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Search results for: ERROR ESTIMATION
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DOP and Pseudorange Error Estimation in Mobile GNSS Systems for Android OS Applications
PublicationIn the near past, GNSS (Global Navigation Satellite Systems) were only offered for a narrow group of recipients. Nowadays, thanks to mobile devices, they are available to anyone and everywhere. Personal navigation, searching for POI (Point of Interest), etc., had become a basic essential activity. Thanks to the widespread and availability of smartphones each user can obtain information considering his or her location even in an...
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DOP and Pseudorange Error Estimation in Urban Environments for Mobile Android GNSS Applications
PublicationJust a couple of years ago, GNSS (Global Navigation Satellite Systems) were available only for a narrow group of users. Currently, with the outbreak of mobile devices, they are accessible to anyone and everywhere. Urban navigation or searching for POIs (Points of Interest) had become an everyday activity. With the availability of consumer electronics and wireless technologies, each user can obtain information considering his or...
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Minimum mean square error estimation of speech short-term predictor parameters under noisy conditions
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Bounding approach to parameter estimation without priori knowledge on model structure error.
PublicationArtykuł przedstawia estymację parametrów modelu ARMA (Autoregresive moving average) metodą zbiorów ograniczonych. Założono brak wiedzy na temat ograniczeń na błąd struktury modelu lub, że wiedza ta jest bardzo konserwatywna. W celu redukcji tego konserwatyzmu, zaproponowano koncepcje modelu punktowo-parametrycznego. W podejściu tym zakłada się istnienie zbioru parametrów modelu oraz błędu struktury odpowiadających każdej z trajektorii...
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Bounding approach to parameter estimation without prior knowledge on modeling error and application to quality modeling in drinking water distribution systems
PublicationW artykule rozważana jest estymacja parametrów modelu autoregresji z ruchoma średnią i sygnałem wejściowym (ARMAX) z wykorzystaniem przedziałowego modelu błędu. Zakłada się, że granice błędu struktury modelu są nieznane, bądź znane, ale bardzo konserwatywne. Dla zmniejszenia tego konserwatyzmu proponowane jest idea modeli punktowo-parametrycznych, w której występują zbiory parametrów i błędu modelu odpowiadające wszystkim wejściom....
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Underwater Navigation Ssystem Based on Doppler Shift – Measurements and Error Estimations
PublicationA new acoustic navigation system was developed to determine the position and speed of moving underwater objects such as divers and underwater vehicles. The path of an object and its speed were determined by the Doppler shifts of acoustic signals emitted by a transmitter placed on the object and received by four hydrophones installed at the periphery of the monitored body of water. The position and speed measurements were affected...
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Lattice filter based autoregressive spectrum estimation with joint model order and estimation bandwidth adaptation
PublicationThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running forward in...
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Lattice filter based multivariate autoregressive spectral estimation with joint model order and estimation bandwidth adaptation
PublicationThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a multivariate nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running...
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New results on estimation bandwidth adaptation
PublicationThe problem of identification of a nonstationary autoregressive signal using non-causal estimation schemes is considered. Noncausal estimators can be used in applications that are not time-critical, i.e., do not require real-time processing. A new adaptive estimation bandwidth selection rule based on evaluation of pseudoprediction errors is proposed, allowing one to adjust tracking characteristics of noncausal estimators to unknown...
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Respiratory Rate Estimation Based on Detected Mask Area in Thermal Images
PublicationThe popularity of non-contact methods of measuring vital signs, particularly respiratory rate, has increased during the SARS-COV-2 pandemic. Breathing parameters can be estimated by analysis of temperature changes observed in thermal images of nostrils or mouth regions. However, wearing virus-protection face masks prevents direct detection of such face regions. In this work, we propose to use an automatic mask detection approach...
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On the Usefulness of the Generalised Additive Model for Mean Path Loss Estimation in Body Area Networks
PublicationIn this article, the usefulness of the Generalised Additive Model for mean path loss estimation in Body Area Networks is investigated. The research concerns a narrow-band indoor off-body network operating at 2.45 GHz, being based on measurements performed with four different users. The mean path loss is modelled as a sum of four components that depend on path length, antenna orientation angle, absolute difference between transmitting...
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Estimation of Average Speed of Road Vehicles by Sound Intensity Analysis
PublicationConstant monitoring of road traffic is important part of modern smart city systems. The proposed method estimates average speed of road vehicles in the observation period, using a passive acoustic vector sensor. Speed estimation based on sound intensity analysis is a novel approach to the described problem. Sound intensity in two orthogonal axes is measured with a sensor placed alongside the road. Position of the apparent sound...
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A new method of wind farm active power curve estimation based on statistical approach
PublicationThe purpose of this paper is to solve the wind farm active power estimation problem, introducing the method which is based on a statistical approach and robust fitting. The proposed algorithm uses a statistical approach and compared to existing ones- includes a wind direction as well as the influence of turbine start-up procedure on the estimation. The results show that additional estimation inputs i.e. the wind direction and the...
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A Novel Approach of Using Selected Unconventional Geodesic Methods of Estimation on VTS Areas
PublicationThe Vessel Traffic Service (VTS) systems belong to the fundamental tools used in ensuring a high level of safety across sea basins with heavy traffic, where the presence of navigational hazards poses a great risk of collision or a ship running aground. In order to determine the mutual location of ships, VTS systems obtain information from different facilities, such as coastal radar stations, AIS, and vision systems. Fixing a ship’s...
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Evaluating Accuracy of Respiratory Rate Estimation from Super Resolved Thermal Imagery
PublicationNon-contact estimation of Respiratory Rate (RR) has revolutionized the process of establishing the measurement by surpassing some issues related to attaching sensors to a body, e.g. epidermal stripping, skin disruption and pain. In this study, we perform further experiments with image processing-based RR estimation by using various image enhancement algorithms. Specifically, we employ Super Resolution (SR) Deep Learning (DL) network...
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On autoregressive spectrum estimation using the model averaging technique
PublicationThe problem of estimating spectral density of a nonstationary process satisfying local stationarity conditions is considered. The proposed solution is a two step procedure based on local autoregressive (AR) modeling. In the first step Bayesian-like averaging of AR models, differing in order, is performed. The main contribution of the paper is development of a new final-prediction-error-like statistic, which can be used to select...
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Akaike's final prediction error criterion revisited
PublicationWhen local identification of a nonstationary ARX system is carried out, two important decisions must be taken. First, one should decide upon the number of estimated parameters, i.e., on the model order. Second, one should choose the appropriate estimation bandwidth, related to the (effective) number of input-output data samples that will be used for identification/ tracking purposes. Failure to make the right decisions results...
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Identification of models and signals robust to occasional outliers
PublicationIn this paper estimation algorithms derived in the sense of the least sum of absolute errors are considered for the purpose of identification of models and signals. In particular, off-line and approximate on-line estimation schemes discussed in the work are aimed at both assessing the coefficients of discrete-time stationary models and tracking the evolution of time-variant characteristics of monitored signals. What is interesting,...
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Identification of models and signals robust to occasional outliers
PublicationIn this paper estimation algorithms derived in the sense of the least sum of absolute errors are considered for the purpose of identification of models and signals. In particular, off-line and approximate on-line estimation schemes discussed in the work are aimed at both assessing the coefficients of discrete-time stationary models and tracking the evolution of time-variant characteristics of monitored signals. What is interesting,...
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Estimation of respiration rate using an accelerometer and thermal camera in eGlasses
PublicationRespiration rate is a very important vital sign. Different methods of respiration rate measurement or estimation have been developed. However, especially interesting are those that enable remote and unobtrusive monitoring. In this study, we investigated the use of smart glasses for the estimation of respiration rate especially useful for indoors applications. Two methods were analyzed. The first one is based on measurements of...
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Computing methods for fast and precise body surface area estimation of selected body parts
PublicationCurrently used body surface area (BSA) formulas give satisfactory results only for individuals with typical physique, while for elderly, obese or anorectic people accurate results cannot be expected. Particularly noteworthy are the results for individuals with severe obesity (body-mass index greater than 35 kg/m2), for which BSA estimation errors reached 80%. The main goal of our study is the development of precise BSA models for...
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A Universal Gains Selection Method for Speed Observers of Induction Machine
PublicationProperties of state observers depend on proper gains selection. Each method of state estimation may require the implementation of specific techniques of finding those gains. The aim of this study is to propose a universal method of automatic gains selection and perform its verification on an induction machine speed observer. The method utilizes a genetic algorithm with fitness function which is directly based on the impulse response...
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Low-Profile ESPAR Antenna for RSS-Based DoA Estimation in IoT Applications
PublicationIn this paper, we have introduced a low-profile electronically steerable parasitic array radiator (ESPAR) antenna that can successfully be used to estimate the direction-of-arrival (DoA) of incoming signals in wireless sensor network (WSN) applications, in which the height of the complete antenna has to be low. The proposed antenna is over three times lower than high-profile ESPAR antenna designs currently available in the literature...
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Identification of nonstationary multivariate autoregressive processes– Comparison of competitive and collaborative strategies for joint selection of estimation bandwidth and model order
PublicationThe problem of identification of multivariate autoregressive processes (systems or signals) with unknown and possibly time-varying model order and time-varying rate of parameter variation is considered and solved using parallel estimation approach. Under this approach, several local estimation algorithms, with different order and bandwidth settings, are run simultaneously and compared based on their predictive performance. First,...
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Adaptive estimation of the transformer stray capacitances for DC–DC converter modelling
PublicationNew low cost and accurate estimation method of transformer stray capacitances for wide band DC–DC converter modelling and design is proposed. The Wiener filter (WF) method is applied to estimate the transformer impedance – referred to the selected transformer winding configurations. Laboratory tests are used to adapt the filter, that is to find optimal impedance which minimises mean square error between measured, noise perturbed...
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On Noncausal Identification of Nonstationary Multivariate Autoregressive Processes
PublicationThe problem of identification of nonstationary multivariate autoregressive processes using noncausal local estimation schemes is considered and a new approach to joint selection of the model order and the estimation bandwidth is proposed. The new selection rule, based on evaluation of pseudoprediction errors, is compared with the previously proposed one, based on the modified Akaike’s final prediction error criterion.
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Estimation of interior-permanent-magnet-synchronous-motor rotor position by analysis of phase-current derivatives
PublicationThis paper describes an algorithm for estimation of IPMSM rotor angular position. The algorithm uses derivatives of motor phase currents resulting from PWM modulation to obtain the rotor position. The presented method is designed for medium- and high-speed range, since it is based on determination of the EMF vector. Calculation of the motor position is performed in every PWM cycle. The standard SV-PWM method is used to determine...
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On adaptive covariance and spectrum estimation of locally stationary multivariate processes
PublicationWhen estimating the correlation/spectral structure of a locally stationary process, one has to make two important decisions. First, one should choose the so-called estimation bandwidth, inversely proportional to the effective width of the local analysis window, in the way that complies with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive...
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Bearing estimation using double frequency reassignment for a linear passive array
PublicationThe paper demonstrates the use of frequency reassignment for bearing estimation. For this task, signals derived from a linear equispaced passive array are used. The presented method makes use of Fourier transformation based spatial spectrum estimation. It is further developed through the application of two-dimensional reassignment, which leads to obtaining highly concentrated energy distributions in the joint frequency-angle domain...
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Towards rainfall interception capacity estimation using ALS LiDAR data
PublicationIn this study we develop a spatial model for interception capacity of vegetation based on LiDAR data. The study is conducted in the natural wetland river valley dominated meadows, reeds and small bushes. The multiple regression model was chosen to relate the field measurements of interception capacity and LiDAR statistics at 2m grid. The optimal model was chosen by stepwise selection and further manual variables selection resulting...
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Detection and Direction-of-Arrival Estimation of Weak Spread Spectrum Signals Received with Antenna Array
PublicationThis paper presents a method for the joint detection and direction of arrival (DOA) estimation of low probability of detection (LPD) signals. The proposed approach is based on using the antenna array to receive spread-spectrum signals hidden below the noise floor. Array processing exploits the spatial correlation between phase-delayed copies of the signal and allows us to evaluate the parameter used to make the decision about the...
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublicationTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Blood Pressure Estimation Based on Blood Flow, ECG and Respiratory Signals Using Recurrent Neural Networks
PublicationThe estimation of systolic and diastolic blood pressure using artificial neural network is considered in the paper. The blood pressure values are estimated using pulse arrival time, and additionally RR intervals of ECG signal together with respiration signal. A single layer recurrent neural network with hyperbolic tangent activation function was used. The average blood pressure estimation error for the data obtained from 21 subjects...
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Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift
PublicationWhile recent computer vision algorithms achieve impressive performance on many benchmarks, they lack robustness - presented with an image from a different distribution, (e.g. weather or lighting conditions not considered during training), they may produce an erroneous prediction. Therefore, it is desired that such a model will be able to reliably predict its confidence measure. In this work, uncertainty estimation for the task...
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Novel Interpolation Method of Multi-DFT-Bins for Frequency Estimation of Signal with Parameter Step Change
PublicationThe IpDFT(Interpolation Discrete Fourier Trans-form) method is one of the most commonly used non-parametric methods. However, when a parameter (frequency, amplitude or phase) step changes in the DFT period, the DFT coefficients will be distorted seriously, resulting in the large estimation error of the IpDFT method. Hence, it is a key challenge to find an IpDFT method, which not only can eliminate the effect of the step-changed...
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Modification of Selected Propagation Models in Terms of Path Loss Estimation in Container Terminal
PublicationIt is particularly important to look for any propagation model that could be useful for designing mobile radio networks in container terminal environment. Selected propagation models have been investigated. Firstly - basing on measurements results - they have been evaluated in this scope and the analysis has shown, that the adjustment is needed. This modification improved significantly the accuracy of path loss modelling. For the...
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Improving Accuracy of Respiratory Rate Estimation by Restoring High Resolution Features With Transformers and Recursive Convolutional Models
PublicationNon-contact evaluation of vital signs has been becoming increasingly important, especially in light of the COVID- 19 pandemic, which is causing the whole world to examine people’s interactions in public places at a scale never seen before. However, evaluating one’s vital signs can be a relatively complex procedure, which requires both time and physical contact between examiner and examinee. These re- quirements limit the number...
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N-point estimators of the Instantaneous Complex Frequency
PublicationIn this paper estimators of the instantaneous complex frequency (ICF) are presented and discussed. The differential approach for the estimation of the ICF is used, therefore the estimators are based on maximally flat N-point FIR filters: differential and delay. The investigation of the filter performance includes static characteristics of ICF estimation and the error of the ICF estimation in the discrete frequency domain.W pracy...
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A hierarchical observer for a non-linear uncertain CSTR model of biochemical processes
PublicationThe problem of estimation of unmeasured state variables and unknown reaction kinetic functions for selected biochemical processes modelled as a continuous stirred tank reactor is addressed in this paper. In particular, a new hierarchical (sequential) state observer is derived to generate stable and robust estimates of the state variables and kinetic functions. The developed hierarchical observer uses an adjusted asymptotic observer...
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Improved magnitude estimation of complex numbers using alpha max and beta min algorithm
PublicationThe paper presents an improved algorithm for calculating the magnitude of complex numbers. This problem, which is a special case of square rooting, occurs for example, in FFT processors and complex FIR filters. The proposed method of magnitude calculation makes use of the modified alpha max and beta min algorithm. The improved version of the algorithm allows to control the maximum magnitude approximation error by using an adequate...
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An improvement of body surface area formulas using the 3D scanning technique
PublicationObjectives: Body surface area (BSA) is one of the major parameters used in several medical fields. However, there are concerns raised about its usefulness, mostly due to the ambiguity of its estimation. Material and Methods: Authors have conducted a voluntary study to investigate BSA distribution and estimation in a group of 179 adult people of various sex, age, and physique. Here, there is provided an extended analysis of the...
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The motion influence on respiration rate estimation from low-resolution thermal sequences during attention focusing tasks
PublicationGlobal aging has led to a growing expectancy for creating home-based platforms for indoor monitoring of elderly people. A motivation is to provide a non-intrusive technique, which does not require special activities of a patient but allows for remote monitoring of elderly people while assisting them with their daily activities. The goal of our study was to evaluate motion performed by a person focused on a specific task and check...
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Stereo vision with Equal Baseline Multiple Camera Set (EBMCS) for obtaining depth maps of plants
PublicationThis paper presents a method of improving the estimation of distances between an autonomous harvesting robot and plants with ripe fruits by using the vision system based on five cameras. The system is called Equal Baseline Multiple Camera Set (EBMCS). EBMCS has some features of a camera matrix and a camera array. EBMCS is regarded as a set of stereo cameras for estimating distances by obtaining disparity maps and depth maps. This...
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On joint order and bandwidth selection for identification of nonstationary autoregressive processes
PublicationWhen identifying a nonstationary autoregressive process, e.g. for the purpose of signal prediction or parametric spectrum estimation, two important decisions must be taken. First, one should choose the appropriate order of the autoregressive model, i.e., the number of autoregressive coefficients that will be estimated. Second, if identification is carried out using the local estimation technique, such as the localized version of...
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Modal parameters identification with Particle Swarm Optimization
PublicationThe paper presents method of the modal parameters identification based on the Particle Swarm Optimization (PSO) algorithm [1]. The basic PSO algorithm is modified in order to achieve fast convergence and low estimation error of identified parameters values. The procedure of identification as well as algorithm modifications are presented and some simple examples for the SISO systems are provided. Results are compared with the results...
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Analysis of Measurement Errors in Rail Vehicles’ Pantograph Inspection System
PublicationThe paper presents an approach to evaluation of height measurement errors in laser scanning inspection system. The system, consisting of a laser line generator and a specialized camera, is dedicated to diagnosing carbon contact strips of railway vehicles’ pantographs. While height measurement resolution is easily computable based on system parameters, determining the measurement error is troublesome due to numerous impacts. As...
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Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublicationThis paper aimed at developing a new method of estimating the impact speed of a passenger car at the moment of a crash into a W-beam road safety barrier. The determination of such a speed based on the accident outcomes is demanding, because often there is no access to full accident data. However, accurate determination of the impact speed is one of the key elements in the reconstruction of road accidents. A machine learning algorithm...
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ZASTOSOWANIE FILTRACJI CZĄSTECZKOWEJ DO ESTYMACJI POŁOŻENIA W SYSTEMIE LOKALIZACYJNYM UWB
PublicationNiniejszy artykuł dotyczy kwestii poprawy dokładności estymacji położenia w systemie lokalizacji wewnątrzbudynkowej, bazującym na radiowych pomiarach odległości realizowanych przez modemy UWB. Proponuje się zastosowanie metody filtracji cząsteczkowej do zmniejszenia błędu wyznaczania pozycji obiektu przy braku bezpośredniej widoczności ze stacją referencyjną. W artykule opisano algorytm filtru cząsteczkowego, jego przykładową implementację...
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Sensorless IPMSM drive with rotor position estimator based on analysis of phase current derivatives
PublicationThis paper describes a sensorless Interior Permanent Magnet Synchronous Motor (IPMSM) drive designed for traction applications. Wide-speed sensorless operation is provided with the use of three methods of rotor position estimation designed for: a standstill, low- and high-speed range. The paper focuses on the high-speed estimation algorithm. The estimator uses the derivatives of motor phase currentsresulting from PWM modulation...
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Influence of Flat Lapping Kinematics on Machinability of Ceramics
PublicationNew tools for flat grinding of ceramics are presented in the paper. Electroplated CBN tools (B64 and B107) were used in a modified single-disc lapping machine configuration. The results from experiments, such as the material removal rate and surface roughness parameters are presented and analyzed. Numerical simulations, based on the model for the shape error and tool wear estimation in machining with flat lapping kinematics, are...