Application of Radar Solutions for the Purpose of Bird Tracking Systems Based on Video Observation

Abstract

Wildlife Hazard Management is nowadays a very serious problem, mostly at airports and wind farms. If ignored, it may lead to repercussions in human safety, ecology, and economics. One of the approaches that is widely implemented in small and medium-size airports, as well as on wind turbines is based on a stereo-vision. However, to provide long-term observations allowing the determination of the hot spots of birds’ activity and forecast future events, a robust tracking algorithm is required. The aim of this paper is to review tracking algorithms widely used in Radar Science and assess the possibilities of application of these algorithms for the purpose of tracking birds with a stereo-vision system. We performed a survey-of-related works and simulations determined five state-of-the art algorithms: Kalman Filter, Nearest-Neighbour, Joint-Probabilistic Data Association, and Interacting Multiple Model with the potential for implementation in a stereo-vision system. These algorithms have been implemented and simulated in the proposed case study

An Application of Analytic Wavelet Transform and Convolutional Neural Network for Radar Intrapulse Modulation Recognition

“…Therefore, faster adaptive methods, such as the one presented in [ 50 ], even if with relatively lower classification accuracy, are preferable over those that are slower with higher classification rates. Moreover, an interesting alternative worthy of consideration is information fusion methods, referred to in [ 11 ], which, apart from the neural-network-based solutions, deliver analytical methods. This may be particularly attractive due to the mentioned speed requirement assessed on the optimizing methods.…”

“…The problem of intrapulse modulation recognition with a fusion network is presented in [ 4 ]. Data fusion techniques are successfully used in areas such as tracking systems [ 11 ] or multisensory systems for unnamed aerial vehicles (UAV) detection [ 12 ].…”