【摘要】 直接序列扩频通信(DSSS)中的窄带干扰造成的接收机性能下降可以通过采取抑制措施来改善。扩张状态的近似条件均值滤波器(ASACM)用扩展状态方程对干扰信号建模,该算法可以有效抑制强窄带干扰,但是需要计算雅可比矩阵,且存在数值稳定性问题。提出了一种基于平方根无轨卡尔曼滤波(SRUKF)的联合估计干扰信号和模型参数的方法,并分析了AR型干扰和单音干扰下的性能。仿真结果表明,该方法的相关输出信噪比有较大改善,并且具有较强的鲁棒性。更多还原

【Abstract】 The degradation of receiver performance due to narrowband interference in DSSS can be improved by mitigation. The augmented-state approximate-conditional-mean (ASACM) filter can suppress strong narrowband interference efficiently by formulating interference with augmented state-space equation, but the flaws is its necessity in computing Jacobian matrix and frangibility to numerical problem. A novel approach estimating interference and unknown parameters jointly based on square root unscented Kalman filter (SRUKF) is proposed for the excision of narrowband interferences in spread spectrum systems. The SNR performance of the proposed SRUKF filter in two kinds of interference (AR model and single tone) are analyzed. Simulation result show great improvement has been achieved in output SNR with good stability.更多还原