Detection of unmanned aerial vehicle signal based on Gaussian mixture model

With the innovation and development of unmanned aerial vehicle(UAV) technology, small UAV has also begun to attract the people's attention. Because of its characteristic of remote control, small size, low cost and other advantages, it already has a wide range of applications. However, the management of UAV has become a common problem throughout the world. It is a prerequisite which is how to detect UAV. Nowadays, the wireless signal of the UAV can help us detect it. In the low-altitude environment, due to the impact of noise, the first step is to identify the start-point of its single accurately. A detection algorithm for UAV signals with an adaptive threshold based on Gaussian mixture model(GMM) is proposed in this paper. The algorithm makes full use of the signal data characteristics, calculates the threshold using the GMM. Meanwhile, it does not need to set the fixed threshold manually. That means it can adaptively detect the wireless signal in a different noise environment.