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We propose a new two-stage approach to estimate the central direction-of-arrival (DOA) and angular spread of locally distributed source. In contrast to earlier works, an advantage of this method is that it has decoupled the central DOA and angular spread based on the steering vector which is a Schur-Hadamard product. So the central DOA can be estimated in a preliminary stage, and then angular spread...
Compressive sampling is a novel framework in signal acquisition and reconstruction, which achieves sub-Nyquist sampling by exploiting the sparse nature of most signals of interest. In this letter, we propose a saliency-based compressive sampling scheme for image signals. The key idea is to exploit the saliency information of images, and allocate more sensing resources to salient regions but fewer...
We consider the problem of estimating the central direction of arrival (DOA) of a coherently distributed source. In this paper, the integral steering vector of coherently distributed source is deduced to be a Schur-Hadamard product comprising point source steering vector and a real vector. And then a blind estimator based on second order statistics is proposed to estimate the central DOA without adopting...
One of the most important constraints on wireless sensor network is the low power consumption. Therefore, topology of wireless sensor network must focus on power conservation. It is possible to extend the lifetime of a network by controlling its topology through clustering. Topology control target tracking-oriented based on overlapping clustering in wireless sensor network is proposed in this paper...
Cognitive radar is a new framework radar system proposed in 2003 and waveform selection is an important problem in this type of radar. In this paper, we design a knowledged-based (KB) waveform selector and use stochastic dynamic programming model to describe waveform selection problem. To solve the problem of curses of dimensionality, we use approximate dynamic programming (ADP) in our solution. This...
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