【摘 要】
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In space-based Automatic Identification Systems(AIS),due to high satellite orbits,several Ad Hoc cells within the observation range of the satellite are vulnerable to interference by an external signal.To increase efficiency in target detection and improv
【机 构】
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The Key Laboratory for Computer Systems of State Ethnic Affairs Commission,School of Computer Scienc
论文部分内容阅读
In space-based Automatic Identification Systems(AIS),due to high satellite orbits,several Ad Hoc cells within the observation range of the satellite are vulnerable to interference by an external signal.To increase efficiency in target detection and improve system security,a blind source separation method is adopted for processing the conflicting signals received by satellites.Compared to traditional methods,we for-mulate the separation problem as a clustering prob-lem.Since our algorithm is affected by the sparse-ness of source signals,to get satisfactory results,our algorithm assumes that the distance between two arbi-trary mixed-signal vectors is less than the doubled sum of variances of distribution of the corresponding mix-tures.Signal sparsity is overcome by computing the Short-Time Fourier Transform,and the mixed source signals are separated using the improved PSO cluster-ing.We evaluated the performance and the robust-ness of the proposed network architecture by several simulations.The experimental results demonstrate the effectiveness of the proposed method in not only im-proving satellite signal receiving ability but also in en-hancing space-based AIS security.
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