基于支持向量回归的多无人机雷达定位

B. Sundaram, M. Palaniswami, S. Reddy, M. Sinickas
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引用次数: 11

摘要

本文首次尝试使用支持向量回归(SVR)来解决地理定位问题。本文提出了一种利用雷达对以固定三角形编队飞行的3架不同的无人机发射的相同特征脉冲的到达时差(TDoA)来精确定位静止敌方雷达的方法。将提出的SVR方法的性能与用于解决相同问题的泰勒级数方法(TSM)的一种变体进行了比较,该方法目前由澳大利亚DSTO部署在Aerosonde Mark III无人机上。探讨了SVR方法对误差的鲁棒性,并与TSM方法进行了比较。提出了SVR方法在无线传感器网络中更一般的定位场景中的扩展应用
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Radar Localization with multiple Unmanned Aerial Vehicles using Support Vector Regression
This paper presents a first attempt to solve the geolocation problem using support vector regression (SVR). This paper proposes a method to pinpoint the location of stationary, hostile radar using the time difference of arrival (TDoA) of the same characteristic pulse emitted by the radar at 3 different unmanned aerial vehicles (UAVs) flying in a fixed triangular formation. The performance of the proposed SVR method is compared with a variation of the Taylor series method (TSM) used for solving the same problem and currently deployed by the DSTO, Australia on the Aerosonde Mark III UAVs. The robustness to error of the SVR method is explored and compared with the TSM. Extended applications of the SVR approach to more general localization scenarios in wireless sensor networks are proposed for further work
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