of position are compared witb their estimates as recorded by a GPS receiver, whose antenna is located on the reference object. The comparison is based on sufficiently long records.

The Development of Dynamic Compliant Wrist for Robots

Based on an analysis of the relative shaft-to-hole position and attiude errors, as well as of the mechanics and Kinematics in the process of automatic assembly of industrial robots, the paper studies the principle of construction of dynamic wrists. Type I-3 and Ⅱ-6 dynamic compliant wrists have been designed and made. Prblems in the production of compliant elements and the connection between compliant elements and wrists were also solved. A study on the results of tests of the function of two kinds of dynamic compliant wrists shows that the dynamic compliant wrist's compliancy function can be improved by adding metallic materials having higher longitudinal and transverse rigidity into the softer elstomer. And the design Principle is proved to be feasible and practicable. It can be expected that the use of dynamic compliant wrist will greatly lower the technical requirements of the shaft-hole assembly and the requirements in the resetting accuracy.

Wavelet Neural Network Based on NARMA-L2 Model for Prediction of Thermal Characteristics in a Feed System

Research of thermal characteristics has been a key issue in the development of high-speed feed system. Most of the work carried out thus far is based on the principle of directly mapping the thermal error against the temperature of critical machine elements irrespective of the operating conditions. But recent researches show that different sets of operating parameters generated significantly different error values even though the temperature of the machine elements generated was similar. As such, it is important to develop a generic thermal error model which is capable of evaluating the positioning error induced by different operating parameters. This paper ultimately aims at the development of a comprehensive prediction model that can predict the thermal characteristics under different operating conditions （feeding speed, load and preload of ballscrew） in a feed system. A novel wavelet neural network based on feedback linearization autoregressive moving averaging （NARMA-L2） model is introduced to predict the temperature rise of sensitive points and thermal positioning errors considering the different operating conditions as the model inputs. Particle swarm optimization（PSO） algorithm is brought in as the training method. According to ISO230-2 Positioning Accuracy Measurement and ISO230-3 Thermal Effect Evaluation standards, experiments under different operating conditions were carried out on a self-made quasi high-speed feed system experimental bench HUST-FS-001 by using Pt100 as temperature sensor, and the positioning errors were measured by Heidenhain linear grating scale. The experiment results show that the recommended method can be used to predict temperature rise of sensitive points and thermal positioning errors with good accuracy. The work described in this paper lays a solid foundation of thermal error prediction and compensation in a feed system based on varying operating conditions and machine tool characteristics.

Progress in image-guided radiotherapy for the treatment of non-small cell lung cancer

Lung cancer is one of the most common malignant tumors. It has the highest incidence and mortality rate of all cancers worldwide. Late diagnosis of nonsmall cell lung cancer(NSCLC) is very common in clinical practice, and most patients miss the chance for radical surgery. Thus, radiotherapy plays an indispensable role in the treatment of NSCLC. Radiotherapy technology has evolved from the classic two-dimensional approach to three-dimensional conformal and intensity-modulated radiotherapy. However, how to ensure delivery of an accurate dose to the tumor while minimizing the irradiation of normal tissues remains a huge challenge for radiation oncologists, especially due to the positioning error between fractions and the autonomous movement of organs. In recent years, image-guided radiotherapy(IGRT) has greatly increased the accuracy of tumor irradiation while reducing the irradiation dose delivered to healthy tissues and organs. This paper presents a brief review of the definition of IGRT and the various technologies and applications of IGRT. IGRT can help ensure accurate dosing of the target area and reduce radiation damage to the surrounding normal tissue. IGRT may increase the local control rate of tumors and reduce the incidence of radio-therapeutic complications.

Simulation of FAST EM performance for both the axial and lateral feed defocusing

Five-hundred-meter Aperture Spherical radio Telescope(FAST)is the world’s largest single dish radio telescope,which is located in Guizhou Province,in southwest China.The FAST feed cabin is supported and positioned by six steel cables.The deviation of the feed position and orientation would lead to loss in the telescope efficiency.In this paper,a series of electromagnetic(EM)simulations of the FAST facility with varying feed positions and orientation offsets was performed.The maximum gain of FAST is about 82.3 dBi and the sibelobe is–32 dB with respect to the main beam at 3 GHz.The simulation results have demonstrated that the telescope efficiency loss is more sensitive to the lateral feed deviation compared with the axial deviation.The telescope efficiency would decrease by 8.2%due to the FAST feed position deviation of 10 mm rms when the observing frequency is 3 GHz.The FAST feed deviation basically has no effect on the sidelobes and cross polarization characteristic according to the simulations.

Photoelectric detection technology of laser seeker signals

The measurement of the rolling angle of the projectile is one of the key technologies for the terminal correction projectile.To improve the resolution accuracy of the rolling angle in the laser seeker weapon system, the imaging model of the detector, calculation model of the position and the signal-to-noise ratio(SNR) model of the circuit are built to derive both the correlation between the resolution error of the rolling angle and the spot position, and the relation between the position resolution error and the SNR. Then the influence of each parameter on the SNR is analyzed at large,and the parameters of the circuit are determined. Meanwhile, the SNR and noise voltage of the circuit are calculated according to the SNR model and the decay model of the laser energy. Finally,the actual photoelectric detection circuit is built, whose SNR is measured to be up to 53 d B. It can fully meet the requirement of0.5° for the resolution error of the rolling angle, thereby realizing the analysis of critical technology for photoelectric detection of laser seeker signals.

A New Approach to Assess the Positional Accuracy of Maps Generated by GIS Overlay Operations

This paper proposes a new approach to assess the positional accuracy of maps generated by overlaying multi_scale spatial data layers with different levels of positional accuracy.The existing techniques for assessing the positional accuracy of point,line and polygon features is first examined.Then a taxonomy of graphic features on the derived maps is developed by analyzing the specific processes of overlay operations.Finally,a detailed description of the new approach is provided and the implementation of this new method in practical applications is described.

The Study of RAIM Performance by Simulation

Receiver Autonomous Integrity Monitoring （RAIM） is a software algorithm available in some GPS receivers which gives an indication if the position solution given by the GPS receiver is suitable to use. The detail algorithm of the parity space method of RAIM technique is presented. Using FDI and FDE methods, the simulations of RAIM performance have been done in three different phases independently with respect to the bias of the fault satellite. Case study of simulation results is discussed and each performance of RAIM is analyzed. According to the analysis of simulation results, the parity space method of RAIM can meet the integrity requirements for nonprecision, terminal and enroute flight phase. It also indicates that the results of performance of FDE are better than that of FDI.

An Enhanced Sensorless Control Scheme for PMSM Drives Considering Self-inductance Asymmetry

Inductance asymmetry,which is brought by inherent asymmetric parameters,manufacture tolerance,winding fault,cables with unequal lengths,etc.,of permanent-magnet synchronous machines(PMSMs)can cause current harmonics and inaccurate position estimation.This paper proposes an enhanced fundamental model based sensorless control strategy for PMSMs with asymmetric inductances.The proportional-integral-resonant current regulator is introduced to reduce the second-order harmonics of currents,but there are still negative sequence components in the estimated back-electromotive forces(EMFs),which can cause the position estimated error.Differing from conventional methods in which negative sequences are filtered out before the phase-locked loop(PLL)module,the proposed method directly applies the estimated back-EMF with negative sequences as the reference input of PLL.An improved PLL with a bi-quad filter is proposed to attenuate the arising second harmonic position error and heighten the steady-state accuracy.Then,this position error is used for asymmetric inductance identification and its result is utilized to update the observer model.Furthermore,the dynamic performance is improved by the output limitation on the bi-quad filter as well as the implementation of a fast-locking technique in the PLL.The effectiveness of the proposed scheme is verified by experimental results.