Stationary symmetric object detection in unknown indoor environments

It is difficult to detect a stationary object in practice, especially in an unknown indoor environment, because t (a) there is no distinct speed difference between the targets and the background; (b) responses of the targets are contaminated by the dense unknown clutter; (c) a priori knowledge of the background is not always available. In the paper, a scheme is designed to enhance the signal by a “time-shift & accumulation” operation. Meanwhile, clutters from different sources are non-uniformly time-shifted. As a consequence, the Signal-to-Clutter Ratio (SCR) is increased. The distribution of the accumulation of clutter and noise from different sources would approach Gaussian according to the Central Limit Theorem (CLT). Then the problem of target detection in an unknown environment becomes target detection under Gaussian clutter and noise. Since the targets concerned are symmetric objects, the signals from the symmetrically placed receiver pairs are examined. In addition, results from measurement in a realistic indoor environment are provided.