未爆弹药
计算机科学
小波
遥感
爆炸物探测
磁强计
信噪比(成像)
声学
地质学
人工智能
物理
爆炸物
磁场
电信
化学
有机化学
量子力学
作者
Ying Shen,Zhiyue Chen,Junqi Gao,Pengfei Zhang,Xiaobao Yang
标识
DOI:10.1109/lgrs.2025.3528102
摘要
Utilizing a rotor drone equipped with a magnetometer presents a practical solution for rapidly surveying unexploded ordance (UXO) areas potentially buried underground. This method effectively reduces operational risks and enhances overall efficiency. Our study has developed an aeromagnetic gradient detection system featuring a scalar sensor mounted on a rotor-based unmanned aerial vehicle(UAV). Experimental results affirm the effectiveness of differential processing in mitigating common-mode noise from the carrier platform and in neutralizing the impact of geomagnetic gradients. The system's dynamic noise is Si=0.013 nT. The wavelet entropy reduction algorithm, utilizing a 'sym6' wavelet basis with j=4 wavelet decomposition, increases the low signal-to-noise ratio SNR= -0.78 dB to 8.46 dB, thereby improving the detection of weak magnetic signals. The system's ultimate depth detection capability for eight buried unexploded bombs has been quantified: the H30, with a length of 17 cm and a mass of 0.3 kg, has a maximum detection range of H=120 cm; the 120 mm caliber projectile, with a length of 240 cm and a mass of 25.8 kg, achieves a maximum detection range of H=550 cm. Such detection capability meets practical detection needs. Furthermore, we perform 50 test sets to assess its detection performance, with four types UXOs randomly placed within a 450 m 2 area. It took 270 seconds to scan the 450 m2 area and 60 seconds to process data . The system demonstrates a correct detection rate of 94.5% while maintaining a false alarm rate of 2%.
科研通智能强力驱动
Strongly Powered by AbleSci AI