Abstract
The detection of a human being behind obstacles using radar technology has many promising applications, such as postdisaster search and rescue missions. In the case of large observation areas, the use of an unmanned aerial vehicle as the moving platform for radar is an appealing approach. However, this task is challenging because human vital signs provide a relatively weak signal compared with background noise and clutter. The drone's instability also negatively affects the obtained radar signal. Thus, this article presents a new signal processing method to extract and enhance respiration signals from drone-mounted radar. The method works by extracting the analytic signal representation and applying the subspace component segregation. Laboratory experiments in a controlled environment show that the proposed method can suppress a considerable level of vibration generated by unbalanced motor motion and enhance the respiration signal from radar data. A field experimental study using an octocopter in hovering mode confirms the method performs well in real-world conditions.
Highlights
N ATURAL disasters occur frequently and can result in both material and nonmaterial losses [1], [2]
The use of unmanned aerial vehicles or drones for search and rescue (SAR) missions in postdisaster environments is of interest to many researchers
The actual respiration signal from the actuator was at a frequency of 0.6 Hz with a displacement of 3 mm located in a sample of around 350 samples in fast time domain
Summary
N ATURAL disasters occur frequently and can result in both material and nonmaterial losses [1], [2]. The use of such sensors has been shown to offer high performance in both laboratory and field applications [5], [6] With this potential in mind, we are building a multisensory drone system for supporting SAR missions in complex and chaotic disaster-affected areas [7], [8] (see Fig. 1). To detect a buried survivor, we adopt through-the-wall detection using a UWB radar technique This technology is of interest to researchers worldwide due to its many promising applications to fields including law enforcement, military, and SAR missions. Use of subspace decomposition to the recorded radar signal on the time and frequency domain has been proposed in [11] and [12], respectively This method aims to suppress the clutter by experimentally selecting the appropriate subspace components based on its singular values so that the signals from a human behind a wall can be enhanced.
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