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In this unique book, Billingsley solves the problem of radar land clutter by showing the reader how to design and predict the performance of radars that operate in situations where echoes from the earth's surface interfere with radar target echoes.
At MIT Lincoln Laboratory, we have collected a large multifrequency data base of radar ground clutter measurements from many sites. We employ our clutter data to develop clutter models. Of particular interest to us is the site-specific prediction of PPI ground clutter maps for ground-sited radars, that is, in simulating the spatial variation of ground clutter. This paper describes our measurements, and presents a statistical clutter model for spatial amplitude statistics based on depression angle, terrain type, RF frequency, and radar resolution.
Detailed knowledge of the temporal statistics of ground clutter is essential to determine the detection threshold settings so as to maximize the probability of target detection while maintaining an acceptable probability of false alarm. The performance of existing false alarm control schemes is often limited due to a lack of detailed knowledge of the ground clutter temporal statistics. In this study we analyze experimental data to characterize the temporal statistics of low-angle ground clutter in terms of the clutter's linear amplitude distribution. Effects of radar frequency, polarization, waveform resolution, land covers and wind speed on the statistics are examined. Results show that the Ricean distribution and its limiting case, the Rayleigh distribution, are appropriate models for ground clutter in steady-state wind conditions. This implies that the diffuse clutter components, which give rise to the random properties of ground clutter may be modeled as a complex Gaussian process. We found, however, that at any given time there is a fraction of the resolution cells with clutter data having nonstationary temporal statistics not well modelled by the Ricean or Rayleigh distribution. The frequency of occurrence of nonstationary clutter statistics depends on radar frequency, land cover and wind speed. Forested land cover represents the worst case scenario. Application of the results of this study to determine optimal detection threshold settings is discussed. Radar clutter; Phased array radar; S band; Canada. (edc).
Provides information on how to design and predict the performance of radars that operate in situations where land clutter is prevalent.
This report determines how ground clutter strength varies with RF frequency from VHF to X-band in ground-sited radar. These results indicate that the frequency dependence of ground clutter strength depends upon terrain type and can vary, for example, from a strongly decreasing function of frequency in forest to a strongly increasing function of frequency in farmland. Five major terrain categories are defined that encompass this dependence, namely, urban, mountains, forest, farmland, and desert. Within each terrain category, results are also shown to be dependent upon relief or roughness of the terrain and upon the depression angle at which the terrain is illuminated. The depression angle dependence is important, even for the very low angles (typically within a degree of grazing incidence) and small (typical fractional) variations in angle that occur in ground-sited radar. This report presents specific clutter strength results at each of five frequencies (VHF, UHF, L-, S-, and X-band) from each of the 42 sites at which measurements were conducted. The report then combines results from similar sites to obtain the general dependence of clutter strength versus frequency for each terrain category. clutter strengths are described in terms of moments (including the mean) and percentile levels (including the median) in measured clutter amplitude distributions resulting from cell-by-cell spatial variation over a selected large kilometer-sized macroregion of terrain at each site called the repeat sector. Measurements over the repeat sector at each site were repeated a number of times to increase the reliability of the results.
This book presents comprehensive coverage of new research into sea clutter characterisation and modelling, radar performance prediction and maritime target detection. The book also includes a summary of sea-clutter scattering characteristics and datasets provided that can be used for modelling.
A procedure is developed for predicting the clutter reflectivity and probability density function of X-band radar clutter returns for resolution cells of arbitrary size and shape. The prediction uses high-resolution measurements of phase and amplitude of the ground reflections made by synthetic aperture radar (SAR) to estimate the properties of the clutter that would be observed with lower resolution radars. Clutter scene images collected by the MSTAR Program form the basis of this work. MSTAR public clutter scene data consists of spotlight mode X-band SAR images with typical resolution 0.3 x 0.3 m. Under certain assumptions, the statistics of the image pixels will approximate those of the associated clutter cells. The probability distribution of the complex pixel amplitudes is found to be significantly non-Gaussian. Larger resolution cells are constructed by coherently combining the returns from adjacent pixels. The statistical properties of clutter in these larger resolution cells is examined for a variety of cell sizes, shapes, and underlying terrain types.