Frequency-hopping technology has excellent anti-jamming and multiple access networks.Frequency-Hopping Sequence(FHS)is faced with the problems of poor performance index and difficulty in considering multiple indexes in design.Therefore,a design method of FHS based on an Enhanced Runge-Kutta optimizer(ERUN)is proposed.First,an objective function is constructed based on the Hamming correlation,complexity,uniformity,and average frequency-hopping interval of the FHS,and a design model of the FHS suitable for a heuristic optimization algorithm is established.Thereafter,aiming at the slow convergence speed and poor optimization accuracy of the Runge-Kutta optimizer(RUN)in complex optimization problems,the ERUN is proposed.The ERUN uses chaos opposition-based learning to improve the quality of the initial population,obtains a better individual update direction based on the quadratic interpolation method,and helps the population jump out of the local optimum through an adaptive t-distribution perturbation.The test results for the six benchmarks and objective functions demonstrate that ERUN has a faster convergence speed and higher solution accuracy than the three latest RUN variants.The obtained FHS is applied to a frequency-hopping system.The experimental results demonstrate that the Bit Error Rate(BER)of this method is approximately 4％in a fixed jamming environment and does not increase significantly in a changing jamming environment,demonstrating strong anti-jamming ability and complex environmental adaptability.
维普
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