Study On The Modeling Of The UAV Communication Channel And Blind Equalization Technology

In recent years, unmanned aerial vehicle(UAV) technology is widely used in various fields and the research of UAV is becoming more and more popular. Due to the interference of surrounding environment and the rapid movement of UAV itself,communication between the base station on the ground and UAV will be affected by the multipath interference and the Doppler frequency shift, thus resulting in a serious decline in the quality of communication. To establish a mathematical model can make the study of the characteristics of UAV communication channel more convenient, so as to formulate and analysis the corresponding anti-interference scheme. UAV communication channel can be divided into three scenarios. This thesis establish the corresponding discrete-time channel model to make an exploratory research on UAV Communication channel. Blind equalization is an important measure to reduce the multipath interference, since it does not require a training sequence, which can improve the utilization rate of channel. This thesis presents a blind equalization algorithm which is decided and directed based on the in-phase and quadrature components(IQDD). The CMA-IQDD is a joint algorithm of CMA and IQDD algorithms,which is converges fast and with little remain error.The thesis is organized as follows:Firstly, it introduces the small scale fading characteristics of wireless channel, as well as the mathematical model of multipath channel and its equivalent discrete-time models under the WSSUS channel. Then UAV communication channel was divided into three scenes, including en-route scenario, takeoff and arrival scenario and task scenario.The Doppler power spectrum and the delay power spectrum characteristics of each channel was studied and analyzed to establish the corresponding discrete-time channel model under different scenarios according to the WSSUS channel modeling theory.Furthermore, the stimulation of channel model with each scenario was processed in Matlab, together with the analysis of some characters such as that of the Doppler power spectrum, scattering function, channel gain, impulse response, frequency response and bit error rate. When using S-band( 2cf =GHz) monitoring and control, channels in the three scenarios are all showing slow frequency-selective fading.Compares the performance of various basic blind equalization algorithms under a time invariant channel, including CMA, MCMA, DD and CMA-DD algorithm. All of these algorithms can complete equalization under good channel condition. The results show that the convergence capability of CMA is stronger, the DD algorithm has smallerremain error after convergence and CMA-DD algorithm combines the advantages of both. However, when the channel conditions are bad, the initial error is large, CMA-DD equalization algorithm cannot be completed. To overcome the shortcomings above, this thesis presents an improved algorithm for blind equalization – IQDD, which performs better under a worse condition, but its convergence speed is still slow. The CMA-IQDD algorithms is a joint algorithm of CMA and IQDD algorithms. Simulation and analysis the equalization effect, rate of convergence and SER of the CMA-IQDD algorithms in Matlab,the results show that the algorithm is suitable for a time-varying channels.Simulation the CMA-IQDD algorithm under the UAV task scenario to verify the performance in time-varying channel, the result shows that the algorithm can effectively reduce the inter-symbol interference caused by the time-varying multipath propagation of UAV communication channel. Finally, the CMA-IQDD algorithm is achieved on the FPGA platform, and tested on the hardware platform. The results are consistent with the theoretical analysis.