Accurate and quick localization of randomly deployed nodes is required by many applications in wireless sensor networks and always formulated as a multidimensional optimization problem. Particle swarm optimization (PSO) is feasible for the localization problem because of its quick convergence and moderate demand for computing resources. This paper proposes a distributed twophase PSO algorithm to solve the flip ambiguity problem, and improve the efficiency and precision. In this work, the initial search space is defined by bounding box method and a refinement phase is put forward to correct the error due to flip ambiguity. Moreover, the unknown nodes which only have two references or three near-collinear references are tried to be localized in our research. Simulation results indicate that the proposed distributed localization algorithm is superior to the previous algorithms.

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In mono-polarized synthetic aperture radar (SAR) imagery, G 0 I distribution often is assumed as the universal model to characterize a large number of targets, which is indexed by three parameters: the number of looks, the scale parameter, and the roughness parameter. The latter is closely related to the number of elementary backscatters in each pixel, and it is the reason why so many researchers focus on it. Although many efforts have been paid on providing many estimates, numerical problems often exist in dependable estimation, such as 'outlier' and small samples and so on. Thus, a robust estimation scheme of two unknown parameters in G 0 I distribution based on random weighting method is proposed in this paper where the relationship between moments and parameters are utilized. Experimental results on SAR computational simulations data and real SAR images show that the particular scheme outperforms alternative forms of bias reduction mechanisms, and we can obtain more accurate estimation than that of other state-of-the-art algorithms.

Institute of Mathematics of the Czech Academy of Sciences provides access to digitized documents strictly for personal use. Each copy of any part of this document must contain these Terms of use.