title: [Analysis and experimental verification of sensitivity and SNR of laser warning receiver].
abstract: In order to countermeasure increasingly serious threat from hostile laser in modern war, it is urgent to do research on laser warning technology and system, and the sensitivity and signal to noise ratio (SNR) are two important performance parameters in laser warning system. In the present paper, based on the signal statistical detection theory, a method for calculation of the sensitivity and SNR in coherent detection laser warning receiver (LWR) has been proposed. Firstly, the probabilities of the laser signal and receiver noise were analyzed. Secondly, based on the threshold detection theory and Neyman-Pearson criteria, the signal current equation was established by introducing detection probability factor and false alarm rate factor, then, the mathematical expressions of sensitivity and SNR were deduced. Finally, by using method, the sensitivity and SNR of the sinusoidal grating laser warning receiver developed by our group were analyzed, and the theoretic calculation and experimental results indicate that the SNR analysis method is feasible, and can be used in performance analysis of LWR.
authors.affiliation: Key Laboratory of Instrumentation & Dynamic Measurement, Ministry of Education, North University of China, Engineering Technology Research Center of Shanxi Province for Optoelectronic Information and Instrument, Taiyuan 030051, China. zhangjl@nuc.edu.cn
authors.forename: Ji-Long
authors.initials: JL
authors.lastname: Zhang
authors.forename: Ming
authors.initials: M
authors.lastname: Wang
authors.forename: Er-Ming
authors.initials: EM
authors.lastname: Tian
authors.forename: Xiao
authors.initials: X
authors.lastname: Li
authors.forename: Zhi-Bin
authors.initials: ZB
authors.lastname: Wang
authors.forename: Yue
authors.initials: Y
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D001330:Electronic Data Processing; D007089:Image Enhancement; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007834:Lasers / Q000706:statistics & numerical data*; D009010:Monte Carlo Method; D009622:Noise; D012680:Sensitivity and Specificity; D017603:Signal Detection, Psychological