Accurate Distance Estimation Research Articles

동적 장면에서의 차간 거리 보정을 위한 광학 흐름 기반 차량 자세 추정

Stable inter-vehicle distance estimations are required in dynamic scenes as they are essential for advanced driver-assistance systems (ADAS) and high-level autonomous driving. However, instantaneous changes in the pose of a vehicle in the dynamic scene may cause errors in the estimation of the inter-vehicle distance, which can lead to traffic accidents and also affect obstacle avoidance performance. In this study, the optical flow motion vector is histogrammed to extract a representative value, and the correlation between the representative value and inertial measurement unit (IMU) data is confirmed to verify the accuracy in vehicle pose estimation based on the optical flow motion vector. Then, an algorithm is proposed for improving the vehicle distance estimation accuracy in real-time ground compensation. Experiments have been conducted using an autonomous vehicle on the road with speed bumps, and the data from the IMU sensor installed in the vehicle and LiDAR detection results are used as the ground-truth data. The pose estimation with the proposed method shows an average error of 0.0029 rad, and the distance correction error can be reduced from 2.73 m (14.8%) to 0.86 m (4.6%), demonstrating the possibility of accurate real-time inter-vehicle distance correction.

Supervised Object-Specific Distance Estimation from Monocular Images for Autonomous Driving.

Accurate distance estimation is a requirement for advanced driver assistance systems (ADAS) to provide drivers with safety-related functions such as adaptive cruise control and collision avoidance. Radars and lidars can be used for providing distance information; however, they are either expensive or provide poor object information compared to image sensors. In this study, we propose a lightweight convolutional deep learning model that can extract object-specific distance information from monocular images. We explore a variety of training and five structural settings of the model and conduct various tests on the KITTI dataset for evaluating seven different road agents, namely, person, bicycle, car, motorcycle, bus, train, and truck. Additionally, in all experiments, a comparison with the Monodepth2 model is carried out. Experimental results show that the proposed model outperforms Monodepth2 by 15% in terms of the average weighted mean absolute error (MAE).

Assessment of camera focal length influence on canopy reconstruction quality

Unoccupied aerial vehicles (UAV) with RGB-cameras are affordable and versatile devices for the generation of a series of remote sensing products that can be used for forest inventory tasks, such as creating high-resolution orthomosaics and canopy height models. The latter may serve purposes including tree species identification, forest damage assessments, canopy height or timber stock assessments. Besides flight and image acquisition parameters such as image overlap, flight height, and weather conditions, the focal length, which determines the opening angle of the camera lens, is a parameter that influences the reconstruction quality. Despite its importance, the effect of focal length on the quality of 3D reconstructions of forests has received little attention in the literature. Shorter focal lengths result in more accurate distance estimates in the nadir direction since small angular errors lead to large positional errors in narrow opening angles. In this study, 3D reconstructions of four UAV-acquisitions with different focal lengths (21, 35, 50, and 85 mm) on a 1 ha mature mixed forest plot were compared to reference point clouds derived from high quality Terrestrial Laser Scans. Shorter focal lengths (21 and 35 mm) led to a higher agreement with the TLS scans and thus better reconstruction quality, while at 50 mm, quality losses were observed, and at 85 mm, the quality was considerably worse. F1-scores calculated from a voxel representation of the point clouds amounted to 0.254 with 35 mm and 0.201 with 85 mm. The precision with 21 mm focal length was 0.466 and 0.302 with 85 mm. We thus recommend a focal length no longer than 35 mm during UAV Structure from Motion (SfM) data acquisition for forest management practices.

Актуальные вопросы изучения реверса движителей

Object and purpose of research. This paper discusses crash-stop of ship propellers. The puspose of the study was to investigate a number of relevant challenges in this process, i.e. to refine the methods of crash-stop distance calculation, to update the scenarios for which crash-stop strength of propeller blades has to be verified, as well as to determine operational parameters and algorithms for automatic control systems of electric power plants in crash-stop conditions. Subject matter and methods. The study was based on the results of quasi-crash-stop model tests, as well as on previous publications about crash-stop maneuvers of ships and operations of their propulsion systems in these conditions. Main results. To obtain more accurate crash-stop distance estimates, it was suggested to use an alternative, bollard-pull system of propeller-hull interaction coefficients for crash-stop conditions. It was also suggested to perform crash-stop strength check of propellers not only for the scenarios with maximum hydrodynamic load, but also for the moment of propeller rotation direction reversal because it might be accompanied by considerable inertial loads. It is shown that model testing is not helpful in determination of operational parameters and automatic control system algorithms for electric power plants because shaft lines cannot be simulated correctly. These parameters can be obtained through calculations, but this will require more refined expressions for shaft line friction moments. Conclusion. The actual problems of ship reverse propulsion theory is presented in the paper. The possible approaches to their solution are proposed.

Underground Metal Pipeline Localization Using Low-Cost Wireless Magnetic Sensors Mounted on an Excavator

To minimize the excavation damage of underground pipelines, in this article, we propose to provide real-time feedback to operators by monitoring the distance information from the underground pipeline. Despite multiple efforts to locate underground ferromagnetic pipelines using the magnetic anomaly detection, it has not been implemented in real-time excavation operations due to low signal-to-noise ratios, unknown external magnetic interference (EMI), and high computational power. To address these limitations, we propose an approach to locating a custom-designed wireless sensor system on the excavator bucket to increase accuracy of real-time distance estimation with efficient EMI cancelation. We present the system using a 14:1 lab-scaled excavator and six sizes of ferromagnetic pipes. To create a distance estimation model of each pipe, we measure the magnetic anomaly caused by ferromagnetic pipes from eight distances (from 5 to 75 mm, spaced 10 mm apart). The wireless system with the localization algorithm successfully estimates the distance between the sensor and the pipe with a less than 4.38 ± 1.62 mm error overall. This pilot study shows that the proposed system with the localization algorithm is able to accurately locate pipes. This will lay the foundation for providing accurate spatial information, and ultimately prevent critical excavation/drilling damage at construction sites.

Detection and Separation of Close Flaws in Coarse-Grained Materials Using Ultrasonic Image Deconvolution

Ultrasonic inspection of coarse-grained steels is a common challenge in various industrial fields. This task is often difficult because of acoustic scattering that creates structural noise in the ultrasonic signals and images. Therefore, inspections usually use low-frequency probes, which achieve poor resolution with standard delay-and-sum (DAS) imaging techniques, such as the well-known total focusing method (TFM). The purpose of this paper is to evaluate the performance of a super-resolution ultrasonic imaging technique presented by Laroche et al. (IEEE Trans Comput Imaging 7:935–947, 2021) for the inspection of industrial coarse-grained materials. An image deconvolution problem (with spatially varying blur) is formulated, relying on a forward model that links the TFM image to the acoustic reflectivity map. The experiments consider an austenitic-ferritic stainless steel sample insonified using array probes at 3 MHz and 5 MHz placed in contact. The goal is to resolve two close reflectors corresponding to side-drilled holes (SDH) with diameter 0.4 mm spaced by 0.4 mm edge-to-edge and positioned at different depths (10, 20, 30, 40 mm). This configuration corresponds to a critical case where the distance between the two reflectors is much lower than the Rayleigh distance, that is the resolution limit of a DAS imaging system. These are typical cases where DAS images obtained from low-frequency inspections critically lack resolution, but where higher frequency probes cannot be used in practice, because a too week signal-to-noise ratio would affect the detection capability. As predicted by the Rayleigh criterion, TFM is not able to separate the reflectors. The proposed image reconstruction method successfully resolves the majority of the reflectors with a rather accurate distance estimation. In the context of coarse-grained structure inspection, subwavelength reflectors distant from each other by two times less than the resolution limit given by the Rayleigh criterion have been successfully detected and separated. This approach hence enables the use of low-frequency probes, in order to improve the signal-to-noise ratio, while keeping high resolution capability which can be particularly interesting for industrial applications. In particular, the proposed approach shows promising results for the sizing of a real crack in an industrial sample.

A distance protection approach for untransposed parallel transmission lines in case of phase-phase-ground inter-circuit faults

Distance relays’ phase and ground elements at either circuits of the parallel transmission lines undergo miscalculation of the correct fault impedance when facing inter-circuit faults. This paper proposes a distance protection approach for untransposed parallel lines in case of phase-phase-ground inter-circuit faults, which can also be served as the fault locator as its auxiliary function. It is a demanding task compared to that of transposed lines due to the mutual coupling between all six phases of the line circuits. Considering the intended faults with the fault arc and ground resistances, the line circuit model is analyzed on a time-domain basis, resulting an equation that is mathematically a linear combination of designated functions. This would provide a great chance of establishing an adaptive linear combiner with windowed inputs (W-Adaline) in consistence with the equation derived. The W-Adaline with its simple structure is capable of giving a fast and accurate estimation of the fault distance in an online manner, which is exploited for both the line distance protection and fault location. The proposed approach is readily implementable and is independent of the system configuration. It operates robustly in high-ground resistance, variable fault arc resistance and noisy conditions. Through extensive simulation studies in PSCAD/EMTDC, performance of the proposed approach would be investigated and verified in a variety of fault and system loading conditions.

Augmented Cooper test: Biomechanical contributions to endurance performance.

Running mechanics are modifiable with training and adopting an economical running technique can improve running economy and hence performance. While field measurement of running economy is cumbersome, running mechanics can be assessed accurately and conveniently using wearable inertial measurement units (IMUs). In this work, we extended this wearables-based approach to the Cooper test, by assessing the relative contribution of running biomechanics to the endurance performance. Furthermore, we explored different methods of estimating the distance covered in the Cooper test using a wearable global navigation satellite system (GNSS) receiver. Thirty-three runners (18 highly trained and 15 recreational) performed an incremental laboratory treadmill test to measure their maximum aerobic speed (MAS) and speed at the second ventilatory threshold (sVT2). They completed a 12-minute Cooper running test with foot-worm IMUs and a chest-worn GNSS-IMU on a running track 1–2 weeks later. Using the GNSS receiver, an accurate estimation of the 12-minute distance was obtained (accuracy of 16.5 m and precision of 1.1%). Using this distance, we showed a reliable estimation [R2 > 0.9, RMSE ϵ (0.07, 0.25) km/h] of the MAS and sVT2. Biomechanical metrics were extracted using validated algorithm and their association with endurance performance was estimated. Additionally, the high-/low-performance runners were compared using pairwise statistical testing. All performance variables, MAS, sVT2, and average speed during Cooper test, were predicted with an acceptable error (R2 ≥ 0.65, RMSE ≤ 1.80 kmh−1) using only the biomechanical metrics. The most relevant metrics were used to develop a biomechanical profile representing the running technique and its temporal evolution with acute fatigue, identifying different profiles for runners with highest and lowest endurance performance. This profile could potentially be used in standardized functional capacity measurements to improve personalization of training and rehabilitation programs.

Testing the homogeneity of type Ia Supernovae in near-infrared for accurate distance estimations

Since the discovery of the accelerating expansion of the Universe more than two decades ago, Type Ia Supernovae (SNe Ia) have been extensively used as standardisable candles in the optical. However, SNe Ia have shown to be more homogeneous in the near-infrared (NIR), where the effect of dust extinction is also attenuated. In this work, we explore the possibility of using a low number of NIR observations for accurate distance estimations, given the homogeneity at these wavelengths. We found that one epoch in J and/or H band, plus good gr-band coverage, gives an accurate estimation of peak magnitudes in the J (Jmax) and H (Hmax) bands. The use of a single NIR epoch only introduces an additional scatter of ∼0.05 mag for epochs around the time of B-band peak magnitude (Tmax). We also tested the effect of optical cadence and signal-to-noise ratio (S/N) in the estimation of Tmax and its uncertainty propagation to the NIR peak magnitudes. Both cadence and S/N have a similar contribution, where we constrained the introduced scatter of each to < 0.02 mag in Jmax and < 0.01 in Hmax. However, these effects are expected to be negligible, provided the data quality is comparable to that obtained for observations of nearby SNe (z ≲ 0.1). The effect of S/N in the NIR was tested as well. For SNe Ia at 0.08 < z ≲ 0.1, NIR observations with better S/N than that found in the CSP sample is necessary to constrain the introduced scatter to a minimum (≲0.05 mag). These results provide confidence for our FLOWS project that is aimed at using SNe Ia with public ZTF optical light curves and few NIR epochs to map out the peculiar velocity field of the local Universe. This will allow us to determine the distribution of dark matter in our own supercluster, Laniakea, and to test the standard cosmological model by measuring the growth rate of structures, parameterised by fD, and the Hubble-Lemaître constant, H0.

An Accurate Near‐Field Distance Estimation Differential Algorithm

The triangular geometry is the basis of near field array accurate distance estimation algorithms. The Fisher expression of traditional distance estimation is derived by utilizing the Taylor series. To improve convergence rate and estimation accuracy, a novel iterative distance estimation algorithm is proposed with differential equations based on the triangular geometry. Firstly, its convergence performance is analysed in detail. Secondly, the selection of the initial value and the number of iterations are respectively studied. Thirdly, compared with the traditional estimation algorithms by utilizing the Fisher approximation, the proposed algorithm has a higher convergence rate and estimation accuracy. Moreover, its pseudocode is presented. Finally, the experiment results and performance analysis are provided to verify the effectiveness of the proposed algorithm.

Single-ended multi-method phasor-based approach for optimized fault location on transmission lines

This paper presents the development of a transmission line multi-method single-ended phasor-based fault location (SEPHFL) approach in a real digital fault recorder (DFR). Unlike classical solutions, it processes the outputs taken from different SEPHFL methods, allowing the calculation of accurate punctual fault distances, such as traditional approaches do, and reliable fault search fields, which is innovative from the point of view of SEPHFL applications. To properly select the algorithms to be used in the proposed solution, a Real-Time Digital Simulator (RTDS) is used to carry out massive hardware-in-the-loop fault simulations on 500 kV and 230 kV test power systems. Firstly, the DFR hardware capabilities are analyzed to identify SEPHFL methods with compatible requirements, and then, eight SEPHFL methods are chosen to be embedded in the DFR. Parametric studies in a fully controllable 500 kV test power network are carried out, varying the system operation conditions and fault features. Based on the obtained results, three techniques are selected to compose the proposed multi-method SEPHFL solution, which is finally implemented in the DFR and validated through tests in a realistic IEEE benchmark 230 kV/60 Hz system. The obtained results show the proposed approach is able to calculate accurate punctual fault distance estimations, with the advantage of providing a reliable search field, which can be used to optimize line inspection procedures, mainly when there is uncertainty on the punctual fault location estimations provided by traditional technologies.

Real-Time Underground Plastic Pipeline Water Leakage Detection and Monitoring System

The leaking of the water pipeline increasingly influences the quality of life and threatens the water supplier in developing countries. Proper method is required to effectively detecting the source for replacement to reduce the loses. Therefore, a water leakage detection with monitoring system is developed to detecting the precise leaking location of a buried plastic pipeline. The real-time pressure data obtained from the pressurized pipeline are transferred to the monitoring system with GUI (graphical User Interface), developed using LabVIEW software. In the experimental execution, a leaking pipeline is designed. Then, few pressure sensors are installed on the pipeline as a primary segment for the detection process. To prevent a false non-leak alarm and malfunction of the pressure sensors, the pressure threshold value and malfunction alarm is set using LabVIEW. Cross-correlation method is implemented that increase the accuracy of the leaking distance estimation. The processing and control unit in this article are manipulated using LabVIEW software and NI myRIO-1900 respectively.

Mobile device-based Bluetooth Low Energy Database for range estimation in indoor environments.

The demand to enhance distance estimation and location accuracy in a variety of Non-Line-of-Sight (NLOS) indoor environments has boosted investigation into infrastructure-less ranging and collaborative positioning approaches. Unfortunately, capturing the required measurements to support such systems is tedious and time-consuming, as it requires simultaneous measurements using multiple mobile devices, and no such database are available in literature. This article presents a Bluetooth Low Energy (BLE) database, including Received-Signal-Strength (RSS) and Ground-Truth (GT) positions, for indoor positioning and ranging applications, using mobile devices as transmitters and receivers. The database is composed of three subsets: one devoted to the calibration in an indoor scenario; one for ranging and collaborative positioning under Non-Line-of-Sight conditions; and one for ranging and collaborative positioning in real office conditions. As a validation of the dataset, a baseline analysis for data visualization, data filtering and collaborative distance estimation applying a path-loss based on the Levenberg-Marquardt Least Squares Trilateration method are included.

Distance relaying of Untransposed parallel transmission lines in case of phase-phase inter-circuit faults

• Untransposed parallel transmission lines are targeted for distance relaying. • Phase-phase inter-circuit faults are addressed in the distance relaying. • The ADALINE is developed for an accurate online estimation of the fault distance. • The proposed approach achieves fast fault tripping and an accurate fault location. • It tolerates noisy conditions and properly handles variable fault arc resistance. Distance relays at both circuits of the parallel transmission lines would miscalculate the right fault impedance during inter-circuit faults. This paper deals with the distance relaying of untransposed parallel lines in case of phase-phase inter-circuit faults. It is a challenging case compared to that of transposed lines due to the mutual coupling between all six phases of the line circuits. Considering a phase-phase inter-circuit fault with the fault arc resistance, the line circuit model is analyzed on a time-domain basis. Consequently, a mathematical equation with a linear combination of specified functions is derived. This provides a splendid opportunity to establish an ADAptive LINEar combiner (ADALINE) consistent with the equation derived. The ADALINE with its simple structure gives a fast and accurate online estimation of the fault distance, employing single-end measurements during the inter-circuit faults. Hence, achieving the fault location along with the distance protection is also made possible. The proposed approach is readily implementable without being dependent on the system configuration. It operates robustly against the dynamic fault arc resistance and tolerates the noise contamination. The simulations in PSCAD/EMTDC provide extensive sensitivity analyses validating the proposed approach performance, in respect of both the accuracy and swiftness, for various fault conditions.

Three-dimensional Shape Explains Star Formation Mystery of California and Orion A

The new Gaia data release (EDR3) with improved astrometry has opened a new era in studying our Milky Way in fine detail. We use Gaia EDR3 astrometry together with 2MASS and WISE photometry to study two of the most massive molecular clouds in the solar vicinity: Orion A and California. Despite having remarkable similarities in the plane of the sky in terms of shape, size, and extinction, California has an order of magnitude lower star formation efficiency. We use our state-of-the-art dust mapping technique to derive the detailed three-dimensional (3D) structure of the two clouds, taking into account both distance and extinction uncertainties, and a full 3D spatial correlation between neighboring points. We discover that, despite the apparent filamentary structure in the plane of the sky, California is a flat 120 pc-long sheet extending from 410 to 530 pc. We show that not only Orion A and California differ substantially in their 3D shapes, but also Orion A has considerably higher density substructures in 3D than California. This result presents a compelling reason why the two clouds have different star formation activities. We also demonstrate how the viewing angle of California can substantially change the cloud’s position in the Kennicutt–Schmidt relation. This underlines the importance of 3D information in interpreting star formation relations and challenges studies that rely solely on the column density thresholds to determine star formation activities in molecular clouds. Finally, we provide accurate distance estimates to multiple lines of sight toward various parts of the two clouds.

Lensfree auto-focusing imaging using nuclear norm of gradient

Auto-focusing is an essential task for lensfree holographic microscopy, where the optimal focal plane needs to be determined from refocused Z-stack data. In this work, we propose a new auto-focusing criterion, nuclear norm of gradient (NoG), to enhance the accuracy of distance estimation for lensfree imaging. The NoG metric is composed of three parts: shape acquisition, gradient calculation, and gradient fusion. The experiment is conducted in a multi-height on-chip system, where 20 sets of samples including resolution target, stained slide, and label-free cell are employed. The experimental results demonstrate that the accuracy of the NoG metric on auto-focusing is superior to state-of-the-art metrics. Also, the experiment of a multi-layer target proves that the NoG metric has a good optical-sectioning capability. We believe that the NoG metric is expected to be a useful tool for lensfree on-chip microscopes.

A new protection scheme for PV-wind based DC-ring microgrid by using modified multifractal detrended fluctuation analysis

This paper presents fault detection, classification, and location for a PV-Wind-based DC ring microgrid in the MATLAB/SIMULINK platform. Initially, DC fault signals are collected from local measurements to examine the outcomes of the proposed system. Accurate detection is carried out for all faults, (i.e., cable and arc faults) under two cases of fault resistance and distance variation, with the assistance of primary and secondary detection techniques, i.e. second-order differential current derivative left( {frac{{d^{2} I_{3} }}{{dt^{2} }}} right) and sliding mode window-based Pearson’s correlation coefficient. For fault classification a novel approach using modified multifractal detrended fluctuation analysis (M-MFDFA) is presented. The advantage of this method is its ability to estimate the local trends of any order polynomial function with the help of polynomial and trigonometric functions. It also doesn’t require any signal processing algorithm for decomposition resulting and this results in a reduction of computational burden. The detected fault signals are directly passed through the M-MFDFA classifier for fault type classification. To enhance the performance of the proposed classifier, statistical data is obtained from the M-MFDFA feature vectors, and the obtained data is plotted in 2-D and 3-D scatter plots for better visualization. Accurate fault distance estimation is carried out for all types of faults in the DC ring bus microgrid with the assistance of recursive least squares with a forgetting factor (FF-RLS). To verify the performance and superiority of the proposed classifier, it is compared with existing classifiers in terms of features, classification accuracy (CA), and relative computational time (RCT).

Classification of Respiratory States Using Spectrogram with Convolutional Neural Network

This paper proposes an approach to the classification of respiration states based on a neural network model by visualizing respiratory signals using a spectrogram. The analysis and processing of human biosignals are still considered some of the most crucial and fundamental research areas in both signal processing and medical applications. Recently, learning-based algorithms in signal and image processing for medical applications have shown significant improvement from both quantitative and qualitative perspectives. Human respiration is still considered an important factor for diagnosis, and it plays a key role in preventing fatal diseases in practice. This paper chiefly deals with a contactless-based approach for the acquisition of respiration data using an ultra-wideband (UWB) radar sensor because it is simple and easy for use in an experimental setup and shows high accuracy in distance estimation. This paper proposes the classification of respiratory states by using a feature visualization scheme, a spectrogram, and a neural network model. The proposed method shows competitive and promising results in the classification of respiratory states. The experimental results also show that the method provides better accuracy (precision: 0.86 and specificity: 0.90) than conventional methods that use expensive equipment for respiration measurement.

A large catalogue of molecular clouds in the Southern sky

ABSTRACT We present a large catalogue of molecular clouds with accurate distance estimates in the Southern sky. Based on the three-dimensional dust extinction map and the best-fitting extinction and distance information of over 17 million stars presented in Guo et al. (2021, ApJ, 906, 47), we have identified 250 dust/molecular clouds in the Southern sky using a hierarchical structure identification algorithm. Amongst these are 71 clouds located at high Galactic latitudes (b < −10°). We have estimated the distances to the clouds by fitting the extinction versus distance profiles of the lines of sight overlapping with the clouds, using a simple Gaussian dust distribution model. The typical uncertainties of the distances are less than 7 per cent. We also provide the physical properties of the individual clouds, including the linear radius, mass and surface mass density.

Acoustic Dual-Function Communication and Echo-Location in Inaudible Band.

Acoustic communications are experiencing renewed interest as alternative solutions to traditional RF communications, not only in RF-denied environments (such as underwater) but also in areas where the electromagnetic (EM) spectrum is heavily shared among several wireless systems. By introducing additional dedicated channels, independent from the EM ones, acoustic systems can be used to ensure the continuity of some critical services such as communication, localization, detection, and sensing. In this paper, we design and implement a novel acoustic system that uses only low-cost off-the-shelf hardware and the transmission of a single, suitably designed signal in the inaudible band (18–22 kHz) to perform integrated sensing (ranging) and communication. The experimental testbed consists of a common home speaker transmitting acoustic signals to a smartphone, which receives them through the integrated microphone, and of an additional receiver exploiting the same signals to estimate distance information from a physical obstacle in the environment. The performance of the proposed dual-function system in terms of noise, data rate, and accuracy in distance estimation is experimentally evaluated in a real operational environment.