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Infrared radiation characteristics measurement and temperature retrieval based on DJI unmanned aerial vehicle
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摘要:
随着无人机技术在各个领域崭露头角，无人机目标在红外波段的辐射特性成为人们非常关注的问题。本文首先对中、长波红外探测器进行辐射定标，针对飞行中的无人机目标的辐射特性进行测量，对飞行状态下的无人机目标的温度进行了反演，分别采用了单波段、双波段比色法、基于黑体校正的双波段法进行探测，结合实测数据对上述各种方法进行了分析对比，对测量结果进行了精度分析并给出误差源。结果表明，实验中的无人机中波辐射强度约为0.04 W/sr、长波辐射强度在0.5 W/sr左右，采用基于黑体校正的双波段测量方法能极大提高无人机目标温度反演的精度。反演温度的绝对误差降低至2 K，相对误差仅为0.5%左右。
Abstract:With the initial applications of unmanned aerial vehicle technology in various fields, the infrared (IR) radiation characteristic of the UAV becomes an issue of mutual concern. In this experiment, the radiometric calibration of middle wave and long wave infrared detectors has been done firstly. The radiation characteristics of the UAV are measured while flying, and the temperature of UAV target is inverted by using single-band method, dual-band colorimetric method and dual-band method based on black-body calibration. Combined with the real measured data, the above methods are analyzed and compared. The measurement precision is analyzed and error source is given. The results show that radiation intensity of UAV is about 0.04 W/sr in middle IR wave, and 0.5 W/sr in long IR wave. Dual-band method based on black-body calibration can improve the precision of UAV temperature inversion greatly, the absolute error of temperature retrieval reduces to 2 K, and relative error is about 0.5%.
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Key words:
- unmanned aerial vehicle /
- radiance /
- radiation characteristics /
- temperature retrieval
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Abstract: With the initial applications of unmanned aerial vehicle technology in various fields, the infrared (IR) radiation characteristics of the UAV become an issue of mutual concern. In this experiment, the radiometric calibration of middle wave and long wave infrared detectors has been done. SR800R 12D_ET extending blackbody made in Israel is used for the radiometric calibration of middle wave and long wave infrared detectors. The quantitative connection between the optical entrance pupil radiation and the output of detector is established, and the responsivity of the infrared detector is obtained. The radiation characteristics of the UAV is measured while flying, and the temperature of UAV target is inverted by using single-band method, dual-band colorimetric method and dual-band method based on black-body calibration.
Firstly, single-band measurement experiment is performed. According to the experimental principle, the mathematical model is established. The equation of radiance and temperature is obtained. The inversion temperature depends on the equation. If each coefficient in the formula is analyzed, the accuracy of the inversion temperature can be obtained theoretically. Using Monte Carlo method, by constructing random number that matches the coefficient uncertainty in the above formula, is a good idea for temperature retrieval of simulation experiment. In this experiment, Phantom 3 of DJI-Innovation is used to simulate the target. The radiation intensity of target UAV is calculated, the absolute error of temperature retrieval reduces to 11 K, and relative error is just near 4%. This method has a significant error in temperature retrieval.
Secondly, in order to eliminate the impact of the emissivity, the experiment of dual-band colorimetry was carried out. Compared to single-band measurement experiment, the experimental principle is improved and the mathematical model is modified. The results show that radiation intensity of UAV is about 0.0486W/sr in middle IR wave and 0.6113 W/sr in long IR wave. The absolute error of temperature retrieval is reduced to 4 K, and relative error is just near 2%. Using atmospheric mode to calculate still has a large error.
At last, dual-band method based on black-body calibration is used to effectively solve the effects of atmospheric transmittance and atmospheric path radiation on infrared radiation characteristics measurement and temperature retrieval. The results show that radiation intensity of UAV is about 0.04 W/sr in middle IR wave and 0.5 W/sr in long IR wave. The absolute error of temperature retrieval reduces to 2 K, and relative error is just near 0.5%. Dual-band method based on black-body calibration can improve the precision of UAV temperature inversion extremely in contrast with the previous method.
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表 1 实验的大气参数.
Table 1. Atmospheric parameters for the experiment.
Temperature/℃ Humidity/(%) Visibility/km Atmospheric pressure/hPa Altitude/m Longitude Latitude 31.6 49 12 1008 4 E121°28' N31°17' 
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表 2 无人机的长波红外辐射温度反演结果.
Table 2. LWIR temperature retrieval results of UAV.
Location Gray value of LW Calculated radiance/(W·sr-1·m-2) Actual temperature/K Calculated temperature/K Absolute error/K Relative error/(%) A 11861 19.4204 305.5 316.7 11.2 3.7 B 11818 19.2739 305.5 316.3 10.7 3.5 C 11861 19.4204 305.5 316.7 11.2 3.7 D 11831 19.3182 305.5 316.5 11.0 3.5 E 11833 19.3250 305.5 316.4 10.9 3.6
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表 3 无人机的长波红外辐射特性结果.
Table 3. LWIR radiation characteristics result of UAV.
Gray value of LW Number Radiance of LWIR/(W·sr-1·m-2) Radiation intensity of LWIR/(W·sr-1) 11797 100 19.2011 0.6240 11805 86 19.2283 0.5374 11800 97 19.2113 0.6056 11810 99 19.2454 0.6192 11817 107 19.2692 0.6701
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表 4 基于传统的双波段温度反演结果.
Table 4. Temperature retrieval results based on traditional dual waveband.
Location Gray value of MW Gray value of LW Calculated radiance of MW/(W·sr-1·m-2) Calculated radiance of LW/(W·sr-1·m-2) Actual temperature/K Calculated temperature/K Absolute error Relative error/(%) A 9250 11861 1.6567 19.4205 305.5 301.5 4.0 1.3 B 9135 11818 1.6260 19.2739 305.5 300.9 4.6 1.5 C 9222 11861 1.6493 19.4205 305.5 301.2 4.3 1.4 D 9223 11831 1.6495 19.3182 305.5 301.6 3.9 1.3 E 9248 11833 1.6562 19.3251 305.5 301.8 3.8 1.2
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表 5 无人机的中、长波红外辐射特性结果.
Table 5. LWIR and MWIR radiation characteristics results of UAV.
Gray value of MW Gray value of LW The number
in MWIRThe number in LWIR Radiance of
MW /(W·sr-1·m-2)Radiance of
LW/(W·sr-1·m-2)Radiation intensity of MWIR/(W/sr) Radiation intensity of LWIR/(W/sr) 9002 11797 99 100 1.5904 19.2011 0.0512 0.6240 9003 11805 86 86 1.5907 19.2283 0.0445 0.5374 8959 11800 90 97 1.5789 19.2113 0.0462 0.6056 8902 11810 99 99 1.5637 19.2454 0.0503 0.6192 8973 11817 99 107 1.5827 19.2692 0.0509 0.6701
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表 6 利用黑体计算大气透过率和大气路径辐射亮度实验结果.
Table 6. Atmospheric transmittance and path radiance experimental results calculated from black body.
Blackbody temperature/K Radiance of MW/(W·sr-1·m-2) Radiance of LW/(W·sr-1·m-2) Gray value of MW Gray value of LW 308 1.6742 17.5531 10071 12226 323 2.7543 22.6943 13430 13293
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表 7 基于黑体校正的双波段温度反演结果
Table 7. Dual waveband temperature retrieval results based on black body calibration.
Location Gray value of MW Gray value of LW Calculated radiance of MW/(W/sr·m2) Calculated radiance of LW/(W/sr·m2) Actual temperature/K Calculated temperature/K Absolute error Relative error/(%) A 9250 11861 1.4102 15.7944 305.5 304.1 1.4 0.46 B 9135 11818 1.3732 15.5872 305.5 303.4 2.1 0.69 C 9222 11861 1.4012 15.7944 305.5 303.7 1.8 0.59 D 9223 11831 1.4015 15.6498 305.5 304.3 1.2 0.39 E 9248 11833 1.4096 15.6595 305.5 304.6 1.1 0.36
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表 8 无人机的中、长波红外辐射特性结果.
Table 8. LWIR and MWIR radiation characteristics of UAV.
Gray value of MW Gray value of LW The number in MWIR The number in LWIR Radiance of MW /(W·sr-1·m-2) Radiance of LW/(W·sr-1·m-2) Radiation intensity of MWIR/(W·sr-1) Radiation intensity of LWIR/(W·sr-1) 9002 11797 99 100 1.3305 15.4860 0.0428 0.5033 9003 11805 86 86 1.3308 15.5245 0.0372 0.4339 8959 11800 90 97 1.3166 15.5005 0.0385 0.4887 8902 11810 99 99 1.2983 15.5486 0.0418 0.5003 8973 11817 99 107 1.3211 15.5486 0.0425 0.5419
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