沖激噪聲環(huán)境下基于最大相關熵準則的雙基地 MIMO雷達目標參數聯(lián)合估計算法
doi: 10.11999/JEIT160022
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1.
(大連大學信息工程學院 大連 116622) ②(大連理工大學電子信息與電氣工程學部 大連 116024)
基金項目:
國家自然科學基金(61401055)
Parameter Jointly Estimation Algorithm in Bistatic MIMO Radar under Impulsive Noise Environment Based on Maximum Correntropy Criterion
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1.
(Information Engineering College, Dalian University, Dalian 116622, China)
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2.
(Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024, China)
Funds:
The National Natural Science Foundation of China (61401055)
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摘要: 該文采用最大相關熵準則(MCC)對平行因子分析算法中基于三線性最小二乘(TALS)迭代準則的目標函數進行了修正,推導出適用于脈沖噪聲環(huán)境的韌性平行因子分析(PARAllel FACtor, PARAFAC)算法(MCC- PARAFAC算法),并將該方法應用于雙基地MIMO雷達系統(tǒng)目標參數估計中。MCC-PARAFAC算法能夠抑制脈沖噪聲的影響,具有較好的估計性能,并且能夠實現(xiàn)自動配對。仿真實驗驗證了算法的有效性。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.
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