Synthetic Aperture Radar (SAR) data processing

The available and optimal methods for generating SAR imagery for NASA applications were identified. The SAR image quality and data processing requirements associated with these applications were studied. Mathematical operations and algorithms required to process sensor data into SAR imagery were defined. The architecture of SAR image formation processors was discussed, and technology necessary to implement the SAR data processors used in both general purpose and dedicated imaging systems was addressed

Passive multifrequency forward-scatter radar measurements of airborne targets using broadcasting signals

This paper demonstrates the feasibility and effectiveness of forward-scatter radar (FSR) target detection based on the signals of opportunity made available by standard radio and TV broadcast transmission stations. This passive FSR (P-FSR) operation is obtained by means of a simple and robust correlation process based on self-mixing. This is shown to be very effective in extracting the characteristic FSR modulation produced by airborne targets, from the signals received from frequency modulated, digital audio broadcasting, and digital video broadcasting transmitters of opportunity. Target detectability is discussed as a function of the carrier frequency, the target size, and its height at the baseline crossing. Experimental results are shown using a wide variety of sources of opportunity, target types, baselines, and receiver configurations. The target signatures obtained from the different illuminators are compared and ways of extracting the kinematic parameters of the aircraft are discussed. This validates the claimed effectiveness and robustness of the P-FSR with the presented processing scheme

FIREX mission requirements document for nonrenewable resources

The proposed mission requirements and a proposed experimental program for satellite synthetic aperture radar (SAR) system named FIREX (Free-Flying Imaging Radar Experiment) for nonrenewable resources is described. The recommended spacecraft minimum SAR system is a C-band imager operating in four modes: (1) low look angle HH-polarized; (2) intermediate look angle, HH-polarized; (3) intermediate look angle, IIV-polarized; and (4) high look angle HH-polarized. This SAR system is complementary to other future spaceborne imagers such as the Thematic Mapper on LANDSAT-D. A near term aircraft SAR based research program is outlined which addresses specific mission design issues such as preferred incidence angles or polarizations for geologic targets of interest

Comparative detections of oil spill using multimode radarsat-1 synthetic aperture radar satellite data

Oil spill or leakage into waterways and ocean spreads very rapidly due to the action of wind and currents. The study of the behavior and movement of these oil spills in sea had become imperative in describing a suitable management plan for mitigating the adverse impacts arising from such accidents. But the inherent difficulty of discriminating between oil spills and look-alikes is a main challenge with Synthetic Aperture Radar (SAR) satellite data and this is a drawback, which makes it difficult to develop a fully automated algorithm for detection of oil spill. As such, an automatic algorithm with a reliable confidence estimator of oil spill would be highly desirable. The main objective of this work is to develop comparative automatic detection procedures for oil spill pixels in multimode (Standard beam S2, Wide beam W1 and fine beam F1) RADARSAT-1 SAR satellite data that were acquired in the Malacca Straits using three algorithms namely, textures using cooccurrence matrix, post supervised classification, and neural network (NN) for oil spill detection with window size 7 x 7. The results show that the mean textures from co-occurrence matrix is the best indicator for oil spill detection as it can discriminate oil spill from its surrounding such as look-alikes, sea surface and land. The entropy and contrast textures can be mainly used for look-like detections. The receiver operator characteristic (ROC) was used to determine the accuracy of oil spill detection from RADARSAT-1 SAR data. The results show that oil spills, lookalikes, and sea surface roughness are perfectly discriminated with an area difference of 20% for oil spill, 35% look–alikes, 15% land and 30% for the sea roughness. The NN shows higher performance in automatic detection of oil spill in RADARSAT-1 SAR data as compared to other algorithms with standard deviation of 0.12. It can therefore be concluded that NN algorithm is an appropriate algorithm for oil spill automatic detection and W1 beam mode is appropriate for oil spill and look-alikes discrimination and detection

Machine Learning and Pattern Recognition Methods for Remote Sensing Image Registration and Fusion

In the last decade, the remote sensing world has dramatically evolved. New types of sensor, each one collecting data with possibly different modalities, have been designed, developed, and deployed. Moreover, new missions have been planned and launched, aimed not only at collecting data of the Earth's surface, but also at acquiring planetary data in support of the study of the whole Solar system. Indeed, such a variety of technologies highlights the need for automatic methods able to effectively exploit all the available information. In the last years, lot of effort has been put in the design and development of advanced data fusion methods able to extract and make use of all the information available from as many complementary information sources as possible. Indeed, the goal of this thesis is to present novel machine learning and pattern recognition methodologies designed to support the exploitation of diverse sources of information, such as multisensor, multimodal, or multiresolution imagery. In this context, image registration plays a major role as is allows bringing two or more digital images into precise alignment for analysis and comparison. Here, image registration is tackled using both feature-based and area-based strategies. In the former case, the features of interest are extracted using a stochastic geometry model based on marked point processes, while, in the latter case, information theoretic functionals and the domain adaptation capabilities of generative adversarial networks are exploited. In addition, multisensor image registration is also applied in a large scale scenario by introducing a tiling-based strategy aimed at minimizing the computational burden, which is usually heavy in the multisensor case due to the need for information theoretic similarity measures. Moreover, automatic change detection with multiresolution and multimodality imagery is addressed via a novel Markovian framework based on a linear mixture model and on an ad-hoc multimodal energy function minimized using graph cuts or belied propagation methods. The statistics of the data at the various spatial scales is modelled through appropriate generalized Gaussian distributions and by iteratively estimating a set of virtual images, at the finest resolution, representing the data that would have been collected in case all the sensors worked at that resolution. All such methodologies have been experimentally evaluated with respect to different datasets, and with particular focus on the trade-off between the achievable performances and the demands in terms of computational resources. Moreover, such methods are also compared with state-of-the-art solutions, and are analyzed in terms of future developments, giving insights to possible future lines of research in this field

Acronym dictionary

This reference was originally compiled as a tool for abstracters who need to know the expansion of acronyms they may encounter in the texts they are analyzing. It is a general rule of abstracting at the NASA Center For Aerospace Information (CASI) that acronyms are expanded in the abstract to enhance both information content and searchability. Over the last 22 years, abstracters at CASI have recorded acronyms and their expansions as they were encountered in documents. This is therefore an ad-hoc reference, rather than a systematic collection of all acronyms related to aerospace science and technology

VHF/UHF band antenna measurement using return loss compensation

Abstract -VHF / UHF band antenna measurement is easily influenced by surroundings. Since the bandwidth of antenna is narrow, the corresponding time-domain resolution is low, so it is difficult to eliminate the effect of multipath signals by adding a time domain gating. This paper presents a method which uses the return loss of antennas to compensate the spectrum of signals. The method extends the test bandwidth of antenna and improves the time domain resolution of signals, thus multipath interference signals are more easily to separate. The experiment of a half wavelength dipole antenna is measured in an anechoic chamber, the results show that the method can eliminate the influence of multipath interference; the measured pattern is consistent with the theoretical value

Spaceborne sensors (1983-2000 AD): A forecast of technology

A technical review and forecast of space technology as it applies to spaceborne sensors for future NASA missions is presented. A format for categorization of sensor systems covering the entire electromagnetic spectrum, including particles and fields is developed. Major generic sensor systems are related to their subsystems, components, and to basic research and development. General supporting technologies such as cryogenics, optical design, and data processing electronics are addressed where appropriate. The dependence of many classes of instruments on common components, basic R&D and support technologies is also illustrated. A forecast of important system designs and instrument and component performance parameters is provided for the 1983-2000 AD time frame. Some insight into the scientific and applications capabilities and goals of the sensor systems is also given

Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms

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