论文标题
遗传算法在仅轴承靶向运动分析上的分析
Analysis of Genetic Algorithm on Bearings-Only Target Motion Analysis
论文作者
论文摘要
仅使用轴承角的目标运动分析是跟踪水中目标的重要研究。包括Kalman样过滤器和进化策略在内的几种方法用于获得良好的预测因子。像卡尔曼一样的过滤器无法获得预期的结果，因此在这一领域使用的进化策略已经很长时间了。具有遗传算法的目标运动分析是仅轴承靶向运动分析的最成功的方法，我们对其进行了研究。我们发现，协方差矩阵适应进化策略可以通过遗传算法进行类似的目标运动分析，并尝试了它。但是它具有统计反馈机制，并且比其他方法更快。在这项研究中，我们比较并批评了这些方法。
Target motion analysis using only bearing angles is an important study for tracking targets in water. Several methods including Kalman-like filters and evolutionary strategies are used to get a good predictor. Kalman-like filters couldn't get the expected results thus evolutionary strategies have been using in this area for a long time. Target Motion Analysis with Genetic Algorithm is the most successful method for Bearings-Only Target Motion Analysis and we investigated it. We found that Covariance Matrix Adaptation Evolutionary Strategies does the similar work with Target Motion Analysis with Genetic Algorithm and tried it; but it has statistical feedback mechanism and converges faster than other methods. In this study, we compared and criticize the methods.
