NARROWBAND INTERFERENCE SUPPRESSION IN DSSS SYSTEM

In order to suppress the strong narrowband interference in the direct sequence spread spectrum (DSSS) system, a new locally optimal detector (LOD) based on maximum entropy probability estimation is proposed. The maximum entropy probability estimation is used to mathematically express the probability density function (PDF) of observation noise in LOD, and a new nonlinear Gauss-Newton algorithm based on LMS initial parameter design is adopted to estimate the Lagrange weights of maximum entropy PDF. This interference rejection technology can reduce the error from PDF estimation, and meanwhile doesn't need any exercise data. The simulation results indicate that the LOD based on maximum entropy probability estimation can forcefully suppress narrowband interference and represent the triangle relation characteristic of DS signal. When the input JNR is 20dB, the JNR improvement after LOD is respectively improved for 30dB and 26dB compared with linearly adaptive FIR filter and nonlinearly adaptive ACM filter, meanwhile the SNR is respectively improved for 3.1dB and 1.6dB, and the JNR improvement is larger for larger input JNR.