Tracking Position of Airborne Target on SPx-Radar-Simulator Using Probabilistic Data Association Filter

M. Sahal, Zaidan Adenin Said, Rusdhianto Effendi Abdul Kadir, Z. Hidayat, Y. Bilfaqih, Abdullah Alkaff
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引用次数: 1

Abstract

Radar has various functions, one of which is tracking the position of targets in the air. In tracking the target position, there are obstacles, namely the uncertainty of data associations. To overcome the uncertainty of data associations, the concept of data association can be used where one of the algorithms that use this concept is the Probabilistic Data Association Filter (PDAF). A single target position tracking system in the air will be tested on radar using the PDAF with our proposed maintenance track algorithm. The data used for testing comes from simulating two motions on the SPx-Radar-Simulator. False alarms originating from interference (clutter) will be generated in the environment around the simulated target. The test results of the target tracking system using the PDAF algorithm that has been designed can track targets well, maintain tracking conditions in an environment that has clutter, and maintain track on multitarget environments. The error between the original data and the prediction on the validated target has a relatively small value, although there is a relatively significant difference in the error of the altitude data when the motion has varying altitude conditions.
基于概率数据关联滤波的spx -雷达模拟器机载目标跟踪
雷达具有多种功能,其中之一是跟踪空中目标的位置。在跟踪目标位置时,存在着障碍,即数据关联的不确定性。为了克服数据关联的不确定性,可以使用数据关联的概念,其中使用该概念的算法之一是概率数据关联过滤器(PDAF)。利用PDAF和我们提出的维护跟踪算法,在雷达上对空中单目标位置跟踪系统进行了测试。用于测试的数据来自于在spx雷达模拟器上模拟两个运动。在模拟目标周围的环境中会产生由干扰(杂波)引起的虚警。实验结果表明,采用所设计的PDAF算法的目标跟踪系统可以很好地跟踪目标,在杂波环境下保持跟踪条件,在多目标环境下保持跟踪。当运动具有不同高度条件时,虽然高度数据的误差有比较显著的差异,但原始数据与对验证目标的预测之间的误差值相对较小。
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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