Localization algorithms for multilateration (MLAT) systems in airport surface surveillance
Localization algorithms for multilateration (MLAT) systems in airport surface surveillance
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DOI：
10.1007/s11760-013-0608-1
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发表时间：
2015-10-01
影响因子：
2.3
通讯作者：
Balbastre-Tejedor, Juan V.
中科院分区：
文献类型：
--
作者：
Mantilla-Gaviria, Ivan A.;Leonardi, Mauro;Balbastre-Tejedor, Juan V.
我们提出了一个通用的定位算法的性能分析（MLAT）系统（或其他分布式传感器，被动定位技术）的一般计划。MLAT系统用于机场地面监视，并基于S模式信号（应答和1090 MHz扩展断续发射器，或1090 ES）的到达时间差测量。在本文中，我们建议考虑定位算法由两个组成部分：数据模型和数值方法，都被适当地定义和描述。以这种方式，定位算法的性能可以与统计和数值性能的适当组合相关。我们提出并回顾了一组数据模型和数值方法，可以描述大多数定位算法。我们还选择了一组现有的定位算法，可以被认为是最相关的，我们描述了他们提出的分类。我们表明，任何定位算法的性能有两个组成部分，即，一个是统计学上的，一个是数值上的统计性能与提供无偏和最小方差解有关，而数值性能与确保解的收敛有关。此外，我们表明，一个强大的定位（即，统计和数值效率）策略，用于机场表面监视，必须由两种特定的算法组成。最后，利用真实的数据对所分析的算法进行了精度分析，得出了一些一般性的准则和结论。
We present a general scheme for analyzing the performance of a generic localization algorithm for multilateration (MLAT) systems (or for other distributed sensor, passive localization technology). MLAT systems are used for airport surface surveillance and are based on time difference of arrival measurements of Mode S signals (replies and 1,090 MHz extended squitter, or 1090ES). In the paper, we propose to consider a localization algorithm as composed of two components: a data model and a numerical method, both being properly defined and described. In this way, the performance of the localization algorithm can be related to the proper combination of statistical and numerical performances. We present and review a set of data models and numerical methods that can describe most localization algorithms. We also select a set of existing localization algorithms that can be considered as the most relevant, and we describe them under the proposed classification. We show that the performance of any localization algorithm has two components, i.e., a statistical one and a numerical one. The statistical performance is related to providing unbiased and minimum variance solutions, while the numerical one is related to ensuring the convergence of the solution. Furthermore, we show that a robust localization (i.e., statistically and numerically efficient) strategy, for airport surface surveillance, has to be composed of two specific kind of algorithms. Finally, an accuracy analysis, by using real data, is performed for the analyzed algorithms; some general guidelines are drawn and conclusions are provided.