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 divergence 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.

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%.

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.

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.

Monte Carlo simulation based thinning and calculating method for noninvasive blood glucose sensing by near-infrared spectroscopy

Previous results show that the floating reference theory(FRT)is an effective tool to reduce the infuence of interference factors on noninvasive blood glucose sensing by near infrared spectros-copy(NIRS).It is the key to measure the floating reference point(FRP)precisely for the application of FRT.Monte Carlo(MC)simulation has been introduced to quantitatively in-vestigate the effects of positioning errors and light source drifts on measuring FRP.In this article,thinning and calculating method(TCM)is proposed to quantify the positioning error.Mean-while,the normalization process(NP)is developed to significantly reduce the error induced by light source drift.The results according to TCM show that 7 purm deviations in positioning can generate about 10.63%relative error in FRP.It is more noticeable that 1%fluctuation in light source intensity may lead to 12.21%relative errors.Gratifyingly,the proposed NP model can effectively reduce the error caused by light source drift.Therefore,the measurement system for FRPs must meet that the positioning error is less than 7 purm,and the light source drift is kept within 1%.Furthermore,an improvement for measurement system is proposed in order to take advantage of the NP model.

Detection and Analysis of Strong Ionospheric Scintillation in Equatorial Region

To detect the occurrence of ionospheric scintillation in the equatorial region,a coherent/non-coherent integration method is adopted on the accumulation of intermediate frequency(IF)signal and local code,in the process of signal acquisition based on software receiver.The processes of polynomial fitting and sixth-order Butterworth filtering are introduced to detrend the tracking results.Combining with ionospheric scintillation detection algorithm and preset thresholds,signal acquisition and tracking,scintillation detection,positioning solution are realized under the influence of strong ionospheric scintillation.Under the condition that the preset threshold of amplitude and carrier phase scintillation indices are set to 0.5 and 0.15,and the percentage of scin-tillation occurrence is 50%,respectively,PRN 12 and 31 affected by strong amplitude scintillation are detected effectively.Results show that the positioning errors in the horizontal direction are below 5m approximately.The software receiver holds performances of accurate acquisition,tracking and positioning on the strong ionospheric scintillation conditions,which can provide important basis and helpful guidance for relevant research on ionospheric scintillation,space weather and receiver design with high performance.

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.

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.

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.

Wireless positioning and path tracking for a mobile platform in greenhouse

In order to realize intelligent greenhouse,an automatic navigation method for a mobile platform based on ultra-wideband(UWB)positioning technology was proposed and validated in this study.The time difference of arrival(TDOA)approach was used to monitor and track the UWB positioning to obtain the localization information of the mobile platform working in a greenhouse.After applying polynomial fitting for positioning error correction,the system accuracy was within 5 mm.A fuzzy controller model was constructed by incorporating the lateral and heading deviations as input variables and the steering angle of front wheel as the output variable.A fuzzy rule was established based on domain knowledge,as well as the steering angle of front wheel offline query table,which was applied to alleviate the calculative load of the controller.Experimental results confirmed that the automatic navigation method proposed in this study performed satisfactorily,with a steady-state error ranging from 41 mm to 79 mm when tracking straight line,and an average error of 185 mm and an average maximum error of 532 mm when tracking polygon.In addition,the maximum error occurred at the polygonal corner which could meet the needs of driving on the narrow road in the greenhouse.The method proposed in this study provides a new systematic approach for the research of greenhouse automatic navigation.

Chord error constraint based integrated control strategy for contour error compensation

As the traditional cross-coupling control method cannot meet the requirements for tracking accuracy and contour control accuracy in large curvature positions, an integrated control strategy of cross-coupling contour error compensation based on chord error constraint, which consists of a cross-coupling controller and an improved position error compensator, is proposed. To reduce the contour error, a PI-type cross-coupling controller is designed, with its stability being analyzed by using the contour error transfer function. Moreover, a feed rate regulator based on the chord error constraint is proposed, which performs speed planning with the maximum feed rate allowed by the large curvature position as the constraint condition, so as to meet the requirements of large curvature positions for the chord error. Besides, an improved position error compensation method is further presented by combining the feed rate regulator with the position error compensator, which improves the tracking accuracy via the advance compensation of tracking error. The biaxial experimental results of non-uniform rational B-splines curves indicate that the proposed integrated control strategy can significantly improve the tracking and contour control accuracy in biaxial contour following tasks.

Localization Algorithm of Wireless Sensor Network Based on Concentric Circle Distance Calculation

Node Localization is one of the key technology in the field of wireless sensor network(WSN)that has become a challenging research topic under the lack of distance measurement.In order to solve this problem,a localization algorithm based on concentric circle distance calculation(LACCDC)is proposed.The LA-CCDC takes the beacon as the center of the concentric circle,then divides the task area into concentric circles with the k communication radius of sensor,which forms concentric rings.The node located in the k hops ring intersects the concentric circle with(k−1)r radius that forms an intersection area.This area is used to calculate the distance from the beacon to the unknown node,hyperbola is then adopted to locate the unknown node.In the application scenario with node random distribution,the simulation results show that the LA-CCDC algorithm gets the node location with low error under different node number,different beacons and different communication radius of sensor.

Adaptive Ultra-short-term Wind Power Prediction Based on Risk Assessment

A risk assessment based adaptive ultra-short-term wind power prediction(USTWPP)method is proposed in this paper.In this method,features are first extracted from the historical data,and then each wind power time series(WPTS)is split into several subsets defined by their stationary patterns.A WPTS that does not match any of the stationary patterns is then included in a subset of non-stationary patterns.Each WPTS subset is then related to a USTWPP model that is specially selected and optimized offline based on the proposed risk assessment index.For online applications,the pattern of the last short WPTS is first recognized,and the relevant prediction model is then applied for USTWPP.Experimental results confirm the efficacy of the proposed method.