基于大规模多目标优化的跳频序列设计方法

Frequency-hopping sequence design method based on large-scale multi-objective optimization

针对跳频序列设计中存在的规模小和难以兼顾多指标的问题,提出一种基于大规模多目标优化的跳频序列设计方法。首先,综合考虑跳频序列的多项性能指标,建立跳频序列多目标优化模型;然后,引入大规模多目标优化方法,并提出决策变量洗牌策略和反向差分进化,通过重新分配决策变量位置以形成具有多样性的非支配集,并通过使反向个体参与差分进化来为后续进化持续提供有效的方向;最后,通过提出算法对模型进行优化得到跳频序列集。实验结果表明,所提方法相较于其他多目标优化方法具有更强的寻优能力,得到跳频序列集的性能指标具有明显优势;所提方法在不同干扰环境中相较于其他方法具有更低的误码率,验证了提出方法的有效性和优越性。

Aiming at the problem of small scale and difficulty in taking into account multiple indexes in the design of frequency-hopping sequences,this paper proposed a frequency-hopping sequence design method based on large-scale multi-objective optimization.Firstly,considering the multiple performance indexes of frequency-hopping sequence,this paper established a multi-objective optimization model of frequency-hopping sequence.Then,this paper introduced a large-scale multi-objective optimization algorithm,and proposed the decision variable shuffling strategy and the opposition-based differential evolution,which could form a diverse non-dominated set by redistributing the position of decision variables and provide an effective direction for subsequent evolution by enabling reverse individuals to participate in differential evolution and provides an effective direction for subsequent evolution.Finally,this method used the proposed algorithm to optimize the model to obtain a frequency-hopping sequence set.The experimental results show that the proposed algorithm has stronger optimization ability than other multi-objective optimization algorithms,and the performance indexes of the frequency-hopping sequence set has obvious advantages.In different interference environments,the proposed design method has lower bit error rate than other methods,which verifies the effectiveness and superiority of the proposed method.