Evaluation of a model based data fusion algorithm with multi-mode OTHR data

I. Dall, A.J. Shellshear
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引用次数: 7

Abstract

Australia's over-the-horizon-radar system, the Jindalee Operational Radar Network, is due to be commissioned in 1997. When operating it is possible that associated tracks of one aircraft may arise from multiple propagation paths and multiple radars. Errors in estimating the propagation path result in errors in estimating the position of the aircraft. Also, the structure of the ionosphere typically supports several propagation modes and it may not be certain which mode caused each track. Generally, association of data from multiple sensors requires that the data be aligned in all its coordinates. If the propagation modes are uncertain, then alignments are compromised. This paper presents the results of applying a previously presented multi-mode multi-radar fusion algorithm to the experimental Jindalee Facility Alice Springs (JFAS) data. The algorithm, which is briefly summarised, uses a simple model of propagation to convert between radar coordinates and latitude-longitude coordinates. The algorithm has been applied to ten days of JFAS data. The results are shown to be comparable to operator performance, with indications that more improvements can be made. The difficulties of evaluating data fusion algorithms are discussed and it is concluded that development of data fusion algorithms is best done with both simulated and synoptic data.<>
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基于模型的多模式OTHR数据融合算法评价
澳大利亚的超视距雷达系统,金达莱作战雷达网络,将于1997年服役。操作时,一架飞机的相关轨迹可能来自多个传播路径和多个雷达。估计传播路径的误差会导致估计飞机位置的误差。此外,电离层的结构通常支持几种传播模式,可能无法确定哪种模式导致每种轨道。通常,来自多个传感器的数据关联要求数据在其所有坐标上对齐。如果传播模式不确定,则会损害对齐。本文介绍了将一种多模式多雷达融合算法应用于金达利设施爱丽丝泉(JFAS)实验数据的结果。该算法采用一种简单的传播模型,在雷达坐标和经纬度坐标之间进行转换。该算法已应用于JFAS 10天的数据。结果显示,与运营商的性能相当,并表明可以进行更多改进。讨论了评估数据融合算法的困难,并得出结论,数据融合算法的开发最好同时使用模拟数据和天气数据。
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