Advanced radar cross section clutter removal algorithms

Producing good quality radar cross section (RCS) measurement data of a target is proportional to the extent of clutter mitigation. Although RCS measurements usually include clutter reduction methods, typically some level of clutter remains in the target data. In order to achieve maximum RCS data quality several computational clutter removal algorithms have been developed, each having strengths and weaknesses, which is the subject of this paper. There are three fundamental algorithms for computationally excising RCS clutter: 1. Coherent Background Subtraction 2. Image Edit Subtraction 3. Mean Subtraction Each clutter removal method is formulated, described, and demonstrated in the paper on actual target measurement data collected in a difficult field-based clutter environment. The paper furthermore demonstrates a novel composite subtraction approach using a combination of algorithms for improved clutter removal.