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Due to the pervasive deployment of Wi-Fi devices, Wi-Fi-based human intrusion detection has attracted intensive attention in recent years. By analyzing temporal changes of signal caused by human movement, the existing solutions can achieve passive human intrusion detection. However, the detection of intrusion direction, from which the person intrudes the area of interests, is still a challenging task. Considering the influence of intrusion direction on the energy and spatial statistical distributions of multiple reflections, in this study, we propose WIDD, a Wi-Fi-based passive human intrusion direction detection system. Concretely, WIDD first extracts the angle of arrival (AoA) and amplitude distributions of the multipath signal and conducts the Jarque-Bera (JB) test to analyze the normality of the obtained distributions. A novel joint hypothesis testing algorithm is proposed to monitor changes in amplitude and AoA …