Kalman filter and ARMA filter as approach to multiple sensor data fusion problem

M. A. Munoz Gutierrez, J. A. Florez Zuluaga, S. Kofuji
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引用次数: 2

Abstract

The Air Traffic Control (ATC) systems are critical due the amount of information that they have to process in real time. These systems combined different kind of information, like primary and secondary radar information and flight planning information. Depending the extent of a country different RADAR are installed trying to cover most of the country area. This could become a problem, because different RADAR can detect and locate the same object at different position on the map, this is a multiple sensor data fusion problem. In this paper we present a technique that combines conventional Kalman filter techniques with an ARMA filter to provide a solution to the problem. Multiple objects tracking examples are presented.
卡尔曼滤波和ARMA滤波在多传感器数据融合中的应用
空中交通管制(ATC)系统至关重要,因为它们必须实时处理大量信息。这些系统结合了不同类型的信息,如初级和次级雷达信息以及飞行计划信息。根据一个国家的面积不同,安装的雷达试图覆盖该国的大部分地区。这可能会成为一个问题,因为不同的雷达可以在地图上的不同位置检测和定位相同的物体,这是一个多传感器数据融合问题。在本文中,我们提出了一种将传统卡尔曼滤波技术与ARMA滤波器相结合的技术来解决这个问题。给出了多目标跟踪实例。
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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