Fig. 1. Detection technology for small targets of low-altitude unmanned aircraft

Fig. 2. Acoustic signal processing algorithm for UAV targets. (a) The power spectral densities of different unmanned aerial vehicles^[17]; (b) the acoustic signal detection process of UAV based on IVA^[21]; (c) the detection accuracy rate of LPCC based on SVM^[18]; (d) the detection accuracy rate of MFCC based on SVM^[18]

Fig. 3. Radar detection scene and TVD^[24]. (a) Radar actual test scene; (b) TVD of a UAV

Fig. 4. Typical radio frequency signal processing flow^[27]. (a) Processing flow; (b) spectrum with UAV; (c) spectrum without UAV

Fig. 5. Comparison of recognition effects between YOLOv8s and SEB-YOLOv8s^[36]. (a) The recognition effect of YOLOv8s; (b) the recognition effect of SEB-YOLOv8s

Fig. 6. Classification of spectral imaging^[38]. (a) Scanning spectral imaging; (b) snapshot spectral imaging

Fig. 7. Different modulation-demodulation spectral imaging techniques and modulation-demodulation process^[46-50]. (a) Photonic crystal system; (b) quantum dot system; (c) metamaterial system; (d) modulation-demodulation process

Fig. 8. Typical wide-spectrum modulation-demodulation snapshot spectral imaging system and its development history^[49-54]

Fig. 9. Flowchart of the KCF tracking UAV algorithm^[58]

Fig. 10. Snapshot spectral imaging UAV small target detection system. (a) UAV small target detection system; (b) multi-spectral band images

Fig. 11. Single-band spectral images in different scenarios. (a) Sky background; (b) building-occluded background; (c) cloud-occluded background

Fig. 12. Detection results of unmanned aerial vehicle targets in different complex scenarios. (a) Sky background; (b) cloud-occluded background; (c) building-occluded background