Synthesis of an algorithm for grouping air objects in radar systems

N. R. Khalimov, S. Ivanov, A. V. Fedorov
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Abstract

Any radar complex exercising control over the airspace has a limited capacity. When processing information about a large number of air objects, overloads occur in information systems and part of the information is inevitably lost. To solve this problem, you need to group the goals. If you refuse to group, then this can lead to oversaturation of the displayed situation on the monitor and the human operator, according to his physical capabilities, will not be able to cope with its assessment. That is, the more goals, the worse the quality of the tasks being solved. One of the ways to solve this problem is to reduce the number of tracked objects by grouping them. Therefore, grouping is a necessary measure taken to simplify the presentation and assessment of the situation. The currently used algorithms for grouping air objects are based on spatial gating, which have low efficiency in a difficult environment. Therefore, the development of new strobe-free methods of grouping air objects is an urgent task. Objective – to develop and research a new strobe-free algorithm for grouping air objects in radar complexes for detecting and tracking air targets. In work a new algorithm for grouping air objects is synthesized, which is based on one of the methods of cluster analysis and an optimal decision rule according to the Neumann-Pearson criterion about the belonging of the considered set of air objects to one group. Some results of simulation modeling of the synthesized algorithm in a complex air environment in comparison with the algorithm based on production rules are presented. Practical significance – the developed algorithm for grouping air objects is more efficient than both the grouping algorithm in the spatial strobe and the algorithm based on production rules. This is especially noticeable in cases of flight of several groups to air objects on intersecting trajectories. The developed algorithm does not impose great requirements on the computing system of the radar complex and can be implemented in practice without restrictions.
雷达系统中空中目标分组算法的综合
任何控制空域的雷达系统的能力都是有限的。在处理大量空中物体的信息时,信息系统会出现过载,不可避免地会丢失部分信息。要解决这个问题,您需要对目标进行分组。如果拒绝分组,那么这可能会导致显示器上显示的情况过饱和,而人类操作员根据他的身体能力,将无法应付其评估。也就是说,目标越多,任务的质量就越差。解决这个问题的方法之一是通过分组来减少跟踪对象的数量。因此,分组是一种必要的措施,以简化情况的介绍和评估。目前使用的空中目标分组算法是基于空间门控的,在复杂环境下效率较低。因此,开发新的无频闪仪对空中目标进行分组的方法是一项紧迫的任务。目的:开发和研究一种新的无频闪的雷达综合体空中目标分组算法,用于探测和跟踪空中目标。本文综合了一种新的空中目标分组算法,该算法基于一种聚类分析方法和基于Neumann-Pearson准则的最优决策规则来判断所考虑的空中目标集是否属于一组。给出了该算法在复杂空气环境下的仿真建模结果,并与基于产生规则的算法进行了比较。实际意义——本文提出的空中目标分组算法比空间频闪分组算法和基于产生规则的分组算法效率更高。这在若干组在相交轨迹上向空中物体飞行的情况下尤其明显。该算法对雷达综合体的计算系统要求不高,可以不受限制地在实际中实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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