局部传感器发射功率约束条件下部分相干检测融合方法 |
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引用本文: | 徐振华,谢先斌,杨秀凯.局部传感器发射功率约束条件下部分相干检测融合方法[J].西安工业大学学报,2014(9):703-709,714. |
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作者姓名: | 徐振华 谢先斌 杨秀凯 |
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作者单位: | 中国电子科技集团公司第三十八研究所,合肥,230088 |
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基金项目: | 国家自然科学基金资助项目 |
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摘 要: | 针对局部传感器发射功率约束部分相干检测融合问题,利用偏移系数极大化理论优化系统检测性能,建立了基于多址接入信道传输的多传感器分布式部分相干检测融合模型,该模型将融合中心处相位同步误差建模为服从吉洪诺夫概率分布的随机变量.将局部发射功率约束部分相干检测融合问题转化为一个非线性非凸优化问题,利用非线性优化理论,得到了问题的一维搜索闭合解.蒙特卡洛仿真结果表明:当环路信噪比大于等于10时,文中方法能在低信噪比和低虚警概率情况下显著提高融合系统对目标的检测概率,其检测性能优于传统的基于并行网络拓扑结构的最优似然比方法.
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关 键 词: | 检测融合 功率约束 部分相干 非线性优化 |
Method for Local Power Constrained Partially Coherent Detection Fusion |
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Authors: | XU Zhen-hua XIE Xian-bin YANG Xiu-kai |
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Affiliation: | XU Zhen-hua;XIE Xian-bin;YANG Xiu-kai;China Electronics Technology Group Corporation No.38 Research Institute; |
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Abstract: | The study aims to solve the problem of the local power constrained partially coherent distributed detection . T he deflection coefficient maximization ( DCM ) is used to optimize the performance of the fusion system under the local power constraint of sensors .The model of partially coherent distributed detection fusion system based on the multiple access channel (MAC ) was established and the residual error of phase synchronization was modeled by the Tikhonov probability distribution function . The problem of power constrained partially coherent detection fusion was transformed into a nonlinear non-convex optimization problem .T he nonlinear optimization theory results to obtain the closed-form solution of one dimensional searching .Monte-Carlo simulations results verified the performance of the proposed method .Simulation results show that ,when the loop SNR is greater than or equal to 10 ,the proposed method can significantly improve the detection performance of the fusion system under the low false alarm probability and the low signal-to-noise ratio (SNR) .The detection performance of the proposed method outperforms the existing LRT method which is the optimal under the parallel access channel (PAC) scheme . |
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Keywords: | detection fusion power constraint partially coherent nonlinear optimization |
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