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基于空域稀疏性的方位依赖阵列误差校正算法

李存勖 陈伯孝

李存勖, 陈伯孝. 基于空域稀疏性的方位依赖阵列误差校正算法[J]. 电子与信息学报, 2017, 39(9): 2219-2224. doi: 10.11999/JEIT161318
引用本文: 李存勖, 陈伯孝. 基于空域稀疏性的方位依赖阵列误差校正算法[J]. 电子与信息学报, 2017, 39(9): 2219-2224. doi: 10.11999/JEIT161318
LI Cunxu, CHEN Baixiao. Spatial Sparsity Based Method on Calibration of Direction-dependent Array Errors[J]. Journal of Electronics & Information Technology, 2017, 39(9): 2219-2224. doi: 10.11999/JEIT161318
Citation: LI Cunxu, CHEN Baixiao. Spatial Sparsity Based Method on Calibration of Direction-dependent Array Errors[J]. Journal of Electronics & Information Technology, 2017, 39(9): 2219-2224. doi: 10.11999/JEIT161318

基于空域稀疏性的方位依赖阵列误差校正算法

doi: 10.11999/JEIT161318
基金项目: 

国家自然科学基金(61571344)

Spatial Sparsity Based Method on Calibration of Direction-dependent Array Errors

Funds: 

The National Natural Science Foundation of China (61571344)

  • 摘要: 针对方位依赖阵列误差的校正问题,通过引入少量精确校正的辅助阵元,该文给出一种基于空域稀疏性的方位依赖阵列误差校正算法。将受方位依赖阵列误差扰动的阵列流型表示为理想情况下的阵列流型与幅相误差系数矩阵的乘积形式。同时利用接收信号的空域稀疏性,对接收信号进行稀疏表示,将阵列误差自校正问题转化为一个二元最优化问题,再通过交替迭代的优化方式求得两个优化变量的最优解,从而实现了信号方位与方位依赖阵列误差的联合估计。该文所提算法相比于已有算法性能提升明显,参数估计性能优于传统算法且接近参数估计的Cramer-Rao下界,仿真实验也验证了算法的有效性和优越性。
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  • 被引次数: 0
出版历程
  • 收稿日期:  2016-12-08
  • 修回日期:  2017-03-30
  • 刊出日期:  2017-09-19

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