冲激噪声环境下基于最大相关熵准则的双基地 MIMO雷达目标参数联合估计算法

李丽; 邱天爽

doi:10.11999/JEIT160022

冲激噪声环境下基于最大相关熵准则的双基地 MIMO雷达目标参数联合估计算法

doi: 10.11999/JEIT160022

李丽^1, ,,
邱天爽²

1.
(大连大学信息工程学院大连 116622) ②(大连理工大学电子信息与电气工程学部大连 116024)

基金项目:

国家自然科学基金(61401055)

计量
- 文章访问数: 1263
- HTML全文浏览量: 109
- PDF下载量: 322
- 被引次数: 0
出版历程
- 收稿日期: 2016-01-11
- 修回日期: 2016-06-15
- 刊出日期: 2016-12-19

Parameter Jointly Estimation Algorithm in Bistatic MIMO Radar under Impulsive Noise Environment Based on Maximum Correntropy Criterion

LI Li^{1
, ,},
QIU Tianshuang²

1.
(Information Engineering College, Dalian University, Dalian 116622, China)
2.
(Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024, China)

Funds:

The National Natural Science Foundation of China (61401055)

摘要

摘要: 该文采用最大相关熵准则(MCC)对平行因子分析算法中基于三线性最小二乘(TALS)迭代准则的目标函数进行了修正，推导出适用于脉冲噪声环境的韧性平行因子分析(PARAllel FACtor, PARAFAC)算法(MCC- PARAFAC算法)，并将该方法应用于双基地MIMO雷达系统目标参数估计中。MCC-PARAFAC算法能够抑制脉冲噪声的影响，具有较好的估计性能，并且能够实现自动配对。仿真实验验证了算法的有效性。
- 双基地MIMO雷达 /
- 参数估计 /
- 最大相关熵准则 /
- 平行因子分析 /
- 冲激噪声
Abstract: By employing the Maximum Correntropy Criterion (MCC) based cost function in PARAllel FACtor (PARAFAC), the MCC-PARAFAC algorithm is deduced, which can be utilized for the parallel factor under impulsive noise environments. The MCC-PARAFAC algorithm is applied to parameter estimation in bistatic MIMO radar under impulsive noise environment. The proposed method can suppress the impulse noise interference and has better estimation performance. Furthermore, the estimated parameters are automatically paired without the additional pairing method. Simulation results verify the effectiveness of the proposed method.
- Bistatic MIMO radar /
- Parameter estimation /
- Maximum Correntropy Criterion (MCC) /
- PARAllel FACtor (PARAFAC) /
- Impulsive noise

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参考文献(22)

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