基于树小波压缩与最大似然的超宽带信道融合估计方法

In order to realize unmanned cluster intelligent inspection, a channel estimation method is proposed to deal with the multipath effect in complex environment, aiming at the disadvantages of pulse UWB technology in complex areas such as mountain and forest. Through theoretical analysis and experimental research, a channel estimation method (TS-SC) based on the fusion of tree wavelet compression and maximum likelihood method is proposed. Based on the Bayesian compressed sensing (CS) model, the hierarchical Bayesian model is established through sparse matrix of wavelet base and Markov chain Monte Carlo sampling to realize the recovery of the original signal under low-speed sampling. Then, the maximum likelihood estimation method (SC) is used to accurately estimate the number and gain of multipath. The experimental results show that under the condition of noise SNR is 10 dB, the detection accuracy can reach 0.559 2 with the help of low frequency sampling data, which meets the requirement of channel estimation in complex environment. The research results break through the limitations of traditional channel estimation methods and provide an effective solution for UAV cluster communication in complex environments.