Tabular algorithm for evaluating the discrete cross-correlation function of the flowmeter acoustic signals

Корреляционная обработка сигналов как частный случай использования цифровой обработки данных, получаемых с акустических датчиков, находит широкое применение в современных ультразвуковых расходомерах жидкости и газа. К ним можно отнести как непосредственно корреляционные меточные расходомеры, так и расходомеры преимущественно время-импульсного или время-пролетного типов, где корреляционная обработка акустических сигналов является дополнением к общему методу измерения объемного расхода жидкости и газа. Применение корреляционной обработки позволяет повысить разрешающую способность расходомера в целом и обеспечить выделение полезного сигнала на фоне присутствия шумов с высокой степенью достоверности. В статье описан способ вычисления дискретных корреляционных функций на основе обобщенного определения дискретной корреляционной функции через свертку дискретизированных сигналов с выходов датчиков потока. Суть данного метода сводится к вычислению набора значений кумулятивных произведений отсчетов зондирующих сигналов, взятых с разным шагом в зависимости от общего количества отсчетов сигналов и предполагаемого числа значений корреляционной функции. Полученный набор значений оформляется в виде двумерного массива или матрицы, однако для большего понимания его можно представить как таблицу. Результаты суммы отдельных элементов этой таблицы или матрицы, выбранных согласно установленному правилу, и будут являться конечными значениями взаимной корреляционной функции акустических сигналов. В рамках работы составлены непосредственно алгоритм вычисления дискретной корреляционной функции в соответствии с рассмотренным методом расчета корреляционной функции, приведены примеры вычисления программным способом взаимной и автокорреляционной функций акустических сигналов, приближенных по своим свойствам к сигналам реальных ультразвуковых расходомеров. Предложенный вариант расчета дискретных корреляционных функций может быть применен в энергоэффективных вычислительных модулях расходомеров, предназначенных для длительной эксплуатации от источника автономного питания, обладающих низкой производительностью. Correlation signal processing as a particular case of using a digital data processing obtained from acoustic sensors is widely used in modern ultrasonic liquid and gas flowmeters. These include both direct correlation flowmeters and predominantly a time-pulse or time-of-flight type’s flowmeters, where the correlation processing of acoustic signals is an addition to the general method for measuring the volumetric flow rate of liquid and gas. The use of correlation processing makes it possible to increase the resolution of the flowmeter as a whole and to ensure the useful signal extraction against the background of the noise presence with a high degree of reliability. The article describes a method for calculating discrete correlation functions based on the generalized definition of a discrete correlation function through the convolution of sampled signals from the flow sensors outputs. The essence of this method comes down to calculating a values set ​​of the cumulative products of the probing signal’s samples taken with different steps depending on the total number of signal samples and the assumed number of the correlation function samples. The resulting values sequence ​​is formatted as a two-dimensional array or matrix, but for better understanding it can be represented as a table. The results of the sum of the individual elements of this table or matrix, selected according to the established rule, will be the final values ​​of the cross-correlation function of acoustic signals. Within the framework, an algorithm for calculating the discrete correlation function is directly compiled in accordance with the considered method for calculating the correlation function, examples of software calculation of the cross- and autocorrelation functions of acoustic signals, which are close in their properties to the real signals of ultrasonic flowmeters, are given. The proposed option for calculating discrete correlation functions can be applied in energy-efficient computational modules of flowmeters designed for long-term operation from an autonomous power source with low performance.

Filtering ground noise from LiDAR returns produces inferior models of forest aboveground biomass

Airborne LiDAR has become an essential data source for large-scale, high-resolution modeling of forest biomass and carbon stocks, enabling predictions with much higher resolution and accuracy than can be achieved using optical imagery alone. Ground noise filtering -- that is, excluding returns from LiDAR point clouds based on simple height thresholds -- is a common practice meant to improve the 'signal' content of LiDAR returns by preventing ground returns from masking useful information about tree size and condition contained within canopy returns. Although this procedure originated in LiDAR-based estimation of mean tree and canopy height, ground noise filtering has remained prevalent in LiDAR pre-processing, even as modelers have shifted focus to forest aboveground biomass (AGB) and related characteristics for which ground returns may actually contain useful information about stand density and openness. In particular, ground returns may be helpful for making accurate biomass predictions in heterogeneous landscapes that include a patchy mosaic of vegetation heights and land cover types. In this paper, we applied several ground noise filtering thresholds while mapping two study areas in New York (USA), one a forest-dominated area and the other a mixed-use landscape. We observed that removing ground noise via any height threshold systematically biases many of the LiDAR-derived variables used in AGB modeling. By fitting random forest models to each of these predictor sets, we found that that ground noise filtering yields models of forest AGB with lower accuracy than models trained using predictors derived from unfiltered point clouds. The relative inferiority of AGB models based on filtered LiDAR returns was much greater for the mixed land-cover study area than for the contiguously forested study area. Our results suggest that ground filtering should be avoided when mapping biomass, particularly when mapping heterogeneous and highly patchy landscapes, as ground returns are more likely to represent useful 'signal' than extraneous 'noise' in these cases.

Optimal nonlinear filtering of M-PSK signals against a background of harmonic interference with a random initial phase

Objectives. The widespread use of radio data transmission systems using signals with multiposition phase shift keying (MPSK) is due to their high noise immunity and the simplicity of constructing the transmitting and receiving parts of the equipment. The conducted studies have shown that the presence of non-fluctuation interference, in particular, harmonic interference, in the radio channel significantly reduces the noise immunity of receiving discrete information. The energy loss in this case, depending on the interference intensity, can range from fractions of dB to 10 db or more. Therefore, interference suppression is an important task for such radio systems. The aim of the work is to synthesize and analyze an algorithm for optimal nonlinear filtering of MPSK signals against a background of harmonic interference with a random initial phase.Methods. The provisions of the theory of optimal nonlinear signal filtering and methods of statistical radio engineering are used.Results. The synthesis and analysis of the algorithm of optimal nonlinear filtering of MPSK signals against the background of harmonic interference with a random initial phase are carried out. The synthesized receiver contains a discrete symbol evaluation unit, two phase-locked frequency circuits of reference generators that form evaluation copies of the signal and interference, and cross-links between them. Analytical expressions are obtained that allow calculating the dependences of the bit error probability on the signal-to-noise ratio and the interference intensity µ. It is established that uncompensated fluctuations of the initial phase of the useful signal have a greater effect on the receiver noise immunity than similar fluctuations of the phase of harmonic interference, especially with low positional signals.Conclusions. Comparison of the obtained results with the results obtained in the case when there are no harmonic interference compensation circuits shows that the use of the obtained phase filtering algorithms allows for almost complete suppression of harmonic interference. Thus, if µ = 0.5 and the probability of error is 10−2, the energy gain at M = 2 is about 2.5 dB, at M = 4 – about 6 dB, at M = 8 and M = 16 – at least 10 dB.

Fluxgate Sensors for Onboard Weighing Systems of Heavy-Duty Dump Trucks

The article reviews the results of the authors’ research on the possibility of using the magnetic field strength generated by DC traction motors as a useful signal carrying information about weight of cargo transported by a mining dump truck.The objective of the research was to find a way to determine weight of cargo carried by a mining dump truck. In contrast to the existing onboard weighing systems, it becomes possible to create a compact autonomous device that does not require integration of sensors into the body structure and electrical circuits of the truck.Problems of increasing the efficiency of measuring devices based on fluxgate converters are considered with the view of using them as onboard systems for estimating cargo weight. The sensitivity of the fluxgate sensor can be increased by increasing both the amplitude and the effective value of the voltage applied to its excitation winding. The proposed original circuit for feeding the fluxgate sensor’s excitation winding from a modulated signal generator made on logical elements allows increasing the voltage supplied to the fluxgate sensor’s excitation winding without increasing the supply voltage, and by increasing voltage surges at the fronts of rectangular modulated high-frequency pulses, as well as due to resonant phenomena. The use of such a generator excludes the influence of the fluxgate sensor’s excitation winding on the generator frequency, since the frequency of modulating signals becomes the operating frequency of the fluxgate sensor, and it remains unchanged. The increased sensitivity makes it possible to install the sensor in any convenient place in the dump truck cab, and not in the immediate vicinity of traction motors.Evaluation of cargo weight is carried out during movement of the dump truck along the control section of the road. The readings are taken from an ammeter (milliammeter), the scale of which is pre-calibrated in mass units. Measurements of mass should be carried out under the same modes of dump truck movement and with the same location of the fluxgate sensor as when calibrating the scale of the measuring device. The control section of the route on which the measurements are carried out must be the same or similar to the one on which the measuring device was calibrated.The proposed device is distinguished by ease of use, is characterised by low energy consumption, is compact, does not contain expensive elements and does not require careful maintenance.

Detection of radio signals against the background of strong electromagnetic noise in transport

The problem of detecting a useful signal in the presence of a strong background noise is considered. To solve it, a statistical approach is used, based on a change in the level of chaos in the system when an additional random or deterministic process occurs, which is probabilistically independent from a set of stochastic phenomena that form background noise. It is shown that the occurrence of this process changes the level of entropy of the measured signal; this fact is the basis of the applied mathematical algorithm. It is based on the elements of the Fourier transform apparatus for the probability density with an appropriate choice of a nonlinear function of the random process under study. The proposed approach, based on variations in the randomness in the system in the presence of a useful signal, makes it possible to record its presence against the background of noise components even at low signal-to-noise ratios. The effectiveness of the method is confirmed both by theoretical justification and by the calculations presented in this work. The condition for the implementation of the technique described in the article, which does not impose restrictions on the studied physical fields and frequency ranges, is the comparability of the width of the probabilistic distribution of the desired useful signal with several intervals of discreteness of the measuring equipment. One of the results of this work is a high sensitivity to the emergence of independent random components.

Processing of strain gauge control signals by the Kalman filter

One of the methods for detecting defects in the rolling surface of the wheels of freight cars is to measure the deformations of the rail under the passing train. The method is based on the analysis of a strain gauge signal. The main task of the strain gauge signal analysis is the selection of informative components and the removal (filtering) of interference. The paper presents methods of filtering diagnostic signals of strain gauge control and the selection of informative components. The useful signal component can be used to measure the mass of cars, to determine the dynamic load on the rails and to detect defects in the rolling surface of the wheels. The method of adaptive Kalman filtering and linear convolution are proposed as signal processing tools. Based on these algorithms, a software module based on the.NET Framework has been developed using the C# programming language. The algorithms were tested on the signals received when the train was moving along the active section of the track, with a strain gauge control system located on it. The computational complexity and speed of the algorithms are assessed, and the possibility of their further application in the autonomous mode of the system is investigated. The results show that the use of the Kalman filtering algorithm provides a significant performance advantage over the linear convolution algorithm.

Missing scalars at the cosmological collider

Light scalar fields typically develop spatially varying backgrounds during inflation. Very often they do not directly affect the density perturbations, but interact with other fields that do leave nontrivial signals in primordial perturbations. In this sense they become “missing scalars” at the cosmological collider. We study potentially observable signals of these missing scalars, focusing on a special example where a missing scalar distorts the usual oscillatory features in the squeezed bispectrum. The distortion is also a useful signal distinguishing the de Sitter background induced thermal mass from a constant intrinsic mass.

Дослідження якісних показників поляризаційної селекції об’єктів на фоні пасивних завад в поляризаційно-доплерівській радіолокаційній системі

The optimal algorithm of polarization-Doppler selection of targets against the background of passive interference is considered. The polarimetric properties of scattered electromagnetic radiation of objects. The functionally-determined mathematical model of the useful signal, structure and correlation characteristics of the internal radiation of the receiver is determined. The algorithm of optimal processing, synthesized within the method of maximum likelihood, is considered for two limit cases. Algorithmic actions in the processing of passive interference and methods of their compensation are considered and investigated. Based on the obtained results, the expression for the algorithm of compensation of interferences reflected from the earth's surface is written. The obtained algorithm equalizes the variance of the input signals and compensates the residual variance with the help of weight coefficients. On the basis of the developed algorithm the scheme of the structurally simplified optimum compensator of passive disturbances is formed. Feature processing of useful signals in the compensation scheme is investigated. To ensure the adaptability of the generated algorithm, the coefficient of the variance ratio is based on the results coming from the variance meter. It is proposed to introduce quality indicators of polarization object selection on the background of the underlying surface, which combines indicators of efficiency of passive interference compensation and indicators of efficiency of useful signal-processing against the background of internal noise of receivers. The corresponding dependence of the indicators on the correlation coefficients of passive interference of different polarizations, as well as on the coefficients that separately characterize the level of difference in signal intensities and interference in the reception channels. The information value of each indicator of the efficiency of polarization signal selection from the ratio of the input variances, the correlation coefficient of passive interference and the ratio of the input signals is investigated.The obtained results are proposed to be used to improve the quality of polarization selection of objects in ground-based and aerospace-based radar systems.

Joint processing of images in two spectral channels for small objects detecting

The article is devoted to the problem of detecting low contrast small-sized objects in two-color images with a powerful spatially non-stationary background. An increase of the detecting reliability is achieved through a combination of three factors: attenuation of the background based on the construction of its locally stationary model; improving the estimation of model parameters by excluding statistically significant outliers from the initial data; joint processing of two-color images with a weakened background component. A method of constructing a linear boundary for detecting a useful signal in a two-dimensional space is proposed. The performance characteristics of a two-channel detector of small-sized objects are presented.