Remote sensing of Earth terrain

Remote sensing of earth terrain is examined. The layered random medium model is used to investigate the fully polarimetric scattering of electromagnetic waves from vegetation. The model is used to interpret the measured data for vegetation fields such as rice, wheat, or soybean over water or soil. Accurate calibration of polarimetric radar systems is essential for the polarimetric remote sensing of earth terrain. A polarimetric calibration algorithm using three arbitrary in-scene reflectors is developed. In the interpretation of active and passive microwave remote sensing data from the earth terrain, the random medium model was shown to be quite successful. A multivariate K-distribution is proposed to model the statistics of fully polarimetric radar returns from earth terrain. In the terrain cover classification using the synthetic aperture radar (SAR) images, the applications of the K-distribution model will provide better performance than the conventional Gaussian classifiers. The layered random medium model is used to study the polarimetric response of sea ice. Supervised and unsupervised classification procedures are also developed and applied to synthetic aperture radar polarimetric images in order to identify their various earth terrain components for more than two classes. These classification procedures were applied to San Francisco Bay and Traverse City SAR images

Remote sensing of earth terrain

In remote sensing, the encountered geophysical media such as agricultural canopy, forest, snow, or ice are inhomogeneous and contain scatters in a random manner. Furthermore, weather conditions such as fog, mist, or snow cover can intervene the electromagnetic observation of the remotely sensed media. In the modelling of such media accounting for the weather effects, a multi-layer random medium model has been developed. The scattering effects of the random media are described by three-dimensional correlation functions with variances and correlation lengths corresponding to the fluctuation strengths and the physical geometry of the inhomogeneities, respectively. With proper consideration of the dyadic Green's function and its singularities, the strong fluctuation theory is used to calculate the effective permittivities which account for the modification of the wave speed and attenuation in the presence of the scatters. The distorted Born approximation is then applied to obtain the correlations of the scattered fields. From the correlation of the scattered field, calculated is the complete set of scattering coefficients for polarimetric radar observation or brightness temperature in passive radiometer applications. In the remote sensing of terrestrial ecosystems, the development of microwave remote sensing technology and the potential of SAR to measure vegetation structure and biomass have increased effort to conduct experimental and theoretical researches on the interactions between microwave and vegetation canopies. The overall objective is to develop inversion algorithms to retrieve biophysical parameters from radar data. In this perspective, theoretical models and experimental data are methodically interconnected in the following manner: Due to the complexity of the interactions involved, all theoretical models have limited domains of validity; the proposed solution is to use theoretical models, which is validated by experiments, to establish the region in which the radar response is most sensitive to the parameters of interest; theoretically simulated data will be used to generate simple invertible models over the region. For applications to the remote sensing of sea ice, the developed theoretical models need to be tested with experimental measurements. With measured ground truth such as ice thickness, temperature, salinity, and structure, input parameters to the theoretical models can be obtained to calculate the polarimetric scattering coefficients for radars or brightness temperature for radiometers and then compare theoretical results with experimental data. Validated models will play an important role in the interpretation and classification of ice in monitoring global ice cover from space borne remote sensors in the future. We present an inversion algorithm based on a recently developed inversion method referred to as the Renormalized Source-Type Integral Equation approach. The objective of this method is to overcome some of the limitations and difficulties of the iterative Born technique. It recasts the inversion, which is nonlinear in nature, in terms of the solution of a set of linear equations; however, the final inversion equation is still nonlinear. The derived inversion equation is an exact equation which sums up the iterative Neuman (or Born) series in a closed form and, thus, is a valid representation even in the case when the Born series diverges; hence, the name Renormalized Source-Type Integral Equation Approach

Remote sensing of earth terrain

Abstracts from 46 refereed journal and conference papers are presented for research on remote sensing of earth terrain. The topics covered related to remote sensing include the following: mathematical models, vegetation cover, sea ice, finite difference theory, electromagnetic waves, polarimetry, neural networks, random media, synthetic aperture radar, electromagnetic bias, and others

CA-CFAR Adjustment Factor Correction with a priori Knowledge of the Clutter Distribution Shape Parameter

Oceanic and coastal radars operation is affected because the targets information is received mixed with and undesired contribution called sea clutter. Specifically, the popular CA-CFAR processor is incapable of maintaining its design false alarm probability when facing clutter with statistical variations. In opposition to the classic alternative suggesting the use of a fixed adjustment factor, the authors propose a modification of the CA- CFAR scheme where the factor is constantly corrected according on the background signal statistical changes. Mathematically translated as a variation in the shape parameter of the clutter distribution, the background signal changes were simulated through the Weibull, Log-Normal and K distributions, deriving expressions which allow choosing an appropriate factor for each possible statistical state. The investigation contributes to the improvement of radar detection by suggesting the application of an adaptive scheme which assumes the clutter shape parameter is known a priori. The offered mathematical expressions are valid for three false alarm probabilities and several windows sizes, covering also a wide range of clutter conditions

Основные характеристики морского клатера, влияющие на обнаружение малоразмерных малоподвижных целей морскими РЛС

В роботі здійснюється пошук математичної моделі морського клатера, придатної для створення на її основі алгоритму виявлення малорозмірних малорухомих цілей морськими РЛС. В результаті аналізу джерел для моделювання стохастичного розподілу амплітуди морського клатера обирається компонована Гаусова модель, оскільки її адекватність підтверджена найбільшою кількістю дослідників. В якості перспективної альтернативи стохастичній моделі обирається обговорювана в останнє десятиліття в літературі модель, основана на теорії хаосу, перевага використання якої для вирішення даного класу задач потребує остаточного підтвердження або заперечення.Searching of the sea clutter mathematical model is carried out in this paper. It is suitable to create based on it algorithm for small slow moving targets detection by marine radars. The compound Gaussian model for modeling sea clutter amplitude stochastic distribution is selected as a result of the sources analysis, because it was confirmed by most of researches. The discussed in the literature model based on chaos theory is choosen as perspective alternative for stochastic model; its advantage of using it for such problems solution must be definitively proved or denied. It was proposed many different distributions for high resolution sea clutter amplitude data modeling. The most frequently reported in the literature are K, Log-Normal and Weibull distributions. K distribution belonging to a compound-Gaussian model has the most significant theoretical and experimental background. This distribution choice is physically explained basing on the processes taking place when electromagnetic waves scattered from capillarity and gravity sea waves create a composed echo. Signal representing this echo is the product of two random components, called texture and speckle. Texture is the result of scattering from gravity waves, has a Gamma pdf (in case of K distribution) and corresponds to slow-varying large-scale structure. Speckle is the result of scattering from isolated scatterers (capillarity waves), has a Rayleigh pdf and corresponds to rapid varying small-scale structure. So, K distribution envelope is a compound distribution consisting of a locally Rayleigh distribution speckle whose mean is modulated by a gamma distribution texture. All researches consider Rayleigh pdf for speckle. The lognormal, generalized Gaussian, inverse gamma and some other distributions were proposed for the texture. Due to literature analyses it is seen that texture distribution depends on radar range resolution, but strong dependence is not proved. Some scientists modified K distribution to K-A distribution consisting of the Rayleigh, gamma and Poisson distributions to describe better spikes appearence caused by whitecaps and bursts. Using of Weibull-Weibull (WW) and KK distributions was proposed for high grazing angle and high resolution sea clutter. Doppler characteristics of the sea clutter has been investigated by many researchers and now we have well developed theory. It is known empirical behavior of sea clutter doppler spectrum for different conditions – grazing angle, resolution, wind speed, polarisation and others. Lee, Walker and Ward models are used for sea clutter doppler spectrum describing. Fast moving targets can be effectively detected in heavy sea clutter by doppler radars. But existing theory cannot improve detection of slow moving small targets in heavy sea clutter, because slow moving targets have doppler shift compared to doppler shift of sea clutter. Correlation properties of high resolution sea clutter cannot be derived from its doppler spectrum. In alternative to stohastic model, many researches prefer deterministic model and use chaos theory to describe sea clutter. This choise is based on the fact that both hydrodynamic and electromagnetic therory relying on deterministic models only. If deterministic theory usefulness in applying to high resolution see clutter description be proved completely, it can lead to great progress for small targets in heavy sea clutter detection; because in this case sea clutter behavior can be predicted if initial conditions are precisely known. Using chaotic model for high resolution sea clutter description is highly disputed in recent years, and many researches have questioned first results of high resolution sea clutter describing with chaotic theory usage by Haykin. But great possibilities can give deterministic model for small targets detection definitively proving its ability to describe high resolution sea clutter data precisely causes different scientists to return to chaos theory again and again. Promising results in this field was obtained by using multifractal theory, but still there are not strong methodological background of using deterministic models for small slow moving targets in sea clutter detection, so it is required to make research to prove or deny deterministic models usefulness for high resolution sea clutter data description.В работе осуществляется поиск математической модели морского клатера, пригодной для создания на ее основе алгоритма обнаружения малоразмерных малоподвижных целей морскими РЛС. В результате анализа источников для моделирования стохастического распределения амплитуды морского клатера избирается составная Гауссова модель, поскольку ее состоятельность подтверждена наибольшим количеством исследователей. В качестве перспективной альтернативы стохастической модели избирается обсуждаемая в литературе модель, основанная на теории хаоса, преимущество использования которой для решения данного класса задач требует окончательного подтверждения или отрицания

Sea clutter simulation

Includes bibliograpical references.This dissertation presents the results of a study, the aim of which was the prediction of sea clutter characteristics including the temporal properties of the return signals as observed by a maritime surveillance radar system. The compound K distribution model used to generate clutter amplitude statistic enables the simulation of sea clutter with a good level of approximation to real radar data and this model forms the basis for the simulation of sea clutter amplitude statistic in this dissertation. Using this distribution, a sea clutter simulator is designed to generate correlated K distributed random variates from a predefined correlation function using the method by Ward and Tough [1 ]. Results from the sea clutter simulator shows that the simulated correlated random variates fit the theoretical K distribution PDF. Experimental sea clutter measurements were carried out using an experimental netted radar system. This was done at Scarborough Cape Town. Result obtained from the monostatic node is presented. This shows the amplitude statistics of the clutter as well as the temporal variation of the Doppler spectrum. Conclusions are drawn based on this results and suggestions made for further work

Active microwave sensing of the atmosphere, chapter 4

The use of active microwave systems to study atmospheric phenomena is studied. Atmospheric pollution, weather prediction, climate and weather modification, weather danger and disaster warning, and atmospheric processes and interactions are covered

The probability of detecting and tracking RADAR targets in clutter at low grazing angles

Modern military acquisition and tracking RADARs are required to operate against aircraft and missiles specifically designed to have minimal radar cross section (RCS) and which fly at very low level to take maximum advantage of terrain screening. A model for predicting system performance is necessary for a range of terrain types in varying precipitation and seasonal cultural conditions. While the main degradation is from surface clutter and denial of sightline due to terrain and other local obstructions, several other factors such as multipath propagation, deliberate jamming and even operator performance contribute to the total model. The possibility that some radars may track obscured targets, however briefly, by using the diffraction path, is of particular interest. Although this report critically examines each of the contributory factors in order to select optimum values for inclusion in an overall computer prediction model; a new surface clutter model is specifically developed for sloped terrain using actual clutter measurements. The model is validated by comparison with an extensive survey of worldwide clutter results from both published and unpublished sources. Certain constraints have been necessary to restrict the study to a manageable size, while meeting the requirements of the sponsors. Attention is therefore focussed upon performance prediction for typical mobile tracking radar systems designed for operation against small RCS low level targets flying overland

Passive Automatic Identification System for Maritime Surveillance

This work describes the main achievements in the Passive AIS (P-AIS) project stage. The extensive literature research in the second chapter concludes performing additional in-situ experiments to estimate reliable target RCS and clutter reflectivity values at the AIS frequency range. The typical effective RCS distribution for ferry, yacht and small wooden boat is experimentally drawn; it reaches up to 26dBsm for the ferry. A clutter model is created, taking into account the literature and the experimental study. The AIS signal waveform is analyzed and the potential range and Doppler resolution is defined. More specifically, the signal ambiguity function gives approximately 20km of range resolution and 40Hz Doppler resolution. A coverage prediction tool, based on the bistatic radar equation, including the aforementioned clutter model; bistatic geometry theory; the effective target RCS; the antenna pattern; the AIS air interface parameters is made. The tool estimates the possible P-AIS coverage area. The work concludes that: even in case of high sea state, the sea is considered as a smooth surface reflection for low grazing angle of observation in the VHF range; the equidistant SNR areas change from Cassini shape to single oval receiver centered; the AIS energy provides excellent target “visibility” if the clutter is not considered. Discussions for further clutter reduction and system sophistication are arisen.JRC.G.4-Maritime affair

A survey of airborne radar systems for deployment on a High Altitude Powered Platform (HAPP)

A survey was conducted to find out the system characteristics of commercially available and unclassified military radars suitable for deployment on a stationary platform. A total of ten domestic and eight foreign manufacturers of the radar systems were identified. Questionnaires were sent to manufacturers requesting information concerning the system characteristics: frequency, power used, weight, volume, power radiated, antenna pattern, resolution, display capabilities, pulse repetition frequency, and sensitivity. A literature search was also made to gather the system characteristics information. Results of the survey are documented and comparisons are made among available radar systems