In a GPS illuminator based passive radar system,estimation of direction of arriving(DOA) of multiple targets is a difficult problem due to strong interference.A two-stage method combining extensive cancellation algorithm(ECA) and sparse representation is proposed.In the first stage,ECA algorithm is used to eliminate the direct-path and multi-path interference.In the second stage,sparse representation of improved weight constraints based on L1 norm is adopted to estimate DOA and suppress the interference.Simulation results show that the proposed method can effectively estimate DOA in low computation complexity without estimating the disturbance parameter.
Analysis of forest canopy hemisphere images is one of the most important methods for measuring forest canopy structure parameters. In this study, our main focus was on using circular image region segmentation, which is the basis of forest canopy hemispherical photography. The boundary of a forest canopy hemisphere image was analyzed via histogram, rectangle, and Fourier descriptors. The image boundary characteristics were defined and obtained based on the following：（1） an edge model that contains three parts, i.e., step, ramp, and roof;（2） boundary points of discontinuity;（3） an edge that has a linear distribution of scattering points. On this basis, we proposed a segmentation method for the circular region in a forest canopy hemisphere image, fitting the circular boundary and computing the center and radius by the least squares method. The method was unrelated to the parameters of the image acquisition device. Hence, this study lays a foundation for automatically adjusting the parameters of high-performance image acquisition devices used in forest canopy hemispherical photography.
