Clutter reduction based on coefficient of variation in through-wall radar imaging

In this paper, the coefficient of variation (CV), defined as the ratio of the standard deviation to the mean in statistics, is applied to through-wall imaging for clutter reduction. The received signals coming from a given point in the imaging scene are taken as the statistical samples of its corresponding pixel in the image. Then the CVs in three classes of pixels are examined: the target pixel, the clutter pixel, and the noise pixel. It could be observed that the CV in target pixel is much smaller than that in clutter pixel as well as in noise pixel. Taking advantage of this, each pixel in the image is weighted by the reciprocal of its CV. The corrected image shows that this approach can highlight the target pixels by suppressing the clutter and noise pixels. The effectiveness of this approach is validated using both simulation and real data.