基于分数低阶类相关熵的双基地MIMO雷达目标参数联合估计新算法

doi:10.11959/j.issn.1000-436x.2016236

Abstract

Abstract:

According to the performance degradation problem of parameter estimation algorithm in the Alpha stable dis-tribution noise, inspired by the concept of correntropy, a new class of statistics, namely, the fractional lower-order cor-rentropy-analogous statistics (FCAS) was proposed. By employing the fractional lower-order correntropy-analogous sta-tistics based cost function in parallel factor (PARAFAC), the FCAS-PARAFAC algorithm was deduced which can be utilized for the parallel factor under impulsive noise environments. The FCAS-PARAFAC algorithm was applied to pa-rameter 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 automati-cally paired without the additional pairing method. Simulation results are presented to verify the effectiveness of the pro-posed method.

Key words: bistatic MIMO radar, parameter estimation, fractional lower-order correntropy-analogous statistics, parallel factor, Alpha stable distribution

Li LI,Tian-shuang QIU,Ming-yan HE. Novel method based on fractional lower-order correntropy-analogous statistics for parameter jointly estimation in bistatic MIMO radar[J]. Journal on Communications, 2016, 37(12): 42-49.

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References 15

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Novel method based on fractional lower-order correntropy-analogous statistics for parameter jointly estimation in bistatic MIMO radar

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