DS/SS通信系统多个窄带干扰消除算法研究

首先提出了一种基于WPT Kalman的干扰分离、增强和消除算法。该算估采用小波包变换 (WPT)准确地跟踪单个干扰的频率和带宽并将其从接收信号中分离出来 ,然后对其使用Kalman滤波进行增强。利用干扰分离所使用的小波包基对消除干扰以后的信号进行再次WPT ,得到单个干扰的量测噪声 ,并采用一种独特的参数估计方法实现量测噪声参数的在线实时估计 ,从而改善了Kalman滤波对干扰信号波形的估计性能。该方法综合利用了WPT自适应构建信号特性所对应的“最佳”滤波器组的能力和Kalman滤波对未知信号的线性的、无偏的、最小方差估计的特点以及量测噪声参数在线实时估计策略的优点 ,可以很好地恢复多个独立的、时变的窄带干扰以便消除。仿真结果表明 ,该算法可以提高DS/SS通信系统抗窄带干扰的能力

Elimination of Multiple Narrow-Band Interferences for a DS/SS Communication System

An interference separation, enhancement and elimination algorithm based on WPT-Kalman is proposed in this paper. First, WPT is adopted to track the center frequency and bandwidth of single interference accurately and separate the interference from the received signal. Then each interference is enhanced by a Kalman filter. To improve the waveform tracking performance of the Kalman filter, another WPT is made by using the optimum wavelet packet base established by the interference separation procedure, which is applied to the signal in which all the interferences are removed to get measurement noise of single interference whose property is updated on-line by an unique parameter estimation algorithm. The ability to construct an optimum filter bank corresponding to the adaptive signal properties of the WPT and the merits of the Kalman filter to produce a linear, unbiased, minimum error-variance estimate of an unknown signal and on-line parameters estimating of the measurement noise are employed, which enableds the algorithm to track multiple independent and time-varying narrow-band interferences so that they can be effectively eliminated. Simulation results show that the proposed algorithm can improve the performance to eliminate the narrow-band interferences for DS/SS communication systems.