Narrowband Interference Cancellation in Chaos Communication Based on Dual Estimation

The performance and capacity of chaos communication systems are degraded in the presence of narrowband interference. The minimum phase space volume (MPSV) method is a well known method to suppress narrowband interference in chaos communication, however, its computing burden is heavy in estimating model parameters due to random search, and the AR model stable assumption does not usually satisfied. In order to alleviate this disadvantage, a dual estimation Narrowband Interference Cancellation (NBIC) algorithm based on squared root unscented Kalman filter (SRUKF) is proposed to estimate the interference state and model parameter simultaneously given noisy observation signal. The complete performance analysis of the various NBIC algorithms was carried out in the differential chaos shift keying (DCSK) systems. Simulation results show that the proposed dual estimation NBIC algorithm yields effective interference suppression capability, especially in single tone jammer. Further, SRUKF-based dual estimation always outperformed the Kalman-based methods.