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基于改进NSGA-II的水声探通一体化正交频分复用波形优化算法

An improved NSGA-II-based optimization method for OFDM waveforms in integrated underwater acoustic detection and communication systems

  • 摘要: 面向水下探测通信一体化需求, 本文以正交频分复用(OFDM)波形为基础, 针对其峰均功率比以及非周期自相关积分旁瓣比较高的问题, 提出一种基于改进第二代非支配排序遗传算法(NSGA-II)的联合波形优化方法。该方法在恒模相位约束下, 以预留子载波(TR)相位为优化变量, 结合自适应交叉与变异策略以及少量精英个体的局部梯度调整, 有效实现峰均功率比与积分旁瓣比协同抑制。仿真结果表明, 与传统NSGA-II算法相比, 所提算法收敛更快、解集质量更高; 与TR-Gerchberg–Saxton (TR-GS)算法、TR-Lp范数循环算法(TR-LNCA)等相比, 所提方法能够获得更低的峰均功率比和积分旁瓣比, 并同步降低通信误码率, 提升弱目标检测概率。海试结果进一步验证了该方法的可行性。

     

    Abstract: Aiming at the integrated requirements of underwater detection and communication, this paper proposes a joint optimization method based on an improved non-dominated sorting genetic algorithm-II (NSGA-II) to address the high peak-to-average power ratio (PAPR) and high integrated sidelobe level ratio (ISLR) of the aperiodic autocorrelation of orthogonal frequency division multiplexing (OFDM) waveforms. Under the constant-modulus phase constraint, the method optimizes the phases of reserved subcarriers. Additionally, it incorporates adaptive crossover and mutation strategies and applies local gradient refinement to a small number of elite individuals, thereby achieving effective suppression of both PAPR and ISLR. Simulation results show that, compared with the conventional NSGA-II, the proposed strategy converges faster and yields higher-quality solution sets. Furthermore, compared with the Tone Reservation-Gerchberg–Saxton (TR-GS) and TR-L-norm cyclic algorithm (TR-LNCA), the proposed approach achieves lower PAPR and ISLR, while simultaneously improving communication bit error rate performance and enhancing the detection probability of weak targets. Sea trial results further verify the feasibility and effectiveness of the proposed method.

     

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