The key for capturing the communication contents of a direct sequence spread spectrum (DSSS) communication system is how to estimate its pseudo-noise (PN) code in a non-cooperative communication condition. This paper proposes a time domain waveform processing algorithm based on Intrinsic Time-Scale Decomposition (ITD) , which can accurately estimate the PN code under a condition of very low Signal/Noise Ratio(SNR). Taking advantage of high time-frequency resolution and convenience of real-time processing in ITD algorithm, it directly analyzes fluctuation characteristics of differential signal between cumulative amplitudes from carrier frequency point and the first up zero-crosssing frequency point to find the positions of polarity alternating points between two adjacent chips in a period of PN code and to reveal the PN Code,without necessity of guessing algebra structure, where coherent accumulation from many periods of PN code signals is employed to raise the SNR of the processed results. This algorithm requires low sampling accuracy, is insensitivity to carrier frequency estimation error and fits for all kinds of PN codes when compared with algorithms available. Computer simulation validates the feasibility of the proposed algorithm.%非合作通信条件下估计未知直接序列扩频信号的伪随机(PN)码是截获直接序列扩频信号信息内容的关键.本文提出一种基于固有时间尺度分解(ITD)的时域波形处理算法,可以在很低信噪比的条件下准确地估计直接序列扩频信号的PN码.该算法充分利用ITD时频分辨率高和适于实时处理的优势,直接分解直扩信号波形,借助于多个周期的伪随机码信号的相干累加提高信噪比,通过对载频处瞬时幅度累加值与第一上过零点频率处瞬时幅度累加值的差分信号波动特性的分析,找到一个PN码周期内相邻码片极性变化的位置,从而揭示PN码,而不必猜测其代数结构.与已有PN码估计算法相比,该算法具有采样精度要求低,对载频估计误差不敏感,适用于各种类型PN码等优势.计算机仿真验证了所提算法的可行性.
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