Narrowband interference suppression in chaos-based communications based on set-membership estimation
基于集员估计的混沌通信窄带干扰抑制技术

This paper presents the set-membership estimation for narrowband interference (NBI) suppression in chaos-based communications. The proposed NBI suppression methods under known or unknown model parameters of interference signals are derived in terms of the optimal bounding ellipsoid criteria and the bounded property of chaotic carriers, respectively. Compared to the mean phase space volume (MPSV) based Kalman filtering and the recursive least square (RLS) algorithms, the proposed NBI suppression method estimates interference signals using only a few observations with the selective updating features, so that the computation is effectively reduced. Simulations results on AR and single tone interference suppression in chaotic parameter modulation (CPM) and differential chaotic shift keying (DCSK) communication systems show that the proposed NBI suppression methods can efficiently eliminate the narrowband interference signal in CPM and DCSK communication systems, and the computation is smaller than that of MPSV-based Kalman filtering and RLS algorithms.