Чувствительность напряжений по обводу контура фантома к изменениям комплексных сопротивлений неоднородностей в электроимпедансной томографии

Проведено аналіз впливу значень поверхневої провідності неоднорідностей на зміну значень комплексних напруг по обводу контуру фантома, порівняно з однорідним фантомом з комплексною поверхневою провідністю. Проведено аналіз впливу анізотропії скінченного елемента та всього фантома в цілому на обчислювані комплексні напруги. Отримано модель скінченного квадратного елемента, який складається з 1024х1024 скінченних елементів, отриманих по спрощеним наближеним формулам. Констатовано, що незалежно від різниці абсолютних значень напруг, виміряних при різних положеннях джерела струму, їх відносні прирощення залишаються незмінними. Для боротьби з такого роду анізотропією запропоновано разом з джерелом обертати сітки фантомів, як скінченних елементів, так і зон провідності. Остаточні висновки про межі чутливості вимірювальних пристроїв можна буде зробити лише після накопичення статистичних даних розв’язання зворотної задачі, обраним авторами методом зон провідності.Introduction. The analysis of surface conductivity influence of inhomogeneities to the changes of complex phantom contour voltages comparing with a homogeneous phantom with complex surface conductivity is carried out. The analysis of the influence of finite element and all phantom generally anisotropy on the calculated complex voltages is conducted. The results. The model of square finite element is obtained. It consists of 1024х1024 finite elements obtained by simplified approximate formulas. The relative increments of voltage values are unchanged regardless of the difference in the absolute values of voltages measured at different positions of the current source. It is proposed to rotate the phantom grids of finite elements and conductivity zones with the current source rotation to overcome this anisotropy. Conclusions. Final conclusions about the limits of the measuring device sensitivity could be done only after the data accumulation of solving the inverse problem by zones conductivity method.Проведен анализ влияния значений поверхностной проводимости неоднородностей на изменение значений комплексных напряжений по обводу контура фантома в сравнении с однородным фантомом с комплексной поверхностной проводимостью. Выполнен анализ влияния анизотропии конечного элемента и всего фантома в целом на вычисляемые комплексные напряжения. Получена модель конечного квадратного элемента, составленного из 1024х1024 конечных элементов, полученных по упрощенным формулам. Отмечено, что независимо от разницы абсолютных значений напряжений, вычисленных при различных положениях источника тока, их относительные приращения остаются неизменными. Для борьбы с такого рода анизотропией предложено вместе с источником поворачивать сетки фантомов, как конечных элементов, так и зон проводимости. Окончательные выводы о границах чувствительности измерительных устройств можно будет сделать после накопления статистических данных решения обратной задачи, выбранным авторами метода зон проводимости

Методи виявлення малорозмірних малорухомих цілей на фоні інтенсивного морського клатера

The search for methods of small targets detection by marine radars is carried out in this paper. As a result of the sources analysis three promising group of methods are selected – adaptive methods based on the clutter amplitude spherically invariant random process representation, methods based on non stohastic clutter representation and methods based on orthogonal transformations. Separately, neural networks and clutter polarization properties are noticed. Most of researches consider compound Gaussian distribution for high resolution sea clutter data modeling. Adaptive CFAR algoritm developed by Kelly for Gaussian clutter was extended for spherical invariant random process. This algorithm can detect target in compound Gaussian clutter and ensure CFAR detection if covariance matrix is precisely known. Many researches proposed different methods of covariance matrix estimating using information from cells adjacent with cell under test. Progress in this field is moving to finding less computation cost but more precise methods of covariance matrix estimation. Further progress for small slow moving targets in heavy sea clutter detection can develop in 3 ways – improving covariance matrix estimation, exploiting not stochastic methods and finding best orthogonal transform for sea clutter Doppler spectrum describing.В работе осуществляется поиск методов обнаружения малоразмерных малоподвижных целей морскими РЛС. В результате анализа источников избирается три перспективные группы методов – адаптивные методы, основанные на представлении амплитуды клатера сферически инвариантным случайным процессом, методы, основанные на моделирования клатера детерминированным процессом и методы, основанные на ортогональных преобразованиях. Отдельно отмечается использование нейронных сетей и поляризационных свойств клатера.В роботі здійснюється пошук методів виявлення малорозмірних малорухомих цілей морськими РЛС. В результаті аналізу джерел обирається три перспективні групи методів – адаптивні методи, основані на представленні амплітуди клатера сферично інваріантним випадковим процесом, методи, основані на представленні клатера детермінованим процесом, основані на ортогональних перетвореннях. Окремо відзначається використання нейронних мереж та поляризаційних властивостей клатера

Continuous Wavelet Transform and Hidden Markov Model Based Target Detection

Standard tracking filters perform target detection process by comparing the sensor output signal with a predefined threshold. However, selecting the detection threshold is of great importance and a wrongly selected threshold causes two major problems. The first problem occurs when the selected threshold is too low which results in increased false alarm rate. The second problem arises when the selected threshold is too high resulting in missed detection. Track-before-detect (TBD) techniques eliminate the need for a detection threshold and provide detecting and tracking targets with lower signal-to-noise ratios than standard methods. Although TBD techniques eliminate the need for detection threshold at sensor’s signal processing stage, they often use tuning thresholds at the output of the filtering stage. This paper presents a Continuous Wavelet Transform (CWT) and Hidden Markov Model (HMM) based target detection method for employing with TBD techniques which does not employ any thresholding

Facilitating Joint Chaos and Fractal Analysis of Biosignals through Nonlinear Adaptive Filtering

Background: Chaos and random fractal theories are among the most important for fully characterizing nonlinear dynamics of complicated multiscale biosignals. Chaos analysis requires that signals be relatively noise-free and stationary, while fractal analysis demands signals to be non-rhythmic and scale-free. Methodology/Principal Findings: To facilitate joint chaos and fractal analysis of biosignals, we present an adaptive algorithm, which: (1) can readily remove nonstationarities from the signal, (2) can more effectively reduce noise in the signals than linear filters, wavelet denoising, and chaos-based noise reduction techniques; (3) can readily decompose a multiscale biosignal into a series of intrinsically bandlimited functions; and (4) offers a new formulation of fractal and multifractal analysis that is better than existing methods when a biosignal contains a strong oscillatory component. Conclusions: The presented approach is a valuable, versatile tool for the analysis of various types of biological signals. Its effectiveness is demonstrated by offering new important insights into brainwave dynamics and the very high accuracy in automatically detecting epileptic seizures from EEG signals

Detection of low observable targets within sea clutter by structure function based multifractal analysis

Sea clutter is the backscattered returns from a patch of the sea surface illuminated by a radar pulse. Robust detection of targets within sea clutter may strengthen coastal security, improve navigation safety, and help environmental monitoring. However, no simple and reliable methods for detecting targets within sea clutter have been proposed. We introduce the structure function based multifractal theory to analyze 392 sea clutter datasets measured under various sea and weather conditions. It is found that sea clutter data exhibit multifractal behaviors in the time scale range of about 0.01 s to a few seconds, especially for data with targets. The fractal and multifractal features of sea clutter enable us to develop a simple and effective method to detect targets within sea clutter. It is shown that the method achieves very high detection accuracy. It is further shown that in the time scale range of 0.01 s to a few seconds, sea clutter data is weakly nonstationary. The nonstationarity may explain why modeling using distributions such as Weibull, log-normal, K, and compound-Gaussian only offers limited understanding of the physics of sea clutter and is not very effective in detecting targets within sea clutter

Polarization techniques for mitigation of low grazing angle sea clutter

Maritime surveillance radars are critical in commerce, transportation, navigation, and defense. However, the sea environment is perhaps the most challenging of natural radar backdrops because maritime radars must contend with electromagnetic backscatter from the sea surface, or sea clutter. Sea clutter poses unique challenges in very low grazing angle geometries, where typical statistical assumptions regarding sea clutter backscatter do not hold. As a result, traditional constant false alarm rate (CFAR) detection schemes may yield a large number of false alarms while objects of interest may be challenging to detect. Solutions posed in the literature to date have been either computationally impractical or lacked robustness. This dissertation explores whether fully polarimetric radar offers a means of enhancing detection performance in low grazing angle sea clutter. To this end, MIT Lincoln Laboratory funded an experimental data collection using a fully polarimetric X-band radar assembled largely from commercial off-the-shelf components. The Point de Chene Dataset, collected on the Atlantic coast of Massachusetts’ Cape Ann in October 2015, comprises multiple sea states, bandwidths, and various objects of opportunity. The dataset also comprises three different polarimetric transmit schemes. In addition to discussing the radar, the dataset, and associated post-processing, this dissertation presents a derivation showing that an established multiple input, multiple output radar technique provides a novel means of simultaneous polarimetric scattering matrix measurement. A novel scheme for polarimetric radar calibration using a single active calibration target is also presented. Subsequent research leveraged this dataset to develop Polarimetric Co-location Layering (PCL), a practical algorithm for mitigation of low grazing angle sea clutter, which is the most significant contribution of this dissertation. PCL routinely achieves a significant reduction in the standard CFAR false alarm rate while maintaining detections on objects of interest. Moreover, PCL is elegant: It exploits fundamental characteristics of both sea clutter and object returns to determine which CFAR detections are due to sea clutter. We demonstrate that PCL is robust across a range of bandwidths, pulse repetition frequencies, and object types. Finally, we show that PCL integrates in parallel into the standard radar signal processing chain without incurring a computational time penalty