## 1 Introduction  
Rockfalls, among the most prevalent geological hazards globally, occur abruptly, boast significant destructive potential, and are broadly distributed, thereby posing substantial threats to human life and infrastructure. On 14 August 2019, a substantial rockfall involving tens of thousands of cubic meters of rock occurred along the Chengkun Railway between Lianghong and Edai stations, damaging the railway infrastructure [1]; similarly, on 30 March 2020, a train derailment was triggered by a landslide along the Beijing-Guangzhou railway [2]. As the railway network continues to expand, particularly through complex and hazardous mountainous terrains, the reliance on sophisticated foreign object detection systems becomes essential [3]. Traditional railway foreign object intrusion detection relies on manual inspections, which are time-consuming, labor-intensive, and often lack high accuracy. In recent years, an array of automated foreign object detection technologies has been implemented in railway operation and maintenance for safety management, including grid, fiber Bragg grating, video, ultrasonic, and infrared detection methods [4]. These automated methods offer significant improvements over traditional manual detection in terms of efficiency, cost reduction, and enhanced stability and accuracy. Detection methods are broadly classified into two categories by researchers: contact and non-contact detection [4]. Contact detection methods, which include grid detection and fiber Bragg grating detection, involve acquiring information through direct or indirect interaction between the sensor and the foreign object. Conversely, non-contact detection methods, such as ultrasonic, infrared, and video detection, obtain parameter information about the intrusive object without any physical contact with its surface. Researchers have also conducted extensive work in the area of contact-based detection. [PERSON] [5] designed a railway foreign object intrusion detection system utilizing fiber Bragg grating stress sensors instead of traditional electrical sensors for the sensing module in railway foreign object intrusion monitoring. [PERSON] et al. [6] devised a system that utilizes broadband Boolean chaotic signals for detection, employing a pair of leaky coaxial cables (LCX) to transmit the detection signal and receive the echo signal. Through comparison of the chaotic echo signal with its delayed repetition signal and analysis of the correlation trajectories before and after an intrusion, they introduced a foreign object intrusion detection system relying on leaky coaxial cables. [PERSON] [7] enhanced traditional approaches by incorporating a layer of netting above and below the protective net, examining the distinct fracture waveforms induced by external forces, thereby proposing a novel foreign object intrusion monitoring scheme grounded in smart dual-electric grid technology. The contact detection method is challenging to deploy due to its reliance on sensor triggers and secondary signal transmission, resulting in a limited detection range. Additionally, manual reinspection is required for daily use. In contrast to contact detection methods, [PERSON] et al. [8] employed computer software to acquire thermal images, calculate scene geometries, detect railways, and identify potential obstacles, subsequently issuing alerts to drivers based on predefined criteria. [PERSON] et al. [9] proposed a railway foreign object detection system that utilizes signal encoding based on complementary sequence pairs and employs optical transmitters. The non-contact detection method offers a longer monitoring distance, wider range, and higher reliability in comparison to the contact detection method. Compared to contact-based detection methods, non-contact approaches offer longer monitoring distances, broader coverage, and higher reliability. However, the effectiveness of detection is still subject to instability due to factors such as sensor sensitivity, infrared thermal radiation, and background radiation.