【摘要】 针对无源声呐中目标与接收器发生相对运动时,接收的线谱信号发生多普勒频移,出现频率展宽,导致传统的相干积分方法积分增益下降的问题,本文提出一种广义Radon-Doppler变换方法。在时频域建立接收到的运动目标辐射线谱信号的时变频谱模型,推导由多维目标运动参数表征的相邻时刻间频率偏移和相位偏移表达式,提出结合广义Radon变换和多普勒相位补偿因子的广义Radon-Doppler变换,基于多维参数空间搜索优化思想同时修正信号的非线性频率偏移和相位偏差,实现相干积分。为提高多维参数搜索效率,基于随机漂移粒子群优化算法,融入了粒子群的均匀初始化策略、适应值并行计算方式和自适应变异机制,提高了算法全局搜索能力。仿真和SwellEx-96试验数据处理结果都表明所提算法相比已有算法可有效实现时频变线谱信号的相干积累,获得聚集性更好的谱估计结果,显著提升目标检测性能。更多还原

【Abstract】 In passive sonar systems, the relative motion between a target and the receiver induces Doppler shifts in received linespectrum signals, resulting in frequency broadening. This phenomenon causes a degradation in the integration gain of conventional coherent integration methods. To address this limitation, a generalized Radon-Doppler transform is proposed in this paper. A timefrequency spectrum model for the received time-varying line-spectrum signal radiated by a moving target is established in the timefrequency domain. Expressions for the frequency offset and phase offset between adjacent time instants, characterized by the target’s multi-dimensional motion parameters, are derived. The proposed method combines the generalized Radon transform with a Doppler phase compensation factor. Based on an optimization framework involving a search over a multi-dimensional parameter space, both the nonlinear frequency shift and phase deviation of the signal are simultaneously corrected to achieve coherent integration. To enhance the efficiency of this high-dimensional parameter search, the random drift particle swarm optimization(RDPSO) algorithm is utilized. A uniform initialization strategy for the particle swarm, a parallel fitness evaluation approach, and an adaptive mutation mechanism are incorporated. These enhancements significantly improve the algorithm’s global search capability. Results from simulations and processing of the SwellEx-96 experimental dataset demonstrate that the proposed algorithm effectively achieves coherent accumulation of time-varying line-spectrum signals. Compared to existing methods, superiorly concentrated spectral e stimates are obtained, leading to a significant enhancement in target detection performance.更多还原