Research And Implementation Of Frequency Management System For High Frequency Surface Wave Radar

High Frequency Surface Wave Radar(HFSWR)has its own advantages.It is a lowcost,easy-to-maintain,new system radar with over-the-horizon and all-weather characteristics.However,the electromagnetic environment of its working frequency band(3?30MHz)is very complicated,and is flooded with a large number of short-wave communication services,radio interference,shock interference,and noise.After the highfrequency surface wave radar is interfered,it will affect its normal operation.Therefore,it is necessary to continuously monitor the spectrum of the radar in real time and find a "silent" frequency suitable for its operation.This is a very meaningful task.At the same time,the detection performance of the HFSWR system is affected by many factors,so how to reasonably and effectively evaluate its detection performance has become an urgent problem to be solved.In response to the actual needs of the compact HFSWR system,this subject aims to design a set of high-frequency ground wave radar frequency management system for engineering applications.As an important part of the HFSWR system,this system can monitor the specific electromagnetic conditions in the working environment of the radar in real time.At the same time,combined with the evaluation and analysis of detection performance,the optimal operating frequency is finally recommended,so that the radar can be used in the harsh electromagnetic environment.This thesis first introduces the composition,structure and working sequence of the frequency management system.Then,the user interaction interface is designed,and the functions of the interface are introduced.Aiming at the problem of impact interference that needs to be resolved,the influence of shock interference on the frequency monitoring subsystem is analyzed.According to the time-frequency characteristics of shock interference,the time-frequency anti-shock algorithm is theoretically studied,and the method of judging and deleting the shock interference is proposed,and the effectiveness and feasibility of the algorithm are verified on the basis of the measured data.Then,the spectrum prediction algorithm and sliding window frequency selection algorithm in the frequency selection module are analyzed and studied.This paper proposes a spectrum prediction algorithm based on Long Short-Term Memory(LSTM)model.The model introduces three additional gating units to control the memory and forgetting of time series information,which has better performance than other time series prediction models.Advantage.Through the verification of the measured data,this algorithm has smaller root-mean-square error and higher prediction accuracy compared with the current prediction model.In the sliding window frequency selection algorithm,the principle of the sliding window and the early frequency selection scheme are discussed.A frequency selection scheme of "average power spectrum and variance" is proposed,and different window functions are simulated and analyzed according to the measured data.Finally,for the evaluation of the detection performance of HFSWR,a clear index system is established,and the detection performance is preliminarily evaluated by the method of hierarchical analysis,and the simulation results are given.At the same time,for the problem of low accuracy of the evaluation results obtained by this method,an analytic hierarchy process evaluation algorithm based on particle swarm optimizationsimulated annealing hybrid algorithm is optimized.This algorithm has the advantage of making the search have a sudden jump ability,and can make the problem of local minima of the results be solved better.Simulations show that the algorithm has higher accuracy,and the evaluation results are more robust and reliable.