Adjoint-based identification of freely moving sound sources

如今，通常使用麦克风阵列方法来定位和识别声源。在时域和频域中进行信号处理的方法之间进行区分。此外，通常分为基于波束形成的方法和逆方法。所有方法的共同之处在于，如果由于测量时间短而导致信噪比非常高并且必须考虑反射边界，则低频声源的确定特别成问题。对于自由移动的声源尤其如此。该项目的目的是开发、实施和验证一种基于伴随的方法，用于识别相应的声源。几个声源的时变位置、它们的信号以及同时它们的方向特性将基于麦克风阵列测量来确定。时域方法将能够识别低频源，并根据少量的测量数据及时将它们彼此分离。该方法及其实现对合成数据进行了验证。此外，它是测试与实验数据，特别是火车通道和四轴飞行器飞越，并与其他已经建立的方法进行比较。

Today, typically microphone array methods are used to localize and identify sound sources. A distinction is made between methods with signal processing in the time domain and the frequency domain. Besides, a division into beamforming-based methods and inverse methods is common. What all methods have in common is that the determination of sound sources at low frequencies is particularly problematic if the signal-to-noise ratio is very high due to short measurement times and reflective boundaries have to be taken into account. This is especially true for freely moving sound sources. The aim of this project is the development, implementation, and validation of an adjoint-based method for the identification of corresponding sound sources. The time-varying positions of several sound sources, their signal, and, at the same time, their directional characteristics are to be determined based on microphone array measurements. The time-domain method will be able to identify low-frequency sources and separate them from one another based on a small amount of measurement data in time. The method and its implementation are validated against synthetic data. Besides, it is tested with experimental data, in particular train passages and quadcopter overflights, and compared with other already established methods.