Error Characteristics Research Articles

Multi-layer parallel-perceptual-fusion spatiotemporal graph convolutional network for cross-domain, poor thermal information prediction in cloud-edge control services

Thermal error, which has spatiotemporal behavior, severely reduces machining accuracy of high-accuracy machine tools and should be controlled in real time. The deep learning is used to establish spatiotemporal thermal error model with large-sample thermal information as input. But the acquisition of large-sample thermal information is extremely difficult and costly. So, in the actual application, thermal error is predicted with poor thermal information as input, and then the robustness is weak because the cross-domain and poor spatiotemporal thermal information prediction is still a severe challenge. In this study, the transfer learning model of multi-layer parallel-perceptual-fusion spatiotemporal graph convolutional network is proposed without deepening network depth, instead, its width is expanded. Specifically, the adjacency matrix is constructed to consider the spatial information by defining the distance between each two sensors, and then the graph convolutional network is integrated into long short-term memory and gated recurrent unit to propose graph convolutional long short-term memory and graph convolutional gated recurrent unit with constructed adjacency matrix as input, respectively. The graph convolutional long short-term memory and graph convolutional gated recurrent unit are superimposed to propose the multi-layer parallel-perceptual-fusion spatiotemporal graph convolutional network. To improve the robustness, the adjacency matrix is retrained, and the transfer learning model of multi-layer parallel-perceptual-fusion spatiotemporal graph convolutional network is proposed and applied to forecast thermal error, and its prediction accuracy is 94.926%. Spatiotemporal characteristics of temperature and thermal error are fully captured by transfer learning model of graph convolutional long short-term memory and graph convolutional gated recurrent unit. Finally, the transfer learning model of multi-layer parallel-perceptual-fusion spatiotemporal graph convolutional network is embedded into thermal error control service architecture based on cloud-edge collaboration. With implementation of thermal error control service architecture based on cloud-edge collaboration, machining error of machine tools is reduced by more than 80%.

A Stepwise Calibration Method for Successive Start-Up Errors of the Three-Axis Gyroscope Based on the Characteristics of Compass Heading Alignment Error

A Stepwise Calibration Method for Successive Start-Up Errors of the Three-Axis Gyroscope Based on the Characteristics of Compass Heading Alignment Error

General characteristics of a legal error : causes of appearance , concept and legal meaning

General characteristics of a legal error : causes of appearance , concept and legal meaning

Design of broadband gradient resistive film metamaterial absorber based on genetic algorithm

In recent years, electromagnetic (EM) wave absorbing devices based on metamaterials have attracted widespread attention, due to their advantages such as broadband, easy preparation, and flexibility to tailor EM waves. Nevertheless, a review of the existing research reveals that the inherent sub-wavelength characteristics of metamaterials and metasurfaces impose certain constraints on their applications in low-frequency ranges. In order to achieve low detectability that takes into account both low-frequency and broadband absorbing performance, this work, presents a metamaterial absorber based on 5-layer gradient resistance film and dielectric composite structure, as shown in <xref ref-type="fig" rid="FigureAbstract">Fig. (a)</xref>. To begin with, we introduce the structural design of the initial element, and based on this, the transmission line theory and impedance matching principle are used to analyze the strong wave absorption conditions of the absorber element. In terms of the element structure optimization, the genetic algorithm is adopted to globally search for the optimal solution in the multi-variable domain, resulting in the rapid determination of metamaterial elements’ configurations and resistance parameters that meet the design goals. In the simulation, the wave absorption performance and mechanism of the designed absorbing element are also investigated in an in-depth manner. Simulation results show that the designed metamaterial absorber can achieve more than 90% EM wave absorption in a frequency range of 1.62–19.16 GHz (with a relative bandwidth of 168.8%) under normal incidence of linearly polarized plane waves, which effectively expands the absorption bandwidth to the L band and K band. In addition, the simulations for oblique incidence at different polarizations provide strong evidence for the device’s insensitivity to both polarization and angle. The radar cross section (RCS) curves obtained by the time domain (TD) simulation illustrate that the novel structure can achieve more than 10 dB RCS reduction in a frequency range of 1.7–20 GHz. In the device's performance verification process, a metamaterial absorber with 20 × 20 elements and dimensions of 1.566<inline-formula><tex-math id="M1">\begin{document}$ {\lambda }_{l} $\end{document}</tex-math><alternatives><graphic specific-use="online" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="7-20231781_M1.jpg"/><graphic specific-use="print" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="7-20231781_M1.png"/></alternatives></inline-formula>×1.566<inline-formula><tex-math id="M2">\begin{document}$ {\lambda }_{l} $\end{document}</tex-math><alternatives><graphic specific-use="online" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="7-20231781_M2.jpg"/><graphic specific-use="print" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="7-20231781_M2.png"/></alternatives></inline-formula>× 0.113<inline-formula><tex-math id="M3">\begin{document}$ {\lambda }_{l} $\end{document}</tex-math><alternatives><graphic specific-use="online" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="7-20231781_M3.jpg"/><graphic specific-use="print" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="7-20231781_M3.png"/></alternatives></inline-formula> is fabricated and tested by using the bow method reflectivity test system. The absorptivity curves under 5° oblique incidence of different polarizations, show that the proposed metamaterial absorber can realize more than 80% EM absorption in an entire frequency range from 2 to 18 GHz, the test results of different polarizations are basically consistent. The test results at oblique incidence (<i>θ</i> ≥ 30°) show that although the measured and simulated curves exhibit discrepancies in certain frequency bands due to human error or material dispersion characteristics, the overall experimental results are consistent with our expectations, which fully proves that the designed metamaterial absorber has potential application value in the field of low-frequency and broadband EM absorption.

Inhibition of Ironic Errors and Facilitation of Overcompensation Errors Under Pressure: An Investigation Including Perceived Weakness.

The conflicting predictions of ironic process theory and the implicit overcompensation hypothesis have been presented as a framework to explain the characteristics of errors that occur when a certain behavior is prohibited. The former predicts that instructions prohibiting a particular behavior will increase the likelihood of an outcome that should be avoided (ironic error), whereas the latter predicts that the likelihood of an outcome opposite of that to be avoided (overcompensation error) will increase. We examined how these errors, which negatively affect performance, are influenced by pressure and perceived weakness. Participants performed a tennis-stroke task, aiming to hit a ball toward a target zone while avoiding a discouraged zone. The results indicate that pressure decreases the ironic errors but increases the overcompensation errors that occur when a particular behavior is discouraged, while an increase in perceived weakness induces random errors.

Propagation and Masking Characteristics of Errors During Software Testing in Synchronous Programming

Propagation and Masking Characteristics of Errors During Software Testing in Synchronous Programming

Research on intelligent analysis device for dynamic error of electric energy

With the development of smart grids, the introduction of intermittent energy and the increase in dynamic loads have led to more and more dynamic characteristics of electricity loads in the grid. Intelligent energy meters that passed calibration under steady-state load may not necessarily meet the measurement error requirements under the excitation of dynamic load test signals, and some may even produce significant errors. At present, research on dynamic error testing of intelligent energy meters mainly focuses on establishing models of dynamic error testing signals, and the reasons for the generation of dynamic errors are still unclear. In order to analyze the sources of dynamic errors in intelligent energy meters, this article adopts a mechanism modeling method to establish a full system model of intelligent energy meters, in order to analyze the influence of model parameters of each unit on the dynamic errors of active energy, and provide important theoretical reference for further improving the dynamic error characteristics of energy meters. In addition, identifying the sources of errors has important application value for improving the algorithm of energy metering chips, optimizing the overall design of energy meters, and selecting energy meters in dynamic load scenarios for the power sector.

Mathematical model channel in the middle of the room systems 5G and 6G

For point-to-point connections in 5G systems, the E-band [1] has already been standardized, which means that the next generation of 6G will also use it. The E-band is located in the frequency range from 60 to 90 GHz. The use of the E-band allows radio systems to approach data transmission over optical fiber in terms of connection speed [1]. An increase in the frequency of the operating range automatically leads to a decrease in the coverage area of one transmitter. The size of cells in 5G and 6G systems is already micro-cells and pico-cells, which sometimes provides coverage only in a certain building. Most of the models used to calculate radio routes located inside buildings are based on the formula describing the propagation of radio waves in free space. However, the presence of walls, floors, furniture, people and other objects significantly affects the nature of radio wave propagation. The variety of conditions leads to the necessity of using some empirical models based on numerous experiments to investigate the conditions of radio wave propagation indoors. In this work, it is proposed to take two models as a basis - an experimental one [3] and an analytical one taking into account the reverberation field [2]. The combination of the analytical and experimental model allows you to estimate both the line-of-sight channel and the channel without line-of-sight; take into account the individual features of the premises, significantly reducing the error characteristic of experimental models; Due to the use of the indicator of the degree of losses on the route according to the experimental model, it is possible to more accurately take into account the nature of the premises. Thus, it is possible to combine the advantages and reduce the disadvantages of two modeling approaches.

Study of interferometric signal correction methods in ultra-precision displacement measurement

The measurement of critical dimensions in the field of integrated circuits has moved from 7 nm to 5 nm. The existing chromium atomic lithography grating has a pitch period of 4700 l mm−1 and uniformity of picometer, and the interferometric signal period based on the above grating is as small as 106.4 nm, which brings new problems and challenges to the accurate processing of the signal. This paper investigates the error characteristics of ultra-high precision grating interferometric signals, establishes a Heydemann correction mathematical model for high inscribed line density grating interferometric signals, corrects the grating interferometer signals based on the random sample consensus (RANSAC), and verifies the effectiveness of the algorithm through simulation. By comparing the repeatability and linearity of the original algorithm and the self-traceable grating interferometric displacement measurement data processed by RANSAC, the conclusion that the standard deviation of the self-traceable grating interferometer repeat measurement after RANSAC is 1.60 nm in a 10 000 nm travel is obtained, and the purpose of improving the stability and uniformity of the signal solution with the algorithm of this paper is achieved, which is important for the study of laser interferometer and grating interferometer The results show that the stability and uniformity of the signal solution can be improved by the algorithm of this paper, which is of great significance for the study of the displacement solution of laser and grating interferometers.

АНАЛИЗ ПАРАМЕТРОВ ОШИБОК ЦИФРОВЫХ КАНАЛОВ И ТРАКТОВ, ИСПОЛЬЗУЮЩИХ ПЛЕЗИОХРОННУЮ И СИНХРОННУЮ ЦИФРОВЫЕ ИЕРАРХИИ

The aim of the work is to summarize the main features of normalizing the of digital channel and path error parameters for modern telecommunications network equipment. The research methods are comparative analysis combined with the analysis of domestic standards and foreign recommendations regarding the standardization of digital channel and path error parameters. The main calculated relationship for the digital channel and path error characteristics are presented, namely long-term standards for the coefficient of seconds with errors, the coefficient of seconds with significant errors and the coefficient of blocks with background errors. Examples show the procedure for their calcu-lation and analysis. The paper specifies that the number of units to be monitored per second should be increased with the transmission rate to keep a unit size constant. The error rates of synchronous digital paths are emphasized to re-main zero for long periods of time even at Gbit/s rates, and a significant factor of error seconds corresponds to poor quality paths, so monitoring the error seconds must be performed for maintenance purposes. The findings are that long-term standards for error parameters of digital channels and paths don’t only take into account the type of digi-tal hierarchy and rate modes, but also the composition of the hypothetical reference path and its length.

ESTIMATION OF PROBABILISTIC AND STATISTICAL CHARACTERISTICS OF THE INFORMATIONAL STATE OF A COMMUNICATION CHANNEL

The methods for determining the informational state of a communication channel based on the assessment of probabilistic and statistical characteristics of errors at the channel output are presented. Adaptive information protection methods in digital communication systems, where encoder parameters change depending on the channel state, require the use of network quality control methods based on determining the statistical characteristics of the channel. It is shown that the bit error probability in the channel is constant for the presented error generation process and is independent of the method of dividing information into code blocks. The methods for assessing the statistical characteristics of the channel are based on the topological representation of error generation processes over the length of code blocks. It is demonstrated that, with a fixed code sequence length and a constant bit error probability at the output of the information channel, different error distributions correspond to sets of n-sequences. With a known number of states in the likelihood transition matrix, calculation of observation intervals for counting erroneous blocks is proposed. The presented method of researching statistical characteristics, based on the assumption of error independence, allows for the development of algorithms and procedures for assessing the state of discrete communication channels. The evaluation of potential bounds and statistical characteristics for the decoding error probability enables establishing a connection between the topological characteristics of error sequence partitioning and code parameters. The work confirms that the proposed method allows the synthesis of algorithms for determining code parameters, whose numerical values are determined based on minimizing potential decoding error probabilities.

Impact of microwave observations on the estimation of Arctic sea surface temperatures

The frequent and persistent cloud cover in the Arctic limits the extent to which sea surface temperature (SST) can be retrieved from thermal infrared (IR) satellite sensors. Passive microwave (PMW) observations provide highly complementary information to IR, enabling measurements through non-precipitating clouds, although at a coarser spatial resolution. The differences in coverage, accuracy, footprint size, spatial resolution and error characteristics between IR and PMW SSTs require a systematic assessment of how to best combine IR and PMW SST retrievals. This is provided in this study on the basis of the ESA-CCI PMW SST climate data record (CDR) and an existing IR-based gap-free SST and sea ice surface temperature CDR covering the Arctic (>58°N), where cloud cover is a serious limitation to IR sensors. An important step towards a combined IR and PMW SST CDR is to correct for systematic biases in the PMW and IR SST datasets relative to each other. The PMW SSTs show reduced biases against in situ SSTs compared to the IR SSTs, but for consistency with time periods when no Arctic PMW SSTs were available, the PMW SSTs have been adjusted to the IR SSTs in this study. This is done using a dynamic bias correction to generate a consistent combined IR and PMW Arctic SST CDR for the period 2002–2017. Including PMW SSTs reduces the standard deviations from 0.54 °C, 0.55 °C and 0.47 °C to 0.47 °C, 0.54 °C and 0.41 °C against drifters, moorings and Argo floats, respectively. The improved performance is seen in almost all regions (including those already covered by IR observations), with the largest improvement in IR data sparse regions. The average theoretical uncertainty reduces by 0.08 °C, which is in good agreement with the observed improvement in the standard deviation against drifters. The results are very promising and expected to improve even further in the future with the launch of the Copernicus Imaging Microwave Radiometer (CIMR), which will enable PMW SST retrievals with lower uncertainties and much closer to coasts and sea ice (where the largest uncertainties arise) than what is possible with previous and current PMW radiometers.

Research on temperature compensation method for photoelectric sensors

In order to make the temperature error of fiber-optic current sensor (FGB) based on polarization modulation principle meet the requirements of engineering applications, the temperature error characteristics of FGB are analyzed theoretically, and the optimized BP neural network is used for the temperature compensation of FGB, which realizes the nonlinear temperature error correction of the sensor, and compares and analyzes the experimental results with those of other types of temperature compensation algorithms. The results show that the temperature compensation results based on the neural network algorithm are better than other compensation effects. Finally, the repeatability of the FGB was experimentally verified using its full temperature experiment, and the temperature errors of the FGB in the range of 20 ℃~ 100 ℃ were less than 0.5% after the correction of the neural network algorithm.

A novel Bayesian-based INS/GNSS integrated positioning method with both adaptability and robustness in urban environments

Achieving higher accuracy positioning results in urban environments at a lower cost has been an important pursuit in areas such as autonomous driving and intelligent transportation. Low-cost Inertial Navigation System and Global Navigation Satellite System (INS/GNSS) integrated navigation systems have been an important means of fulfilling the above quest due to the complementary error characteristics between INS and GNSS. The complex urban driving environment requires the system sufficiently adaptive to keep up with the time-varying measurement noise and sufficiently robust to cope with measurement outliers and prior uncertainties. However, many efforts lack a balance between adaptability and robustness. In this paper, a novel positioning method with both adaptability and robustness is proposed by coupling the Mahalanobis distance method, the Variational Bayesian method and the student’s t-distribution in one process (M-VBt method). This method is robust against non-Gaussian noise and priori uncertainties, plus adaptive against measurement noise uncertainty and time-varying noise. The field test results show that the M-VBt method (especially the Mahalanobis distance part) has significantly improved the system performance in the complex urban driving environment.

A Wind Power Scenario Generation Method Based on Copula Functions and Forecast Errors

The scenario of renewable energy generation significantly affects the probabilistic distribution system analysis. To reflect the probabilistic characteristics of actual data, this paper proposed a scenario generation method that can reflect the spatiotemporal characteristics of wind power generation and the probabilistic characteristics of forecast errors. The scenario generation method consists of a process of sampling random numbers and a process of inverse sampling using the cumulative distribution function. In sampling random numbers, random numbers that mimic the spatiotemporal correlation of power generation were generated using the copula function. Furthermore, the cumulative distribution functions of forecast errors according to power generation bins were used, thereby reflecting the probabilistic characteristics of forecast errors. The wind power generation scenarios in Jeju Island, generated by the proposed method, were analyzed through various indices that can assess accuracy. As a result, it was confirmed that by using the proposed scenario generation method, scenarios similar to actual data can be generated, which in turn allows for preparation of situations with a high probability of occurrence within the distribution system.

Short-term forecast large-scale error characteristics and their relationship with precipitation forecast skill under two rainfall regimes

Although precipitation forecast skill has improved significantly in recent decades, both location and intensity of precipitation forecast based on kilometric-scale numerical weather prediction (NWP) models still contain errors. The importance of large-scale error in NWP has been recognized, but characteristics of large-scale error under different rainfall regimes and the influence of large-scale error on precipitation forecast skill remain unclear. In this regard, we focused on the Yangtze-Huaihe River Basin (YHRB) and used an operational forecast dataset covering the summer seasons of 2018 and 2019 obtained from the Anhui Meteorology Observatory to investigate large-scale error characteristics and their relationship with precipitation errors under two rainfall regimes.Large-scale error characteristics were measured by root-mean-square errors (RMSE), relative RMSE (RRMSE), and large-scale spatial pattern correlation (LSCC). The large-scale RMSEs were highly correlated with the rainfall intensity and area, while the large-scale RRMSE and LSCC can be used to describe precipitation forecast skill for rainfall events under the two rainfall regimes. In general, the precipitation forecast for strongly forced rainfall events performed better than that for weakly forced rainfall events. Under strong forcing conditions, the majority of rainfall events were concentrated in the intervals of smaller precipitation errors with smaller RRMSEs and higher LSCCs, and the precipitation forecast skill was weakly related to the large-scale RRMSE, LSCC and the initial large-scale variance contribution (LVC). Under weak forcing conditions, most of the rainfall events had a larger precipitation error and the frequency of location error was higher than that of intensity error. The low precipitation forecast skill and large forecast uncertainties for weakly forced rainfall events were strongly related to the large RRMSEs and low LSCCs in the geopotential height in the middle-upper troposphere and meridional wind component (V) in the lower troposphere. In particular, a strong negative correlation was found between the initial LVC and the large-scale RRMSE under weak forcing. This suggests that large-scale information could play a more important role in precipitation forecast for weakly forced rainfall events, and could potentially be used to indicate the magnitude of large-scale forecast errors in short-term forecasts under weak forcing conditions.

Statistical investigations of profile error impact on flow and performance of a low-pressure turbine cascade

Profile error impacts on turbomachinery flow and blade performance have been attracting widespread attention. In the study, the characteristics of profile error of about one thousand real low-pressure turbine blades are extracted. Sensitivities of total pressure loss coefficient (ζ), outflow angle (β), and Zweifel lift coefficient (zw) of the blade to the basis modes of profile error are calculated. Flow solutions of the blades considering specified basis modes with high sensitivities illustrate that profile error contributes much to the variations of transition onset and flow acceleration on the suction side and flow mixing intensity in the wake. Uncertainty quantification of performance changes is then implemented by the method of moment (MM) using second-order sensitivities. With only 5% computational cost of that by Monte Carlo simulation (MCS), the MM-based statistical results are close to MCS ones with maximum relative error not exceeding 1.07%. The statistical results reveal that the variations of both β and zw are linearly dependent, whereas the variation of ζ is nonlinearly dependent on profile error. As the variation range of profile error increases, the standard deviation and skewness increase, indicating that the performance is more dispersive and the nonlinear dependence of ζ on profile error is intensified. Finally, the MCS flow fields are analyzed. Statistical shear stress near the leading edge and transition onset, statistical boundary layer momentum thickness near transition onset, statistical intermittency near transition onset, and statistical entropy in the wake are more considerable. The impact mechanisms of profile error on turbine flow and performance changes are demonstrated.

Characteristics of student errors in solving geometric proof problems based on Newman's theory

This study aims to determine the characteristics of student errors in solving geometry proof based on Newman's Theory. The research method used is a qualitative research method with a phenomenographic approach. This research was conducted to prevent students from repeating mistakes in advanced geometry courses. The types of errors based on Newman's Theory used in this study are: (1) reading errors in the representation of mathematical symbols; (2) comprehension errors of the proof problem; (3) transformation errors of the proof problem; (4) process skills errors of the proof problem; and (5) encoding errors. The subjects of this study were 15 students, and the instruments used were interview guidelines and documentation. The results of this study are reading errors in the representation of mathematical symbols with an average of 15.81%, with error characteristics that students do not write geometry symbols according to the rules. Comprehension errors of the proof problem with an average of 4.78%. Transformation errors of the proof problem with an average of 26.84%. Process skill errors of proof problems with an average of 29.04%. Encoding errors with an average of 23.53%.

Ellipsoidal estimation of parameters of rotational and translational motion of a non-cooperative space vehicle from visual information


 The use of near-Earth space is currently complicated by the presence of space debris objects in Earthʼs orbit, which include spent stages of launch vehicles, inoperative spacecraft, and other large and small objects associated with human activity in space. One of the elements of solving the problem of space debris is the docking and capture of an uncontrolled non-cooperative space object or spacecraft by a so-called on-orbit servicing spacecraft to carry out further actions to repair it, refuel or change its orbit. The situation is complicated by the fact that, under the influence of various factors, uncontrolled space objects are in a state of rotation. The parameters of the orbital motion of such objects are known quite accurately from measurements from the Earth. To carry out safe approach and docking, knowledge of the parameters of rotational motion, as well as the parameters of relative motion, is also required. The most general case of motion of a non-cooperative tumbling spacecraft located in an elliptical orbit is considered. It is assumed that the three-dimensional graphic model of such spacecraft is known. The servicing spacecraft (SSC) is equipped with a mono camera that takes pictures of the non-cooperative spacecraft (NSC). Based on a comparison of the characteristic features of photographs and images obtained using the graphical model, the computer vision system (CVS) determines the distance vector to the so-called graphical coordinate system, rigidly fixed on the NSC and the quaternion of its relative attitude. The specific type of CVS is not considered. It is assumed that the SSC carries out some maneuvers near the satellite. All parameters of the SSC angular motion are assumed to be known. This work considers the most general case of the relative motion of SSC and NSC. Using quaternion calculus, all basic kinematic and dynamic equations are obtained. The measured parameters are not enough to ensure safe rendezvous and docking with the NSC. The stochastic characteristics of errors of the CVS measurement are not assumed to be known and, accordingly, are not used. Only their maximum values are specified for them. We consider the use of new dynamic set-membership filter using ellipsoids to solve the problem of determining the parameters of the relative motion of the NSC which is in free uncontrolled motion. The filter can be implemented under conditions of the limited computational capability available on onboard processors. The relative motion parameters include the distance vector between the centers of mass (c.m.) of the NSC and the SSC, the relative velocity vector, the quaternion of the orientation of the main axes of inertia of the satellite relative to the inertial coordinate system, the ratio of the moments of inertia of the satellite, the vector of the position of the NSC c.m. in the graphical coordinate system. The properties of the proposed algorithm are demonstrated using numerical simulation. The results obtained are expected to be used in the development, creation and testing of a navigation system for the rendezvous and docking of the SSC, developed by a group of Ukrainian space industry enterprises under the leadership of the LLC «Kurs-orbital» (https://kursorbital.com/).

Advancing airborne Doppler lidar wind profiling in turbulent boundary layer flow – an LES-based optimization of traditional scanning-beam versus novel fixed-beam measurement systems

Abstract. There is a need for improved wind measurements inside the planetary boundary layer (PBL), including the capability to sample turbulent flow. Airborne Doppler lidar (ADL) provides unique capabilities for spatially resolved and targeted wind measurements in the PBL. However, ADL wind profiling in the PBL is challenging, as turbulence violates the flow homogeneity assumption used in wind profile retrieval and thereby introduces error in the retrieved wind profiles. As turbulence is a dominant source of error it is necessary to investigate and optimize ADL wind profiling capabilities in turbulent PBL flow. This study investigates the potential of a novel multiple-fixed-beam ADL system design to provide improved wind information in turbulent PBL flow compared to traditional single-scanning-beam ADL systems. To achieve this, an LES-based (LES: large eddy simulation) airborne Doppler lidar simulator presented in Gasch et al. (2020) is employed and extended in this study. Results show that a multiple-fixed-beam system with settings comparable to those of commonly used single-scanning-beam systems offers distinct advantages. Advantages include overall reduced wind profile retrieval error due to turbulence and improved spatial representation alongside higher wind profile availability. The study also offers insight into the dependence of the retrieval error on system setup parameters and retrieval parameters for both fixed-beam and scanning-beam systems. When using a fixed-beam system, an order of magnitude higher wind profile resolution appears possible compared to traditional scanning systems at comparable retrieval accuracy. Thus, using multiple-fixed-beam systems opens the door to better sampling of turbulent PBL flow. Overall, the simulator provides a cost-effective tool to investigate and optimize wind profile error characteristics due to turbulence and to optimize system setup and retrieval strategies for ADL wind profiling in turbulent flow.