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针对混沌直接序列扩频信号(以下称混沌直扩信号)通过非理想信道,利用信道和混沌直扩信号的状态方程及其均衡和解调的关联性,提出一种基于状态估计的联合均衡与解调算法.算法采用多扩展卡尔曼滤波(extended kalman filter,EKF)结构,一边对信道均衡,一边估计二进制信息码,二者互为因果,同时进行,不仅可以有效克服非理想信道所带来的多径信道畸变、加性噪声等对信号的影响,还可将掩藏在混沌直扩信号中的原始二进制信息码解调出来,比均衡和解调分离的做法更有效地利用信息,有更好的实时性.仿真结果表明,所提出的算法收敛速度快,能在信道特性未知情况下较好地抵御多径效应和噪声影响,实现了混沌直扩信号在非理想信道条件下的有效可靠传输.
Aiming at the chaotic direct sequence spread spectrum signal (hereinafter referred to as chaotic DS signal), by using the state equation of channel and chaotic DS signal and its correlation between equalization and demodulation through non-ideal channel, a joint equalization based on state estimation Demodulation algorithm.The algorithm uses extended kalman filter (EKF) structure to estimate the binary information code while equalizing the channel, and each of them is a causal and simultaneous implementation, which not only can effectively overcome the non-ideal channels Multipath channel distortion, additive noise and other signals on the signal, but also can be hidden in the chaotic DS signal demodulation of the original binary information code than the equalization and demodulation method to make more efficient use of information, there are more Good real-time performance.The simulation results show that the proposed algorithm has the advantages of fast convergence, better protection against multipath effects and noise under the condition of unknown channel characteristics, and realizes the effective and reliable chaotic DS signals under non-ideal channel conditions transmission.