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基于混沌载波的有界性和最优定界椭球(OBE)准则,推导出了已知干扰信号模型参数的状态估计和未知干扰信号模型参数的自适应状态估计的干扰对消算法.与基于最小相空间体积(MPSV)的Kalman滤波和传统的递归最小二乘(RLS)算法相比,本算法具有选择更新特性,能在仅有少量数据参与更新的情况下达到与前者接近的性能,降低了计算量.该方法的性能通过在混沌参数调制(CPM)和差分混沌相移键控(DCSK)两种通信方式下对自回归(AR)型和单音两种窄带干扰的有效抑制得到了验证.
Based on the boundedness of the chaotic carrier and the principle of the optimal delimiter ellipsoid (OBE), the interference cancellation algorithm for the state estimation of the known interference signal model parameters and the adaptive state estimation of the unknown interference signal model parameters is derived. Compared with the traditional Recursive Least Squares (RLS) algorithm, the Kalman filter of the minimum phase space volume (MPSV) has the characteristics of selective update and achieves the performance close to the former with only a small amount of data involved in the update, The computational complexity of the proposed method is obtained by the effective suppression of the two kinds of narrowband interferences such as autoregressive (AR) and single tones under the two communication modes: chaotic parameter modulation (CPM) and differential chaotic phase shift keying (DCSK) verification.