应用于窄带干扰抑制的支持向量机方法

抑制扩频系统窄带干扰的传统方法多数是采用自适应LMS滤波来预测窄带干扰以及减少在解扩前对接受到的信号的预测干扰信号．但是由于这些方法不考虑复杂度的控制以及不能保证全局最小值，所以它们的性能不稳定．提出一种窄带干扰抑制的新方法——支持向量回归方法．它可以替代LMS滤波器用来预测窄带干扰．采用实际参数选择法则，它不但有效而且容易操作．通过计算机仿真可以看出，在多数情况下它比传统方法的性能优越，这表明它是一种对于扩频系统中窄带干扰的抑制的好方法．

A SUPPORT VECTOR MACHINE METHOD FOR NARROW-BAND INTERFERENCE SUPPRESSION

The conventional approaches to suppress the narrow - band interference of spread spectrum systems mostly use the adaptive LMS filter to predict the narrow -band interference and subtract the predicted interfering signal from the polluted received signal before de -spreading. However, since these approaches take no account of complexity control and have no guarantee of global minimum, they often suffer from unstable performance. In this paper, a new approach to narrow - band interference suppression is used to predict the narrow - band interference instead of using adaptive LMS filter. With the help of practical parameter selection rules, it is not only effective but also easy to handle. Computer simulations show that it is superior to the conventional approaches in most cases and thus is a good approach for narrow - band interference suppression in spread spectrum systems.