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

LI Li; QIU Tianshuang

doi:10.11999/JEIT160022

Volume 38 Issue 12

Jan. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2016 > 38(12): 3189-3196

LI Li, QIU Tianshuang. Parameter Jointly Estimation Algorithm in Bistatic MIMO Radar under Impulsive Noise Environment Based on Maximum Correntropy Criterion[J]. Journal of Electronics & Information Technology, 2016, 38(12): 3189-3196. doi: 10.11999/JEIT160022

Citation:

LI Li, QIU Tianshuang. Parameter Jointly Estimation Algorithm in Bistatic MIMO Radar under Impulsive Noise Environment Based on Maximum Correntropy Criterion[J]. Journal of Electronics & Information Technology, 2016, 38(12): 3189-3196. doi: 10.11999/JEIT160022

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

doi: 10.11999/JEIT160022

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)

Received Date: 2016-01-11
Rev Recd Date: 2016-06-15
Publish Date: 2016-12-19

Abstract

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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References(22)

References

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