This paper introduces a novel and efficient algorithm for online estimation of zero-effortmiss and time-to-go based on data driven method.Only missile-target separations are utilized to construct the estimation models...This paper introduces a novel and efficient algorithm for online estimation of zero-effortmiss and time-to-go based on data driven method.Only missile-target separations are utilized to construct the estimation models,and a practical Fisher fusion algorithm is derived to acquire the estimates with high accuracy and computational efficiency.Further,the two parameters can be online estimated at a particular time.Meanwhile,the kinematics equations of the missile-target engagement are independent,and assumptions of the missile guidance system dynamics and behaviors of the missile and target are completely out of consideration.Moreover,the effectiveness and applicability are explicitly verified through various simulation scenarios.展开更多
场景生成技术通过模拟多种典型场景的随机性和多样性,为解决历史数据样本有限和极端场景难以覆盖的问题提供了重要数据支撑。该文提出一种基于特征约束与目标驱动的WGAN-GP(Wasserstein GAN with gradient penalty)光伏多场景生成方法...场景生成技术通过模拟多种典型场景的随机性和多样性,为解决历史数据样本有限和极端场景难以覆盖的问题提供了重要数据支撑。该文提出一种基于特征约束与目标驱动的WGAN-GP(Wasserstein GAN with gradient penalty)光伏多场景生成方法。该方法通过引入Wasserstein距离及梯度惩罚,提高了生成器的稳定性与生成样本的多样性;在此基础上,提取晴天、阴雨天和多云天3类典型场景的关键特征,明确生成目标,并在生成器的输出阶段嵌入动态门函数,动态划定白天与夜间的分界点,确保生成的夜间输出为零,白天的辐照度变化符合实际物理规律;此外,采用加权采样优化策略,通过动态调整样本权重和选中概率,进一步强化对关键特性样本的学习,使生成器能够更准确地捕捉目标特性,从而显著提升稀缺场景的生成效果。算例结果表明,该方法能够精准捕捉不同天气场景的关键特征,生成样本在目标特性匹配及物理合理性方面表现良好,为光伏场景生成提供了一种可靠的解决方案。展开更多
基金supported by the National Natural Science Foundation of China(No.71571190)
文摘This paper introduces a novel and efficient algorithm for online estimation of zero-effortmiss and time-to-go based on data driven method.Only missile-target separations are utilized to construct the estimation models,and a practical Fisher fusion algorithm is derived to acquire the estimates with high accuracy and computational efficiency.Further,the two parameters can be online estimated at a particular time.Meanwhile,the kinematics equations of the missile-target engagement are independent,and assumptions of the missile guidance system dynamics and behaviors of the missile and target are completely out of consideration.Moreover,the effectiveness and applicability are explicitly verified through various simulation scenarios.
文摘场景生成技术通过模拟多种典型场景的随机性和多样性,为解决历史数据样本有限和极端场景难以覆盖的问题提供了重要数据支撑。该文提出一种基于特征约束与目标驱动的WGAN-GP(Wasserstein GAN with gradient penalty)光伏多场景生成方法。该方法通过引入Wasserstein距离及梯度惩罚,提高了生成器的稳定性与生成样本的多样性;在此基础上,提取晴天、阴雨天和多云天3类典型场景的关键特征,明确生成目标,并在生成器的输出阶段嵌入动态门函数,动态划定白天与夜间的分界点,确保生成的夜间输出为零,白天的辐照度变化符合实际物理规律;此外,采用加权采样优化策略,通过动态调整样本权重和选中概率,进一步强化对关键特性样本的学习,使生成器能够更准确地捕捉目标特性,从而显著提升稀缺场景的生成效果。算例结果表明,该方法能够精准捕捉不同天气场景的关键特征,生成样本在目标特性匹配及物理合理性方面表现良好,为光伏场景生成提供了一种可靠的解决方案。
