Microphone arrays can be used for many purposes, or goal is the determination of the position of sound sources. The estimation of the position is based on the Delay-and-Sum method, which can be used to focus on different points in the space, and to create sound maps representing the source distribution. This method can be enhanced further with different beamforming algorithms, for example with Multiple Signal Classification (MUSIC), or Functional Beamforming (FB). These algorithms all have their strength and weakness, and their main beam width, side lobe strength, computational cost etc. must be considered. Beamforming algorithms complemented with the Kalman-filter algorithm is suitable for tracking non- stationary sources as well. Our goal is to evaluate these methods through simulations and measurements. The measurement data is acquired from Unmanned Aerial Vehicles (UAVs) acting as sound sources in an outdoor environment with less-than-ideal environmental conditions. Due to this, the results indicate the efficiency of the algorithms when used in real-life applications, and their limitations, so that improvements can be made to the methods for increased efficiency, accuracy and robustness.