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1 Opto-Electronic Engineering Article CCD m 300 mm 300 mm 200 mm 60 E926.4TN249 A. [J] (4): An optoelectronic system for fast search of low slow small target in the air 1 School of Communication and Information Engineering, Shanghai University, Shanghai , China; 2 Optical Astronomy Technology Laboratory, Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai , China; 3 School of Astronomy and Space Science, University of Chinese Academy of Sciences, Beijing , China; 4 Shanghai Astronomical Optoelectronic Technology Co. LTD, Shanghai , China Abstract: On the development trend of opening low altitude airspace in our country and the protection requirements for key areas, combined with the latest optoelectronic technology, a fast search method to detect low slow small target for low altitude airspace was presented, and a set of prototype system was developed. The system uses a linear CCD camera mounted on a high-precision one-dimensional turntable to collect 360-degree panoramic images (15DZ ) (1993-) xiyuding@shao.ac.cn (1977-) yuy@shao.ac.cn

2 of low altitude airspace. The image data is transmitted to the data processing workstation in real time through gigabit Ethernet slide ring. The data processing workstation detects small targets in the area above the skyline and figures out the orientation of target. Preliminary observation experiments of the prototype are conducted, the result shows that the system can detect low slow small target in broad low airspace in all directions. In the case of good atmospheric transparency, it can detect unmanned aerial vehicle (UAV) in size of 300 mm 300 mm 200 mm within 2300 m. The accuracy of the direction of measurement is 60 arcsecond. This research provides an effective mean to solve the problem of searching and finding low slow small targets. Keywords: low slow small target; target detection; low airspace protection; panoramic image acquisition Citation: Xi Y D, Yu Y, Ding Y Y, et al. An optoelectronic system for fast search of low slow small target in the air[j]. Opto-Electronic Engineering, 2018, 45(4): () [1] (radar scattering cross section area, RCS) 2013 (pulse doppler, PD) [2] PD RCS [3] 2014 [4] 2016 [5] [6] CCD CCD s/r 5 m 50 mm 100 mm CCD mm s r arctan (1) d

s d 20 CCD 360 2 ( 20) 360 360 () 3 3 3.1 1) 65536 pixels 4096 pixels 2.

3 s d 20 CCD ( 20) () ) pixels 4096 pixels ) 3) 4) pixels n n-1 n 1 Fig. 1 Image of acquisition platform 2 Fig. 2 Image acquisition methods 3 Fig. 3 Low and slow small target search discovery system composition block diagram

4 4 Fig. 4 UAV in panoramic images Fig. 5 Gray value distribution of the image column UAV target located 3.2 1) 2) () 6 Canny [7-9] f(x, h(x, g( x, f ( x, h( x, (2) g g x x g( x, (3) g g y y g( x, f ( x, h( x, f ( x, h( x, (4) h( x, [9]

[7] 5 5 Canny 10 pixels 7 3.2.2 [10-11] 8 s [12-14] [15] 6 Top-Hat Top-Hat Top-Hat I 2 () 0 I 1 I 2 -I 1 0 I 3 6 Fig.

5 [7] 5 5 Canny 10 pixels [10-11] 8 s [12-14] [15] 6 Top-Hat Top-Hat Top-Hat I 2 () 0 I 1 I 2 -I 1 0 I 3 6 Fig. 6 Image target detection process based on single frame 7 Fig. 7 Example of extracting results from the skyline

[16] RPNSR I max / B, (5) I max B 8 4 4.

6 [16] RPNSR I max / B, (5) I max B pixels 0.9 pixels(1) ( ) 10(b) Intel i ThinkStation Fig. 8 Principle of Image distributed processing 9 Fig. 9 Point marker for direction-finding

7 2 s 11 ( )()( )() 1 3 (a) (b) 10 (a)(b) Fig. 10 Panoramic image (a) and processing results real-time display interface (b) (a1) (a2) (a3) (a4) (b1) (b2) (b3) (b4) (c1) (c2) (c3) (c4) 11 (a1)(a4) (b1)(b4) ; (c1)(c4) Fig. 11 Some samples of low slow small target detected. (a1)(a4) Different kinds of low slow small targets; (b1)(b4) Low slow small targets in complex context; (c1)(c4) Mistakenly detected targets

1 156 139 17 10.9 205 157 48 23.4 409 395 14 3.

8 100 7.6 200 4.8 500 3.1 1000 2.0 2300 1.

8 300 mm 300 mm 200 mm m Table 1 False detecting rate in different weather /% Table 2 Peak signal-to-noise ratio of target in different distances /m (a) (b) (c) (d) (e) (f) 12 (a) 50 m; (b) 100 m; (c) 200 m; (d) 500 m; (e) 1000 m; (f) 2300 m Fig. 12 Target detection result in different distances. (a) 50 m; (b) 100 m; (c) 200 m; (d) 500 m; (e) 1000 m; (f) 2300 m

9 5 CCD 360 1) 602) 2300 m 300 mm 300 mm 200 mm [1] Zhang J W, Guo H M. Net cast interception system research aimed at low small slow target[j]. Computer Engineering and Design, 2012, 33(7): ,. [J]., 2012, 33(7): [2] Wu C, Li H F, Wang H, et al. Influence analysis of PD radar detecting LSS-target[J]. Science Technology and Engineering, 2013, 13(28): , 8519.,,,. PD [J]., 2013, 13(28): , [3] Ren Q A, Lv C Y. Research on radar and photoelectric collaborative tracking algorithm[j]. Radar Science and Technology, 2016, 14(2): , 183.,. [J]., 2016, 14(2): , 183. [4] Li D, Li Y X, Meng W, et al. Research of plane array propelled laser imaging detection for small targets at low altitude and slow speed[j]. Laser Technology, 2014, 38(1): ,,,. [J]., 2014, 38(1): [5] Li B, Meng L F, Li J, et al. Research on detecting and locating technology of LSS-UAV[J]. China Measurement & Test, 2016, 42(12): ,,,. [J]., 2016, 42(12): [6] Kittle D S, Marks D L, Son H S, et al. A testbed for wide-field, high-resolution, gigapixel-class cameras[j]. Review of Scientific Instruments, 2013, 84(5): [7] Wu X, Yu W B, Ma Y H, et al. A new improved Canny image edge detection algorithm[j]. Imaging Science and Photochemistry, 2016, 34(1): ,,,. Canny [J]., 2016, 34(1): [8] Jia D, Dong N, Meng X F, et al. A method for continuous image edge extraction[j]. Computer Engineering & Science, 2015, 37(2): ,,,. [J]., 2015, 37(2): [9] Xue L X, Li T, Wang Z C. Adaptive Canny edge detection algorithm[j]. Application Research of Computers, 2010, 27(9): ,,. Canny [J]., 2010, 27(9): [10] Liu R, Wang D J, Jia P, et al. Overview on small target detection technology in infrared image[j]. Laser & Optoelectronics Progress, 2016, 53(5): ,,,. [J]., 2016, 53(5): [11] Wei M, Wen W, Zhou J, et al. Deep sky small target detection using registration difference[j]. Opto-Electronic Engineering, 2015, 42(11): ,,,. [J]., 2015, 42(11): [12] Tong W Q, Ling Y S, Huang C C, et al. Processing method of IR image based on mathematical morphology and wavelet transform[j]. Optics and Precision Engineering, 2007, 15(1): ,,,. [J]., 2007, 15(1): [13] Wang D. Infrared small target detection based on morphological and neighbor information[j]. Electro-Optic Technology Application, 2016, 31(2): 19 21, 30.. [J]., 2016, 31(2): 19 21, 30. [14] Lv J M, Niu Y X, Liu H X, et al. Study of small target detection in single frame image based on local characteristics[j]. Infrared, 2014, 35(2): ,,,. [J]., 2014, 35(2): [15] Dai H D, Hu M F, Lu H Z, et al. Design and implementation of target detection algorithm based on connected-domain labeling[j]. Modern Electronics Technique, 2015, 38(20): ,,,. [J]., 2015, 38(20): [16] Wang X W, Wang C X, Zhang Y Y. Research on SNR of point target image[j]. Electronics Optics & Control, 2010, 17(1): ,,. [J]., 2010, 17(1):

10 An optoelectronic system for fast search of low-slow-small target in the air 1 School of Communication and Information Engineering, Shanghai University, Shanghai , China; 2 Optical Astronomy Technology Laboratory, Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai , China; 3 School of Astronomy and Space Science, University of Chinese Academy of Sciences, Beijing , China; 4 Shanghai Astronomical Optoelectronic Technology Co. LTD, Shanghai , China UAV in panoramic images Overview:With the development of technology, the maneuverability of all kinds of aviation aircraft are constantly enhanced. In recent years, low-altitude airspace has gradually opened up in our country, and man-kind low-altitude activities have increased, the management of aircraft in low-altitude airspace has become increasingly difficult. It has become a world-wide problem to prevent grand activities from the interference and damage of low slow small targets. At present, there are various methods to detect the flight targets in low altitude airspace, including radar detection, radio detection and photoelectric detection. Among them, the photoelectric detection method has the characteristics of strong anti-interference, intuitive and clear, flexible deployment and so on. Therefore, it is expected to play an important role in the search and discovery of low-slow-small targets in complex urban environment. In order to resolve the contradiction between the large field and the high resolution when using optoelectronic techniques to monitor small targets, Shanghai Astronomical Observatory developed an optical prototype system to search and find low slow small targets in low-altitude airspace. The system consists of a high-precision one-dimensional turntable platform, a large field-of-view refractor, a set of computers to control hardware and analysis images. Firstly, the linear CCD camera collects 360-degree panoramic images of low-altitude airspace in 8 seconds when the platform rotates continuously. Then the images are transferred to the computer through gigabit Ethernet slide ring and analyzed in real time. Due to factors such as human activity, trees shaking and illumination changes, it is difficult to detect slow small targets in the area below the skyline in one image. We extracted the skyline in the panoramic images and detect low slow small targets above the skyline by automatic program. Finally, the directions of targets are calculated so as to take further steps to them. And we developed a real-time display interface to show the panoramic images and the processing results. In order to achieve real-time detection of the target, two workstations are set up in the LAN and the panoramic images are processed in a distributed way. Observation experiment was carried out in July 2017, we flew an unmanned aerial vehicle (UAV) in size of 300 mm 300 mm 200 mm in different distance and in different weather in order to check the ability of the prototype system. The result shows that the prototype system can detect UAV at distance of 2.3 km when the weather is nice, the accuracy of the direction of UAV is about 1 arcminute. Citation: Xi Y D, Yu Y, Ding Y Y, et al. An optoelectronic system for fast search of low slow small target in the air[j]. Opto-Electronic Engineering, 2018, 45(4): Supported by Shanghai Science and Technology Achievement Transformation and Industrialization Project (15DZ ) * yuy@shao.ac.cn

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[1-3] (Smile) [4] 808 nm (CW) W 1 50% 1 W 1 W Fig.1 Thermal design of semiconductor laser vertical stack ; Ansys 20 bar ; bar 2 25 Fig 40 6 2011 6 Vol.40 No.6 Infrared and Laser Engineering Jun. 2011 808 nm 2000 W 1 1 1 1 2 2 2 2 2 12 (1. 710119 2. 710119) : bar 808 nm bar 100 W 808 nm 20 bar 2 000 W bar LIV bar 808 nm : : TN248.4 TN365