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Emitter geolocation using low-accuracy direction-finding sensors

机译:使用低精度测向传感器的发射器地理位置

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This paper examines the concept of replacing a few expensive high-accuracy radio direction-finding (DF) sensors operating in a stand-off baseline with many low-accuracy DF sensors deployed on existing military vehicles located throughout an area of interest. A formula is presented to estimate the geolocation accuracy that could be achieved for a given number of sensors with a specified DF accuracy. Monte Carlo and virtual simulation of sensors with varying DF accuracy is used to assess the accuracy and reliability of the geolocation estimates that could be achieved. Geolocation results are computed using Stansfield's method and a technique developed at DRDC Ottawa, called the Discrete Probability Density (DPD) method, and compared to the theoretical location accuracy limit predicted by the Cramer-Rao Lower Bound. The DPD method is shown to provide more accurate and more reliable geolocation estimates than Stansfield's method when incorporating large quantities of low-accuracy DF data. This suggests that the DPD method could be used with several less-expensive low-accuracy DF sensors to provide improved emitter geolocation capability compared to the conventional deployment of a few high-accuracy DF sensors.
机译:本文研究了用部署在整个感兴趣区域的现有军用车辆上部署的许多低精度DF传感器替换在对峙基线下运行的一些昂贵的高精度无线电测向(DF)传感器的概念。给出了一个公式来估算对于给定数量的具有指定DF精度的传感器可以实现的地理位置精度。蒙特卡罗(Monte Carlo)和具有不同DF精度的传感器的虚拟仿真用于评估可以实现的地理位置估计的准确性和可靠性。地理定位结果是使用斯坦斯菲尔德(Stansfield)方法和渥太华DRDC开发的一种称为离散概率密度(DPD)方法的技术计算的,并与Cramer-Rao下界预测的理论位置精度极限进行比较。当合并大量低精度DF数据时,显示出DPD方法可提供比Stansfield方法更准确,更可靠的地理位置估计。这表明,与一些高精度DF传感器的常规部署相比,DPD方法可与几种价格较低的低精度DF传感器一起使用,以提供改进的发射器地理定位功能。

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