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Bias phenomenon and analysis of a nonlinear transformation in a mobile passive sensor network

机译:移动无源传感器网络中的偏见现象和非线性变换分析

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In this article, we consider the bias issue in a passive tracking system which utilizes a mobile passive sensor network, where bearing-only sensors such as Inferred or ESM are used. Biases due to nonlinear transformations have already been recognized, but have not been studied for this particular case of converted pseudo measurements in a mobile passive sensor network. Based on the Taylor series, the bias equations for a network of two passive sensors are derived. Monte Carlo simulation is used for analysis. There are two other non-linear transformations which are related to this study: 1. range/azimuth to X/Y; 2. range/azimuth to latitude/longitude. Insightful studies with explicit expressions are available for the first nonlinear transformation, but not for the second and the new nonlinear transformations. This article will provide an approximate solution and simulation study for the new nonlinear transformation.
机译:在本文中,我们考虑了利用移动式无源传感器网络的无源跟踪系统中的偏差问题,该网络中仅使用诸如Inferred或ESM之类的方位传感器。已经认识到由于非线性变换引起的偏差,但尚未针对移动无源传感器网络中这种转换后的伪测量的特殊情况进行过研究。基于泰勒级数,推导了两个无源传感器网络的偏置方程。蒙特卡洛模拟用于分析。还有另外两个与这项研究有关的非线性变换:1.范围/方位角到X / Y; 2.范围/方位角到纬度/经度。具有显式表达式的有见地的研究可用于第一个非线性变换,但不适用于第二个和新的非线性变换。本文将为新的非线性变换提供一个近似的解决方案和仿真研究。

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