基于超流体几何投影矢量机制的高频混沌移动信号优化算法

The chaotic network signal optimization algorithm based on the fluid geometry projection vector mechanism

针对当前高频混沌移动网络信号解调过程中存在星座结构辨析困难、投影复杂度高和信号解析效率低等难题,提出了基于超流体几何投影矢量机制的高频混沌移动信号解调算法。基于互相正交的三维旋转矢量平面投影方式,构建超流体几何投影机制,并获取星座接收结构,且将接收信号进行基于正交平面方式的投影分解,提高对基准矢量的获取效率。根据超流体星座接收结构特征,按环状接收方式对接收节点进行层次排列,并引入性能排序方式降低信号互相干扰现象。依据信号矢量映射方式构建信号裁决矢量,采用线性方式对独立同分布的接收信号进行分解,有效避免接收信号投影在旋转控制域上的重叠和高混沌噪声干扰。仿真实验表明,与当前混合噪声自旋解调算法、高频超高阶随机信号解调算法对比,本文算法具有更强的抗噪和抗衰落性能。

Current constellation structure of high frequency signal chaos mobile network demodulation process has problem of the projection of high complexity and low efficiency problem of signal analysis. The chaotic signal demodulation algorithm of super high frequency mobile fluid mechanism was proposed based on geometric projection vector. The super fluid geometric projection mechanism was constructed based on 3D rotation vector plane projection method with orthogonal to each other and obtain constellation receiver,as well as the access efficiency of the reference vector was improved based on orthogonal projection plane. According to the superfluid constellation receiving structure characteristics and based on the way of receiving node loop receiving hierarchy,a performance ranking method is introduced to reduce the signal interference phenomenon. Using the signal vector mapping method to build decision signal vector and using linear mode to decompose the received signal,which effectively avoid the received signal in the control domain of the rotating projection overlap and high chaotic noise. The simulation results show that the proposed algorithm has better anti noise and anti-fading performance compared with the current high temperature super high order random signal demodulation algorithm.