利用遗传模拟退火算法解决分布式OS-CFAR检测的优化问题
The optimization of distributed OS-CFAR detection using genetic simulated annealing algorithms
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摘要: 利用遗传模拟退火算法(GSAAs)对分布式有序统计恒虚警检测(OS-CFAR)系统的k,T参数与融合规则进行了优化设计,给出了典型的3传感器在一致与非一致检测条件下的一组准最优搜索结果。分析表明 GSAAs对于该问题的优化具有良好的适应性。Abstract: The distributed multisensor detection system with Order Statistic Constant False Alarm Rate (OS-CFAR) is optimized in terms of fusion rule and (k, T) parameters using Genetic Simulated Annealing Algorithms (GSAAs). A set of quasi-optimum results of a tri-sensor system under identically and unidentically detect conditions are given and analyzed, which proves that GSAAs are efficient for this optimization.
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M. Barket, P. K. Varshney, Decentralized CFAR signal detection, IEEE Trans. on AES, 1989,AES-25(3), 141-149.[2]A.R. Elias-Fuste, A. Broquetas-Ibars, J. P. Antequera, J. C. M. Yuste, CFAR date fusion center with inhomogeneous receivers, IEEE Trans. on AES, 1992, AES-28(1), 276-285.[3]M.K. Uner, P. K. Varshney, Distributed CFAR detection in homogeneous and nonhomogeneous backgrounds, IEEE Trans. on AES, 1996, AES-32(1), 84-97.[4]周明,孙树栋编,遗传算法原理及应用,北京,国防工业出版社,1999,第四章. -
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