## 1 Introduction  
After a natural disaster, the rapid and effective rescue of trapped individuals within collapsed structures has paramount importance since the window of survival in such scenarios is limited [1]. Efficient procedures and the timely deployment of appropriate rescue resources are crucial for reaching survivors within the critical timeframe [2, 3, 4]. Technological tools, such as acoustic detectors, trained canines, snake camera robots, and high-sensitivity microphones, are used by search and rescue teams to detect survivors. However, each method possesses inherent limitations when deployed in a complex debris field [5]. Thus, it is imperative to use a reliable sensing device that can detect living victimsin the debris. Over the years, there has been a growing interest in utilizing remote sensing technologies for the detection of living humans, especially as part of search and rescue operations [6]. Radar technology has emerged as a particularly effective tool for this purpose, enabling the detection of human breathing and movement under debris [7]. By analyzing the reflected electromagnetic waves from the debris area, radar devices can distinguish the presence of objects in the environment, including individuals trapped in collapsed structures. Specialized radar technology further improves this capability by detecting vital signs such as heartbeats, breathing, and body movements under debris conditions [8; 9]. Various radar types, such as pulse radar, continuous wave radar, and Doppler-based methods, have been used for detecting trapped victims in collapsed buildings [10; 11; 12; 13]. Recently, ultra-wideband (UWB) radar systems have emerged as promising tools for penetrating debris and detecting vital signs such as respiration and movement responses. The integration of Doppler techniques with UWB radars has enabled the detection of micro-movements indicative of living individuals [14; 15; 16]. Despite the challenges associated with higher frequencies and penetration depth, UWB radar systems have demonstrated impressive performance in detecting individuals buried under debris, thus enhancing the efficiency of the search and rescue teams significantly [17; 18; 19; 20]. The heterogeneity of the environment is the main difficulty that radar systems face. Building wreckage is a heterogeneous environment with various structural components, such as concrete, wood, cement, aggregate, and brick, each of which has different compositions and positioning [21]. This heterogeneity causes scattering of the electromagnetic waves, thereby reducing the detection depth. Prior work, such as [22], has demonstrated high accuracy in detecting weak ranging signals in FoV scenarios using mmWave radar at 60-64 GHz. This method leverages range profile variations and clutter removal techniques to identify a human presence before proceeding to respiration monitoring. In [22], by using Alpha filtering in the Fourier transform of the FMCW intermediate signal, the environmental clutter is significantly reduced, and weak signals from the subject can be observed. The study shows that the detection rate is increased, especially when the object sits behind the radar. Furthermore, several studies highlight the significance of reducing clutter and mitigating signal attenuation through dense materials in post-disaster scenarios, especially for locating survivors and critical assets [23; 24]. These approaches employ specialized radar methods and advanced signal processing algorithms to enhance detection accuracy under extreme conditions [25]. Additionally, there is a further complication in signal detection due to the clutter of moving objects, which causes difficulty in discriminating human movement from noise [26]. This issue can be addressed by denoising the stationary clutter through advanced signal processing techniques [27]. The detection of a human presence within the debris is still an important scientific and technological issue that requires additional solutions with higher detection accuracy and depth.