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Robust bearing estimation in the presence of direction-dependent modelling errors: identifiability and treatment

机译:在存在与方向有关的建模误差的情况下的可靠轴承估计:可识别性和处理

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This paper presents identifiability and treatment relative to bearing estimation in presence of modelling errors. It introduces the general case of direction-dependent modelling errors. The classical direction-independent case is only a particular case which takes into account a prior knowledge. This general case introduces the important issue of simultaneous sources and perturbation identifiability which is analysed. A new self-calibration technique based on MUSIC algorithm and which is able to treat direction-dependent errors is also proposed. For the purpose of regularization, a "cost term" is introduced in this algorithm. It confers good robustness to the algorithm which usually fails in the presence of great gap between the model and reality. After reduction of the new multidimensional "increased function", values of azimuths are easily obtained on a monodimensional spectrum. Some simulations support results and verify the improvements expected from the theory.
机译:本文介绍了在存在模型错误的情况下相对于方位估计的可识别性和处理方法。它介绍了与方向有关的建模错误的一般情况。经典的与方向无关的情况只是考虑到先验知识的特定情况。这个一般案例引入了同时源和扰动可识别性的重要问题,并对其进行了分析。提出了一种新的基于MUSIC算法的自校准技术,该技术能够处理与方向有关的误差。为了进行正则化,在此算法中引入了“成本项”。它赋予算法良好的鲁棒性,而该算法通常在模型与实际情况之间存在较大差距时会失败。在减少了新的多维“增加的函数”之后,很容易在一维频谱上获得方位角的值。一些仿真结果支持并验证了该理论所期望的改进。

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