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首页> 外文期刊>IEEE Transactions on Robotics >Necessary and Sufficient Conditions for Observability of SLAM-Based TDOA Sensor Array Calibration and Source Localization
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Necessary and Sufficient Conditions for Observability of SLAM-Based TDOA Sensor Array Calibration and Source Localization

机译:基于SLAM的TDOA传感器阵列校准和源定位的可观察性的必要和充分条件

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Sensor array-based systems, which adopt time difference of arrival (TDOA) measurements among the sensors, have found many robotic applications. However, for existing frameworks and systems to be useful, the sensor array needs to be calibrated accurately. Of particular interest in this article are microphone array-based robot audition systems. In our recent work, by using a moving sound source, and the graph-based formulation of simultaneous localization and mapping (SLAM), we have proposed a framework for joint sound source localization and calibration of microphone array geometrical information, together with the estimation of microphone time offset and clock difference/drift rates. However, a thorough study on the identifiability question, termed observability analysis here, in the SLAM framework for microphone array calibration and sound source localization, is still lacking in the literature. In this article, we will fill the abovementioned gap via a Fisher information matrix approach. Motivated by the equivalence between the full column rankness of the Fisher information matrix and the Jacobian matrix, we leverage the structure of the latter associated with the SLAM formulation, and present necessary and sufficient conditions guaranteeing its full column rankness, which lead to parameter identifiability. We have thoroughly discussed the 3-D case with asynchronous (with both time offset and clock drifts, or with only one of them) and synchronous microphone array, respectively. These conditions are closely related to the motion varieties of the sound source and the microphone array configuration, and have intuitive and physical interpretations. Based on the established conditions, we have also discovered some particular cases where observability is impossible. Connections with calibration of other sensors will also be discussed, amongst others. To our best knowledge, this is the first systematic work on observability analysis of SLAM-based microphone array calibration and sound source localization. The tools and concepts used in this article are also applicable to other TDOA sensing modalities such as ultrawide band (UWB) sensors.
机译:基于传感器阵列的系统,在传感器中采用到达时间差(TDOA)测量,发现了许多机器人应用。但是,对于现有框架和系统有用,需要准确地校准传感器阵列。本文特别兴趣的是基于麦克风阵列的机器人试镜系统。在我们最近的工作中,通过使用移动的声源和基于图形的同时定位和映射(SLAM)的制定,我们提出了一种用于联合声源定位和麦克风阵列几何信息校准的框架,以及估计麦克风时间偏移和时钟差/漂移率。然而,在麦克风阵列校准和声源定位的SLAM框架中,对可识别性问题进行了彻底的研究,可观察性分析,在文献中仍然缺乏。在本文中,我们将通过Fisher信息矩阵方法填补上述差距。通过Fisher信息矩阵的全柱级和雅可比矩阵之间的等效性,我们利用了与SLAM制剂相关的后者的结构,并提供了保证其全柱秩的必要和充分条件,这导致参数可识别性。我们已经彻底讨论了使用异步(具有时间偏移和时钟漂移,或仅具有其中一个)和同步麦克风阵列的三维情况。这些条件与声源的运动品种和麦克风阵列配置密切相关,并具有直观和物理的解释。根据既定条件,我们还发现了一些特殊情况,可观察性是不可能的。其他传感器的校准也将在其他传感器中进行连接。为了我们的最佳知识,这是对基于SLAM的麦克风阵列校准和声源定位的可观察性分析的第一个系统工作。本文中使用的工具和概念也适用于其他TDOA感测模式,如超广域带(UWB)传感器。

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