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
Keyword(s):  
Target Detection ◽  
Calculation Method ◽  
Spectral Filtering ◽  
Detection Ability ◽  
Photoelectric System ◽  
Space Target

DYNAMIC SPECTRAL FILTERING OF SIGNALS IN OPTOELECTRONIC SYSTEMS OF TARGET DETECTION

2018 ◽  
Vol 77 (8) ◽  
pp. 689-704
Author(s):  
L. F. Kupchenko ◽  
A. S. Rybiak ◽  
O. A. Goorin
Keyword(s):  
Target Detection ◽  
Spectral Filtering ◽  
Optoelectronic Systems

A large field of view optical system design for space target detection

2018 ◽  
Author(s):  
Dongwei Ni ◽  
Xuyang Li ◽  
Mingyang Yang ◽  
Chunlin Tian ◽  
Ling Zhang
Keyword(s):  
System Design ◽  
Target Detection ◽  
Optical System ◽  
Field Of View ◽  
Large Field ◽  
Optical System Design ◽  
Space Target

Small space target detection based on feature stability algorithm

2011 ◽  
Author(s):  
Jianwei Gao ◽  
Rui Yao ◽  
Lei Jiang ◽  
Jinqiu Sun ◽  
Yanning Zhang
Keyword(s):  
Target Detection ◽  
Small Space ◽  
Space Target ◽  
Feature Stability

Moving space target detection algorithm based on trajectory similarity

2018 ◽  
Author(s):  
Dong Wang ◽  
Yan Wen ◽  
Zhao Li
Keyword(s):  
Target Detection ◽  
Detection Algorithm ◽  
Trajectory Similarity ◽  
Space Target

Passive Radar Based on LOFAR Radio Telescope for Air and Space Target Detection

2021 ◽  
Author(s):  
Mateusz Malanowski ◽  
Konrad Jedrzejewski ◽  
Jacek Misiurewicz ◽  
Krzysztof Kulpa ◽  
Artur Gromek ◽  
...  
Keyword(s):  
Target Detection ◽  
Radio Telescope ◽  
Passive Radar ◽  
Space Target

Waveband Selection for Space Target Detection and Identification

2009 ◽  
Vol 29 (1) ◽  
pp. 67-71
Author(s):  
李雅男 Li Yanan ◽  
孙晓兵 Sun Xiaobing ◽  
乔延利 Qiao Yanli
Keyword(s):  
Target Detection ◽  
Detection And Identification ◽  
Selection For ◽  
Space Target

ASSESSMENT OF TARGET DETECTION ABILITY FOR LASER FUZES IN FOG CONDITIONS

2021 ◽  
pp. 8-16
Author(s):  
Linh
Keyword(s):  
Target Detection ◽  
Detection Probability ◽  
Detection Efficiency ◽  
Signal To Noise Ratio ◽  
Evaluation Model ◽  
Laser System ◽  
Weather Conditions ◽  
Signal To Noise ◽  
Detection Ability ◽  
Bad Weather

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.

scholarly journals Micromotion Feature Extraction of Space Target Based on Track-Before-Detect

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Yijun Chen ◽  
Qun Zhang ◽  
Ying Luo ◽  
Tat Soon Yeo
Keyword(s):  
Feature Extraction ◽  
Target Detection ◽  
Feedback Loop ◽  
Feature Extraction Method ◽  
Feature Parameters ◽  
Detection And Tracking ◽  
Transition Set ◽  
Target Detecting ◽  
Track Before Detect ◽  
Space Target

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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