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低信噪比情况对空间点目标的识别仍然是很困难的问题,尤其在区分卫星目标和系留诱饵等干扰时尤为困难。此时系留诱饵与目标具有相同的运动轨迹和相似的外形特性,因而所能利用的差异仅有辐射特性差异。然而提取多光谱辐射差异并不是简单的问题,尤其是辐射会受到探测距离、探测角度的影响。基于目标和诱饵等干扰具有不同辐射强度及辐射变化频率的特点,建立了空间目标等效黑体温度的概念。并相应的设计了等效黑体温度的计算模型,该模型可以有效的减小空间环境的干扰而充分体现目标和诱饵等干扰的辐射差异。然而由于噪声的干扰,此模型会产生计算误差,并且不同的探测波段组合具有不同的误差传递能力。为了使这种噪声引起的误差最小,需要确定最佳的探测波段。通过计算噪声存在情况下,误差随探测波段参数的变化趋势,获得了最佳探测双波段、最佳探测多波段和最佳探测波段数。通过分析仿真实验的结果,使用最佳探测双波段可以减小20%的误差,而最佳探测多波段会进一步的减小20%的误差,这种结果证明了文中研究结论的正确性。
The recognition of spatial point targets at low S / N ratios remains a difficult issue, especially when it comes to distinguishing interferences such as satellite targets and tethered decoys. In this case, the tethered bait has the same trajectory and similar appearance characteristics as the target, so the difference that can be utilized is only the difference in radiation characteristics. However, extracting multi-spectral radiation differences is not a simple problem, especially the radiation will be affected by the detection range and detection angle. Based on the characteristics of different radiation intensity and frequency of radiation change such as target and bait, the concept of equivalent blackbody temperature in space target was established. Correspondingly, a calculation model of equivalent black body temperature is designed. This model can effectively reduce the interference of space environment and fully reflect the radiation difference of interference such as target and bait. However, due to noise interference, this model will produce calculation error, and different combinations of detection bands have different error transfer capabilities. In order to minimize the error caused by this noise, it is necessary to determine the best detection band. By calculating the variation tendency of the error in the presence of noise, the optimal detection dual band, the best detection multi-band and the best detection band are obtained. By analyzing the results of simulation experiments, using the best detection dual-band can reduce the error of 20%, and the best detection of multi-band will further reduce the error of 20%, this result proves the correctness of the conclusions in this paper.