基于压缩域的直扩测控信号干扰抑制算法

Jamming Suppression Algorithm of Direct Sequence Spread Spectrum TT&C Signal Based on Compressed Domain

压缩感知理论突破了经典采样理论的束缚,可有效缓解直扩测控信号大带宽采样引起的信号处理和数据存储的压力。通过分析直扩测控信号与干扰信号的差异,提出一种压缩域直扩测控信号自适应干扰抑制算法。该算法基于直扩测控信号特点构建相应的稀疏基,分析直扩测控信号与干扰信号在稀疏基下的归一化残差及其变化规律,通过稀疏系数重构直扩测控信号,并结合归一化残差变化率实现算法的自适应控制。仿真结果表明,所提算法能够有效抑制干扰信号,采用该算法的检测概率和误码率较直接处理分别提高了3 d B和2 d B。

Compressed sensing theory breaks the bondage of classical sampling theory, and effectively eases thesignal processing and data storage pressure of direct sequence spread spectrum（DS） telemetry tracking andcommand （TT＆C） signals in large bandwidth sampling. After analyzing the difference between DS TT＆C andjamming signals, an adaptive jamming suppression algorithm of DS TT＆C signals based on compression domainwas proposed. Based on the feature of DS TT＆C signals, corresponding sparse matrix was built. The normalizedresidual and relevant change rule of DS TT＆C signals and jamming signal in the sparse matrix were computedand validated, DS TT＆C signals were reconstructed with sparse coefficient, and the adaptive control of algorithmwas achieved combined with change rate of normalized residual. Simulation results show that the algorithm caneffectively restrain jamming signals, and detection probability and bit error rate respectively increased by 3 dBand 2 dB compared with those of the direct treatment.