## 2 Bimodal Information Collection System
### The Optimized Multispectral Sensing Module  
The multispectral sensing (MSS) module on a cruising UAV at high altitude is used to acquire some specific spectral features of the target background for suspected human targets detection, which is referred to in _stage 1_ in Figure 3 during the entire search process. In our study, a few multispectral bans are specifically selected by observing and analyzing the sensitivity of different spectral bands to the environment and background. Consequently, some optimal bands would be picked out from numerous hyperspectral bands, which has the greatest ability to distinguish suspected human targets from the natural environment with complex background situations. Since the relative reflectivity was defined as follows:  
\[R_{relative}=\frac{L_{subject}}{L_{board}}.R_{board} \tag{1}\]  
where \(R_{relative}\) and \(R_{board}\) are the reflectivity of subject and reference board, \(L_{subject}\) and \(L_{board}\) are the spectral radiance of subject and reference board. According to the spectral curve, we could pick out corresponding characteristic points which are promising to distinguish green clothes from grassland. In our study, a large number of preliminary measurement experiments were carried out to obtain the wavelength-relative reflectivity curve for green vegetation (to simulate background) and green camouflage (to simulate suspected injured human target outdoors) using a spectrometer. Here, the ATP9100 portable object spectrometer was used to measure the current spectral parameters of ground objects (wavelength range of 300-1100 nm, 2048-pixel CCD detector, spectral resolution of 1.4 nm, wavelength accuracy of 0.5 nm, and signal-to-noise ratio > 800) [28]. The instrument parameters are set as follows: automatic integral time, multiple detections, and followed with dark-current correction. Specifically, we measured three times the ground objects in one validation experiment. The measurement duration is 1-10 s and they will be integrated optimally. Then, the average spectral parameters of ground objects could be acquired by averaging. Finally, the spectral reflectance curve of green clothes and green vegetation can be acquired as shown in Figure 4.  
Figure 3: Suspected target detection and human nature re-identification based on UAV bio-modal information from multispectral camera and bio-radar. Target recognition based on single-band features is vulnerable and unstable. Therefore, by constructing sensitive spectral indexes through inter-band operations, background-target differences could be enhanced, which would facilitate the target extraction. By observing the wavelength-relative reflectivity curve in Figure 4, there are six bands showing significant differences between background and the target; thus, they are promising for later target identification: (1) in the 400-500 nm band, the spectral curves of camouflage clothing and green vegetation follow the same trend, and the reflectance is low and difficult to distinguish, so the band of 450 nm can be used as the reference point for the inter-band calculation; (2) there is a reflection peak caused by vegetation chlorophyll in the spectrum curve of green vegetation in 550-560 nm band, which is much higher than that of green camouflage. So, the band of 555 nm is selected; (3) in the 660-690 nm band, there is an absorption peak that corresponds to the reflectance of green vegetation, which is much lower than the reflectance of camouflage clothing, so the band of 660 nm is selected; (4) nearby 710 nm, the reflectance of green vegetation rose sharply and reached the peak rapidly, thus the band of 710 nm is adopted as the first high-reflectivity band; (5) the high-reflectivity-platform continues until 1000 nm. This band of camouflage clothing has high contrast with green vegetation, and the characteristics are obvious. Therefore, the band of 840 nm and 940 nm are reasonably selected for feature recognition. Within a certain band number range, more spectra contain richer information.