Julian C. Holtzman

A Model for Radar Images and Its Application to Adaptive Digital Filtering of Multiplicative Noise

Standard image processing techniques which are used to enhance noncoherent optically produced images are not applicable to radar images due to the coherent nature of the radar imaging process. A model for the radar imaging process is derived in this paper and a method for smoothing noisy radar images is also presented. The imaging model shows that the radar image is corrupted by multiplicative noise. The model leads to the functional form of an optimum (minimum MSE) filter for smoothing radar images. By using locally estimated parameter values the filter is made adaptive so that it provides minimum MSE estimates inside homogeneous areas of an image while preserving the edge structure. It is shown that the filter can be easily implemented in the spatial domain and is computationally efficient. The performance of the adaptive filter is compared (qualitatively and quantitatively) with several standard filters using real and simulated radar images.

Textural Features for Radar Image Analysis

Texture is an important spatial feature useful for identifying objects or regions of interest in an image. While textural features have been widely used in the analysis of a variety of photographic images, they have not been used for processing radar images. In this paper, we present a procedure for extracting a set of textural features for characterizing small areas in radar images and show that these features can be used for classifying segments of radar images corresponding to different geological formations.

Systems engineering of computer-based systems

This report from the State of Practice Working Group of the IEEE Computer Society Task Force on Engineering of Computer-Based Systems (ECBS) advocates a new discipline at the systems engineering level. The report addresses the need for an ECBS discipline, identifies current practice and needed research, and suggests improvements that are achievable today. It addresses problem areas: the ECBS process itself, requirements definition, design, interfaces, management, process automation, and documentation. The report concludes that an improved ECBS discipline is necessary for improving processes and for fostering research and training.<<ETX>>Advances in microprocessor and network technology have led to the proliferation of complex systems with distributed processing and databases, internal communication systems, and heterogeneous components. The processing components can by themselves comprise a system, or they can be embedded in a physical system such as an automobile aircraft, or medical diagnostic system. Both the encompassing system and the processing system are known as computer-based systems (CBSs). Developing large computer-based systems with complex dynamics and component interdependencies requires analysis of critical end-to-end processing flows to determine feasibility and proper allocation. Currently, no engineering discipline provides the knowledge base for the necessary trade-off studies concerning software, hardware and communication components; a new discipline is needed at the systems engineering level. The paper defines the need for a discipline devoted to engineering of computer based systems, identifies current practice and needed research, and suggests improvements that are achievable today.<<ETX>>

Moisture Dependency of Radar Backscatter from Irrigated and Non-Irrigated Fields at 400 MHz AND 13.3 GHz

Scattered 2.25 cm radar signals from an agricultural area have been found to increase 5-7 dB at angles within 45° of vertical as the radar flies from dry to irrigated parts of the same field. Indications at 75 cm are that similar effects occur, but the results are less clear because of instrumental geometry. This result was the fortuitous consequence of an overflight by the NASA/MSC earth resources aircraft at a time when a group of fields was in the process of receiving irrigation water, so that the same field contained both dry and wet soil areas. Implications for use of radar as a sensor of agricultural areas are that determining soil moisture requires incidence under 45° and avoiding soil moisture effects requires incidence beyond 45°, at least for the low vegetation in the sample fields.

The slightly-rough facet model in radar imaging of the ocean surface

Abstract The slightly-rough facet model of the ocean surface, an extension of the two-scale radar scattering model, is well suited for investigating synthetic aperture radar (SAR) imaging of the surface. We derive several statistical properties of the facets that are important in an imaging model. The two-scale scattering model is extended to include both first-order and second-order large-scale effects (tilt and curvature) using physical optics, showing that a spectrum of small-scale ripples, rather than a single ripple given by the Bragg resonance condition, contributes to the backscatter from a facet. The bandwidth of the resonant ripple spectrum depends on the radar wavelength, large-scale curvature and illumination widths. The properties of the facets are deduced from this dependence. The large-scale curvature of the surface determines the size of the facets. The expected facet size depends directly on the radar wavelength and is much smaller than the resolution of realistic radars. The resonant ripp...

The influence of sensor and flight parameters on texture in radar images

Texture is known to be Important in the analysis of radar images for geologic applications. It has previously been shown that texture features derived from the grey-level co-occurrence matrix (GLCM) can be used to separate large-scale texture in radar images. Here the influence of sensor parameters, specifically the spatial and radiometric resolution and flight parameters, i.e., the orientation of the surface structure relative to the sensor, on the ability to classify texture based on the GLCM features is investigated. It was found that changing these sensor and flight parameters greatly affects the usefulness of the GLCM for classifying texture on radar images.

Optimum Signals for Radar

The research reported herein deals with the general problem of the selection of radar waveforms. The investigation is specifically concerned with the synthesis of radar signals which are optimum in the sense that they are characterized by ambiguity surfaces minimized over certain predetermined regions of the ambiguity plane. The weighted ambiguity surface is utilized as the weighted error criterion. This error criterion is mathematically tractable and pertinent to radar system performance but is not unduly restrictive as some orientation parameters are left unspecified for subsequent cost or penalty function analysis. The signal optimization is approached by variational techniques augmented by equality and inequality constraints, for example, limiting the amount of bandwidth or frequency modulation to be less than some system requirement. Several examples are presented demonstrating the optimization techniques and providing a minimum error for the stated problem. It is shown that for any given type of amplitude modulation of the radar signal, the variance or dispersion of the ambiguity surface is not decreased for any type of phase modulation added. The optimum signal for an elliptical weighting function is derived for several cases. The minimum error is shown to depend upon the constraints and the unspecified orientation parameters and, for one case, on the second moment of the signal.

Slope-induced nonlinearities on imaging of ocean waves

The MTF (modulation transfer function) is the primary descriptor used to relate the variations of the electromagnetic backscatter from the ocean to the ocean wave parameters. The major assumption involved in the definition of the MTF is a linear relation between the backscattered power and the long-wave slope. An investigation of this assumption is presented showing that the backscattered power and wave-height are nonlinearly related at least for tilt modulation. The nonlinear relation between the backscattered power and the long-wave slope is analyzed for both vertically and horizontally polarized backscatterers. For HH polarization, at maximum slopes of 0.1 rad, the second harmonic contribution is 37% for a pointing angle of 20 degrees and reaches its minimum of roughly 19% at a pointing angle of 50 degrees . For VV polarization, the first-order amplitude and harmonic nonlinearities are always smaller than the corresponding values for HH polarization and are significant only at angles near vertical. >

Synthetic-aperture-radar imaging of the ocean surface using the slightly-rough facet model and a full surface-wave spectrum

Abstract A new technique to model synthetic-aperture-radar (SAR) imaging of ocean waves is developed using the slightly-rough-facet model of the surface. The facets are mapped into the image plane individually and their responses are added coherently to give the composite image. A windowing technique allows the orbital motions of all electromagnetically large-scale waves to be included in the mapping function deterministically; no scene coherence time is used. Simulated images show that the image cut-off of azimuthally propagating waves is due to smearing by wind-generated intermediate waves. The focus adjustment that gives the greatest image contrast when imaging azimuthally propagating waves is half the phase velocity of the dominant long wave. However, spatially offsetting the multiple looks in the image domain to compensate the propagation of the long waves during the integration time of the SAR appears to be the optimal processing technique. The imaging process is highly non-linear under most realist...

Skylab Scatterometer Measurements of Hurricane Ava: Anomalous Data Correction

The high wind-speed Ku-band backscatter data measurements of hurricane Ava made by the scatterometer flown on the Skylab were degraded. Extensive data processing and receiver calibration were required to salvage the scientific information contained in these measurements. The highlights of the special processing applied to these data are described, and the results are compared to previous experimental results and to theoretical predictions.