Research on space target detection ability calculation method and spectral filtering technology in sky-screen's photoelectric system

2016 ◽  
Vol 58 (5) ◽  
pp. 1035-1041 ◽  
Author(s):  
Hanshan Li
2011 ◽  
Author(s):  
Jianwei Gao ◽  
Rui Yao ◽  
Lei Jiang ◽  
Jinqiu Sun ◽  
Yanning Zhang

Author(s):  
Mateusz Malanowski ◽  
Konrad Jedrzejewski ◽  
Jacek Misiurewicz ◽  
Krzysztof Kulpa ◽  
Artur Gromek ◽  
...  

2009 ◽  
Vol 29 (1) ◽  
pp. 67-71
Author(s):  
李雅男 Li Yanan ◽  
孙晓兵 Sun Xiaobing ◽  
乔延利 Qiao Yanli

Author(s):  
Linh

The article presents a method to evaluate the target detection efficiency of laser fuzes operating in foggy conditions. The evaluation model is built from: the distance equation of the laser system, the attenuation of the beam in two-way propagation, the disturbances affecting the system; the signal to noise ratio SRN has determined the detection probability of the receiver. The model was used to evaluate with wavelengths: 850 nm, 1000 nm and 1550 nm, when propagating in three different bad weather conditions. The results show that the most effective detection of the target when using a wavelength of 1550 nm in visibility in haze and mist conditions (visibility V > 500 m). In fog conditions (visibility V < 500 m), the above three wavelengths provide the same detection efficiency. The article provides the method and instructions for choosing the wavelength of the laser fuze.


2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Yijun Chen ◽  
Qun Zhang ◽  
Ying Luo ◽  
Tat Soon Yeo

The micromotion feature of space target provides an effective approach for target recognition. The existing micromotion feature extraction is implemented after target detection and tracking; thus the radar resources need to be allocated for target detection, tracking, and feature extraction, successively. If the feature extraction can be implemented by utilizing the target detecting and tracking pulses, the radar efficiency can be improved. In this paper, by establishing a feedback loop between micromotion feature extraction and track-before-detect (TBD) of target, a novel feature extraction method for space target is proposed. The TBD technology is utilized to obtain the range-slow-time curves of target scatterers. Then, micromotion feature parameters are estimated from the acquired curve information. In return, the state transition set of TBD is updated adaptively according to these extracted feature parameters. As a result, the micromotion feature parameters of space target can be extracted concurrently with implementing the target detecting and tracking. Simulation results show the effectiveness of the proposed method.


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