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

发布时间：2018-02-27 14:08

  本文关键词： 双基地MIMO雷达 参数估计 分数低阶类相关熵 平行因子分析 Alpha稳定分布　出处：《通信学报》2016年12期 　论文类型：期刊论文

【摘要】：针对Alpha稳定分布噪声环境下参数估计性能退化的问题,受类相关熵概念的启发,提出分数低阶类相关熵(FCAS)的概念,并采用分数低阶类相关熵准则对平行因子分析(PARAFAC)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,推导出适用于冲激噪声环境的韧性平行因子分析(FCAS-PARAFAC)算法,并将该方法应用于双基地MIMO雷达系统中目标参数估计中。FCAS-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。
[Abstract]:In order to solve the problem of parameter estimation performance degradation in Alpha stable distributed noise environment, the concept of fractional low order class correlation entropy (FCAS) is proposed, which is inspired by the concept of class correlation entropy. The objective function of parallel factor analysis (PARAFAC) algorithm based on trilinear least squares iteration criterion is modified by using fractional low order correlation entropy criterion, and the FCAS-PARAFAC algorithm suitable for impulse noise environment is derived. The method is applied to the estimation of target parameters in bistatic MIMO radar system. FCAS-PARAFAC algorithm can suppress the influence of impulse noise, has better estimation performance, and can realize automatic pairing. The simulation results show that the algorithm is effective.
【作者单位】： 大连大学信息工程学院;大连理工大学电子信息与电气工程学部;
【基金】：国家自然科学基金资助项目(No.61401055,No.61671105)~~
【分类号】：TN958
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本文编号：1542987