Research On Multiuser Interference Elimination Technology Of UAV Measurement And Control System

Due to the characteristics of low cost and strong mobility,unmanned aerial vehicle(UAV)is widely used in military and civil fields.However,as the scale of UAV cluster expands,the reception performance of the downlink of its measurement and control system deteriorates sharply due to the influence of multi-user interference.In order to improve the ability of anti-interception and anti-jammin g,and enhance the capacity of the cluster system,it is urgent to introduce large spread spectrum multi-user code division multiple access technology.Multi-user interference is the most important interference which affects its performance.The elimination technology of multi-user interference mainly includes two aspects:channel estimation and multi-user detection.This paper studies the spread spectrum multi-user interference elimination technology of large-scale UAV measurement and control system,and puts forward the channel estimation and multi-user detection algorithm adapted to this environment.The main research contents and innovative achievements are as follows:As for the channel estimation technology,the pilot frequency of different users has a certain correlation.In large-scale UAV measurement and control system,the signal receiving of the target terminal is often interfered by a large number of other terminals,which leads to inaccurate channel estimation results.To solve this problem,a pre-IC channel estimation algorithm based on interference pre-elimination strategy is proposed in this paper.By using the autocorrelation and balance of pseudo-noise Code(PN)sequences,the interference between users is completely avoided,and excellent channel estimation results can be obtained even in large clusters.The simulation of the channel estimation algorithm using MATLAB shows that the precision of the pre-IC channel estimation algorithm will not become worse with the increase of the cluster size,which completely avoids the influence of multi-user interference on the channel estimation results,and avoids the matrix inversion operation to ensure the real-time performance of the algorithm.For multi-user detection technology,the time complexity of multi-user detection algorithm is often too high due to the large capacity cluster scale,which is difficult to meet the real-time requirements of ground receiving base stations.To solve this problem,a wavelet neural network multi-user detection algorithm,namely Morlet-Hopfield multi-user detection algorithm,is proposed in this paper.This algorithm is based on the Minimum Mean Square Error(MMSE)criterion to eliminate the interference to the terminal signal of the target UAV.The number of iterations of the algorithm is effectively reduced.Since Hopfield neural network is easy to fall into local optimal solution and has many network iterations in large-scale optimization problems,Morlet based wavelet model is used as the activation function of Hopfield neural network in this paper,which improves the ability of Hopfield neural network’s neurons to conduct chaotic search on global optimal solution to a certain extent.The number of iterations is reduced by about 50%,and the accuracy of the multi-user detection algorithm is guaranteed.