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目前伪随机序列捕获算法在低信噪比、高误码率情况下性能不够理想,尤其在初始捕获相位未知时,传统序列捕获算法性能较差.文中分析了传统捕获算法模型,并且指出在现有序列捕获算法中,因捕获目标序列分散遍历于整个接收序列,造成错误信息重复累积、捕获效率低等问题.为此文中提出单状态累积修正思想,并设计出一种可控单积累状态序列捕获(CSAS-SA)算法,可以控制捕获接收机更有效地积累正确信息.信息累积过程的理论分析及仿真表明,CSAS-SA较现有序列捕获算法在实时性和纠错能力上有较大提高,尤其在信噪比为-3 dB的Gauss白噪声环境下,可提高70%的捕获成功率.
At present, the performance of Pseudo-random sequence acquisition algorithm is not ideal at low signal-to-noise ratio (SNR) and high bit error rate (BER), especially when the initial acquisition phase is unknown, and the traditional acquisition algorithm has poor performance.In this paper, In the sequential acquisition algorithm, the problem of accumulative erroneous information accumulating and acquisition efficiency is low because of traversing the target sequence scatteredly and traversing the entire receiving sequence. In this paper, we propose a single state cumulative correction idea and design a controllable single accumulated state sequence (CSAS-SA) algorithm can control the capture receiver to accumulate the correct information more effectively.The theoretical analysis and simulation of the information accumulation process show that the CSAS-SA has a greater real-time and error correction capability than the existing sequence capture algorithm Especially in Gauss white noise with SNR of -3 dB, can improve the acquisition success rate by 70%.