Modeling and Verification of Ground Point Source for Mid-Wave Infrared Detection
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摘要: 红外系统在大范围内对异常热源点目标的探测需要平衡像元分辨率与温度灵敏度之间的关系。在探测器规模一定时，现有星载红外载荷存在幅宽大时灵敏度不够、空间分辨率高时幅宽小的问题。针对上述问题，本文提出利用时间延时积分（time delay intergration，TDI）算法处理图像的大视场异常点热源探测初步方案，在一定条件下，达到探测所需的温度灵敏度要求时，能做到217 km×122 km的理论幅宽。同时搭建了一套高灵敏度红外成像实验系统，开展了测试与模拟探测实验，结果表明本方案在实现202 km×114 km幅宽情况下，灵敏度性能约37 mK，满足大范围异常点热源探测的要求。考虑到目标和背景的太阳光反射率等问题，实际应用时取200 m像元分辨率，对应幅宽128 km×102 km。Abstract: The detection of anomalous heat source point targets in a wide range of infrared systems requires a balance between the pixel resolution and temperature sensitivity. Given that the scale of the detector is stable, the existing space-borne infrared payloads have insufficient sensitivity when the amplitude is large and small amplitude when the spatial resolution is high. In response to these problems, in this study, we propose a preliminary plan for detecting heat sources at abnormal points in a large field of view using a time-delay integration (TDI) algorithm to process images. Under certain conditions, the temperature sensitivity requirements for detection can be satisfied and a theoretical width of 217 km × 122 km can be achieved. A set of high-sensitivity infrared imaging experimental systems was built, and testing and simulation-based detection experiments were conducted. The results show that the sensitivity performance of this scheme is approximately 37 mK when a width of 202 km× 114 km is realized, which fulfills the requirements for detecting a large-scale abnormal point heat source. Considering the solar reflectance of the target and background, a pixel resolution of 200 m is used in practical applications, which corresponds to a width of 128 km×102 km.
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图 1 热源所在目标微元示意图
Figure 1. Schematic diagram of the target micro element where the heat source is located
图 2 NETD与探测器空间分辨率的关系
Figure 2. The relationship between NETD and detector spatial resolution
图 3 光学镜头焦距与空间分辨率之间几何关系示意图
Figure 3. Schematic diagram of geometric relationship between optical lens focal length and spatial resolution
图 4 较长积分时间下采集的图像经不同阶TDI处理后的NETD
Figure 4. NETD of images collected under a longer integration time processed by different levels of TDI
图 5 TDI算法处理后的图像非均匀性噪声与均方根噪声
Figure 5. Image non-uniformity noise and root mean square noise processed by TDI algorithm
图 6 推扫成像模拟探测实验方案示意图
Figure 6. Schematic diagram of push-broom imaging simulation detection experiment scheme
图 7 推扫成像模拟探测实验现场示意图：(a) 探测器系统及电控转台实物；(b) 探测器系统与目标位置关系实物图；(c) 模拟热源实物
Figure 7. Schematic diagram of the push-broom imaging simulation detection experiment site (a) The physical diagram of the detector system and the electric control turntable; (b) The physical diagram of the positional relationship between the detector system and the target; (c) The physical diagram of the simulated heat source
图 8 模拟探测实验结果：(a) 热源像元及其同一行附近的像元DN值曲线；(b) 经8阶TDI处理后的热源像元及其同一行附近的像元DN值曲线；(c) 经16阶TDI处理后的热源像元及其同一行附近的像元DN值曲线；(d) 经25阶TDI处理后的热源像元及其同一行附近的像元DN值曲线
Figure 8. The results of the simulated detection experiment: (a) The DN value curve of the heat source pixel and the pixel near the same row; (b) The heat source pixel and the DN value curve of the pixel near the same row after 8th-order TDI processing; (c) The DN value curve of the heat source pixel after 16-level TDI processing and the pixel near the same row; (d) The heat source pixel after the 25-level TDI processing and the DN value curve of the pixel near the same row
表 1 红外探测系统参数理论值
Table 1. Theoretical values of detector parameters that meet the heat source detection standards of preset scenarios
Parameter Value Working wavelength 3.7~4.8 μm F# 2 Scan width 217 km×122 km Orbit height 500 km NETD ≤6.25 mK Focal length 21.6 mm Distance between the center of pixels 15 μm×15 μm Spatial resolution 346 m 
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表 2 部分阶数TDI算法处理后模拟热源所在像元DN值与背景像元DN值均值差值
Table 2. The difference between the DN value of the pixel where the simulated heat source is located and the average DN value of the background pixel after processing by the partial order TDI algorithm
TDI stage DN for pixel contain the heat source DN1 Average DN for background pixels DN2 DN1− DN2 Raw picture 579 552.8 26.2 8 576 549 26.2 16 582 536.9 45.1 25 570 524.4 45.6
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