Aiming at the problem that improper selection of detector spectrum has a serious impact on detection efficiency in point target detection. This paper analyzes the main factors affecting point target detection and proposes a point target detection spectrum selection method based on constant false alarms. This method takes detection probability as an evaluation index, comprehensively considers the target and background radiation characteristics, atmospheric radiation transmission, background clutter and sensor noise level. It can calculate the optimal detection spectrum for different target and background information. Taking the typical target detection as an example, the spectrum range where the detection probability meets the requirements under several conditions is calculated, and its feasibility is verified. Through the method in this paper, the point target detection spectrum that meets the requirements of false alarm rate and detection probability can be obtained
Aiming at the problem of noise and the difficulty of periodic extraction in infrared data acquisition. In this paper, a line method of infrared data period extraction based on CEEMDAN is proposed, which can eliminate the noise and interference of infrared data and accurately extract the period. The method preprocesses the original foreign teacher data by determining the signal mode, so as to improve the quality of infrared data; However, the data cycle was accurately extracted by using the method of correlation split mean cap. Finally, the validity and correctness of the extraction method are verified by simulation experiments.
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