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Multifunctional Software-Defined Radar Sensors for Detection, Imaging, and Navigation
Published in Reza Mahmoudi, Krzysztof Iniewski, Low Power Emerging Wireless Technologies, 2017
Dmitriy Garmatyuk, Kyle Kauffman, Y. T. (Jade) Morton, John Raquet
Multifunctional radio frequency (RF) sensors are a natural evolution of radar. When first deployed in World War II, the early radar systems were tasked with estimating the range to the potential targets of interest only, and even due to this single functionality it has been claimed that it “is obvious that radar transformed the nature of war more than has any other single invention” [1]. Less than two decades after this triumphant entrance, the radar functionalities were enriched with imaging [2]. This, too, signaled a fundamental change in a number of fields—from the military, which could now perform all-weather, day or night surveillance of obscured targets [3], to the civilian applications of radar, such as monitoring ice sheets or obtaining imagery of space bodies [4]. In parallel, the radar as a navigational tool was also explored, primarily for airborne and seaborne navigation [5]. Once these capabilities were established, the need to distinguish between the targets and objects of different shapes and dimensions quickly emerged and, with it, the automatic target recognition (ATR) field [6]. Thus, the functionalities of imaging and detection began to converge.
Classification of Vehicles with High-Speed Airborne Radar Based on Micro-Doppler Signatures
Published in IETE Technical Review, 2018
Xin-yi Li, Yin-he Huang, Kui-ying Yin, Yin-qi Qiao
It is less than twenty years since Victor C. Chen brought the concept of micro-Doppler to radar field. However, micro-Doppler signatures have been widely used in a variety of researches in radar Automatic Target Recognition (ATR). According to different targets, these researches can be sorted to four categories: space targets such as ballistic missile warhead [1,2], aerial targets such as planes [3,4], ground targets such as tracked and wheeled vehicles [5–7] and biological targets such as human [8,9]. Specially, in classification of moving ground targets, almost all of the existing researches are done with stationary radar. Researchers employ stationary radar for return signal and then extract features like entropy in frequency domain, energy ratio and harmonic number, using signal processing methods like Empirical Mode Decomposition and Wavelet Transform [10].