This paper presents a novel algorithm for space-time adaptive processing (STAP), by exploiting the characteristic of sparsity in the radar echo in Spatial-Doppler domain. Unlike traditional algorithm for STAP, our new method needs much less (even only one) training cells to eliminate the clutter energy in the test cell and reveal the target buried in strong clutter clearly. Owing to its excelle...

This paper considers the radar scenes which contain numerous rapidly changing terrains, i.e., there are more than one clutter-edge in the environment. This kind of radar scenes incurs sharply degradation in the performance of the present adaptive constant false alarm rate (CFAR) detectors as the statistical characteristic of reference cells is highly heterogeneous. To solve this problem, we pro...

Radar backscatter from the ground can contaminate weather signals, often resulting in severely biased meteorological estimates. If not removed, these clutter returns tend to bias reflectivity high as well as Doppler velocity and spectrum width toward zero. A ground clutter filter (GCF) can mitigate this contamination and provide unbiased meteorological estimates but typically with reduced quali...

Weather Radars provide valuable information on various weather phenomenon such as rain, hail, storm, etc that are increasingly become important in today’s scenario where disaster management has got a wider role to play. But due to the way a radar works, not only precipitation but also unwanted echoes ,that we broadly classify as clutter , which includes returns from land, sea waves, birds, inse...

Ice sounding with radar is a well-established technique for the retrieval of ice depth, and provides information on ice structures and layering. Airborne radar ice sounders suffer from off-nadir surface clutter that masks the signal from bedrock and ice layers with unwanted but simultaneously received surface reflections. This is of importance for future satellite ice-sounding missions, as the ...

A spaceborne radar for atmospheric observation must be able to detect atmospheric backscatter in the presence of clutter due to antenna sidelobes. Here, we analyze the problem in detail, deriving a method for computing clutter which includes effects of all contributing transmit pulses, Doppler shifting, finite receiver bandwidth, and curved earth's surface. The results are applied to analysis o...

In conventional radar signal and image processing, the background clutter and noise are assumed to follow the Gaussian model. Under this assumption, it has been shown that the conventional matched filter is optimal in target detection (Reference 1). However, recent research has found that many nonhomogeneous types of clutter and noise, such as sea clutter, do not fit the Gaussian model well bec...

We develop and investigate several novel multiresolution algorithms for detecting coherent radar targets embedded in clutter. These multiresolution detectors exploit the fact that prominent target scatterers interfere in a characteristic manner as resolution is changed, while multiresolution clutter signatures are random. We show, both on simulated and collected synthetic aperture radar data, t...

We have developed a Radar Echo Classifier (REC) algorithm to identify various radar echoes such as precipitation, clear air, and in particular anomalously propagated (AP) ground clutter in NEXRAD radar data. The REC uses fuzzy logic to identify these various echo types. We implemented the REC using the Python language along with C++ extensions. This implementation replaces and extends the funct...

This report reviews the published literature on the characteristics of mono-static radar seaclutter observed with high grazing angles (typically above about 10). To date, most of the analysis and modelling of sea-clutter has been undertaken at low grazing angles with the main application being for surface and airborne maritime radars. The report identifies some of the data sets that have been ...