Coarse-To-Fine 3D Randomized Hough Transform for Dim Target Detection

Abstract

This paper makes some improvements on Roberts representation for straight line in space and proposes a coarse-to-fine three-dimensional (3D) Randomized Hough Transform (RHT) for the detection of dim targets. Using range, bearing and elevation information of the received echoes, 3D RHT can detect constant velocity target in space. In addition, this paper applies a coarse-to-fine strategy to the 3D RHT, which aims to solve both the computational and memory complexity problems. The validity of the coarse-to-fine 3D RHT is verified by simulations. In comparison with the 2D case, which only uses the range-bearing information, the coarse-to-fine 3D RHT has a better practical value in dim target detection.