摘要
为了提高无线传感通信的均衡性和抗干扰性,提出一种基于协同Kalman滤波无线传感通信大数据分配机制,实现通信信道均衡,构建无线传感通信大数据分配的信道模型,采用时间反转镜技术实现无线传感通信信道中传输信道的特征重组,提取传感通信大数据的频域相关性特征量,采用协同Kalman滤波算法实现无线传感通信大数据分配的过程中的抗多径干扰处理,构建无线传感通信大数据分配模型,结合相关性的融合滤波检测方法,根据采样信号频谱的不同进行模糊卷积融合处理,得到无线传感通信大数据分配的自适应调节迭代模型,实现无线传感通信的大数据分配优化。仿真结果表明,采用该方法进行无线传感通信大数据分配的均衡性较好,抗干扰能力较强,降低了大数据输出的误比特率。
In order to improve the balance and the anti-interference of the wireless sensing communication,a cooperative Kalman filtering wireless sensing communication large data distribution mechanism is proposed,the time reversal mirror technology is adopted to realize the characteristic recombination of the transmission channel in the wireless sensing communication channel,the frequency domain correlation characteristic quantity of the sensing communication large data is extracted,the anti-multipath interference processing in the process of the large data distribution of the wireless sensing communication is realized by adopting a cooperative Kalman filtering algorithm,constructing a wireless sensor communication large data distribution model,combining the correlation fusion filtering detection method,performing fuzzy convolution fusion processing according to different sampling signal spectrum,and obtaining an adaptive adjustment iterative model of the wireless sensor communication large data distribution,And realizes the optimization of the large data distribution of the wireless sensor communication.The simulation results show that the method is good in balance of large data distribution of wireless sensor communication,and the anti-interference ability is strong,and the bit error rate of large data output is reduced.
作者
林美
何竹峰
Lin Mei;He Zhufeng(Guangdong Nanfang Institute of Techonlogy,Jiangmen 529000,China)
出处
《电子测量技术》
2019年第23期123-127,共5页
Electronic Measurement Technology
