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.

中文翻译：

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仅轴承目标运动分析的遗传算法分析

仅使用方位角进行目标运动分析是跟踪水中目标的一项重要研究。包括卡尔曼滤波器和进化策略在内的几种方法可用于获得良好的预测器。类卡尔曼滤波器不能得到预期的结果，因此进化策略在这方面已经使用了很长时间。使用遗传算法进行目标运动分析是仅轴承目标运动分析最成功的方法，我们对此进行了研究。我们发现 Covariance Matrix Adaptation Evolutionary Strategies 和 Target Motion Analysis with Genetic Algorithm 做了类似的工作，并进行了尝试；但它具有统计反馈机制，并且比其他方法收敛得更快。在这项研究中，我们对这些方法进行了比较和批评。