针对相关性衰减的子阵子空间降秩检测及最优子阵划分 -- 西北工业大学学报,2016,34(3):520-528
论文:2016,Vol:34,Issue(3):520-528
引用本文:
邵炫, 孙超. 针对相关性衰减的子阵子空间降秩检测及最优子阵划分[J]. 西北工业大学学报
Shao Xuan, Sun Chao. Reduced-Rank Sub-Array Detection and the Optimal Sub-Array Division for Spatial Correlation Attenuation[J]. Northwestern polytechnical university

针对相关性衰减的子阵子空间降秩检测及最优子阵划分
邵炫, 孙超
西北工业大学 航海学院, 陕西 西安 710072
摘要:
针对海洋波导环境下空间相关性衰减导致检测性能下降的问题进行研究。结合子空间降秩和子阵处理,提出了子阵子空间降秩检测方法并对其检测性能进行分析。结果表明,在相关性衰减的情况下,该检测方法能够获得比全阵列处理更好的检测性能。同时研究了子阵划分对子阵检测性能的影响,并给出了空间相关性衰减下的最优子阵划分方法。研究发现:最优子阵长度和信号相关长度之间存在一定的比例关系;当子阵长度与相关长度比值的取值范围为1~2.5时,可以获得最佳的检测效果。最后针对特定海洋波导环境,利用蒙特卡罗方法进行仿真验证。
关键词:    空间相关性    指数幂律相关性模型    卡方分布    子阵目标检测    最优子阵划分    水下声学    特征值    特征向量    最大似然    蒙特卡罗方法    信号处理    信噪比   
Reduced-Rank Sub-Array Detection and the Optimal Sub-Array Division for Spatial Correlation Attenuation
Shao Xuan, Sun Chao
School of Marine Science and Technology, Northwestern Polythechnical University, Xi'an 710072, China
Abstract:
In this paper, we consider the problem of detection performance degradation caused by the spatial correlation attenuation in the ocean environment. A reduced-rank detector is developed via combining the subspace Eigen Value Decomposition(EVD) with the sub-array processing,and the performance of the detector is evaluated. The results show that the reduced-rank detector using sub-arrays has a better performance than the full-array detector in the presence of imperfect correlation. Meanwhile, effects on the sub-array detection performance of the sub-array geometry are studied, and the optimal sub-array division method is proposed. We notice that there is a certain proportional relation between the optimal sub-array length and the signal correlation length, and that the optimal detection performance can be reached, as the ratio between the sub-array length and the correlation length is in the range of 1 to 2.5. The results are validated by computer simulations.
Key words:    spatial correlation    exponential-power-law modal    chi-square distribution    sub-array target detection    optimal sub-array division    underwater acoustics    eigenvalues    eigenvectors    maximum likelihood    Monte Carlo methods    signal processing    signal to noise ratio   
收稿日期: 2015-10-27     修回日期:
DOI:
基金项目: 国家重点基础研究发展计划(6131870201)和国家自然科学基金(11274252、11534009)资助
通讯作者:     Email:
作者简介: 邵炫(1988—),西北工业大学博士研究生,主要从事水声信号处理研究。
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