An Optical Readout Method Based Uncooled Infrared Imaging System

Transcription

1 Int J Infrared Milli Waves (2008) 29: DOI /s An Optical Readout Method Based Uncooled Infrared Imaging System Binbin Jiao & Chaobo Li & Dapeng Chen & Tianchun Ye & Yi Ou & Lijun Dong & Qingchuan Zhang & Zheying Guo & Fengliang Dong Received: 16 July 2007 / Accepted: 7 January 2008 / Published online: 2 February 2008 # Springer Science + Business Media, LLC 2008 Abstract This paper presents an optical readout method based uncooled infrared imaging system that contains an optical read-out section and a bi-material micro-cantilever arrays (BMCA) detector. The optical read-out section is based on incoherent light spatial filter technique. The read-out section converts the deflection angles of BMCA caused by absorption of infrared (IR) radiation to a visible image through optical filtering operation of the BMCA with a knife-edge filter. A spatial mathematical model is presented to describe the read-out method and its validity is proved. The IR image of a person s hand obtained through the using of the BMCA and the 12-bit A/D quantizer demonstrates the ability of the system to create image. The performance test shows that the average Noiseequivalent temperature difference (NETD) of the imaging system can arrive at about 183 mk with some areas having a NETD as low as 78 mk. Keywords IR. Imaging. Spatial filter. Opto-mechanical. Uncooled Project supported by Natural Science Foundation of China (No ), National Technology Research and Development Program of China (No.2007AA03Z333). B. Jiao : C. Li : D. Chen : T. Ye : Y. Ou : L. Dong Micro-processing and Nano-technology Department, Institute of Microelectronics, Chinese Academy of Sciences, Beijing , China B. Jiao jiaobinb@hotmail.com Q. Zhang: Z. Guo : F. Dong KEY Laboratory of Mechanical Behavior and Design of Materials, University of Science and Technology of China, Hefei , China D. Chen (*) Silicon Device & Integrated Technology Department, Institute of Microelectronics, Chinese Academy of Sciences, Beijing , China dpchen@ime.ac.cn

2 262 Int J Infrared Milli Waves (2008) 29: Introduction Optical read-out methods are playing an important role in thermal sensing [1 3] using micro-cantilever due to their advantages of non-contact, high resolution, no micro-read-out circuit compared with electronic read-out method. Although the optical lever technique has been used in a single cantilever with sub-angstrom resolution [1 4], it is susceptible to cross talk when applied to cantilever array. Sequential position read-out of a microcantilever sensor array solves the problem [5]. However, it is not suitable for large arrays. The interferometry method can measure the vertical displacement of micro-cantilever array simultaneously [6], however, its resolution is in the range of 1=10 1=100 typically and it is sensitive to environment vibration. In 2001, incoherent light spatial filter technique is introduced by T. Ishizuya et al., which solves most of the problems [7]. However, their system can not reconcile the conflict between the resolution and the sensitivity of the detector, and can not have the linear relation between the light intensity and the inclination angle of micro-cantilevers. To solve these problems, we proposed a uncooled infrared imaging system based on optical read-out method for large arrays using knife-edge filter [8] and obtained room temperature infrared images [9, 10]. 2 Working principle The complete IR imaging system is shown in Fig. 1. The system is composed of BMCA and a series of lenses. 2.1 BMCA BMCA is sealed in a vacuum chamber to prevent dissipation of heat [11]. Figure 2 shows the top view of the pixel of BMCA. The reflector (micro-mirror) is supported by two SiNx legs which are selected coating by gold film [12]. When the incident IR flux is absorbed by a pixel in the BMCA, the pixel s temperature rises, and then causes a small inclination angle θ of the micro-mirror because of the mismatch of thermal expansion coefficients between the two materials [12], which is shown in Fig. 3. Fig. 1 The schematic diagram of the whole IR imaging system.

3 Int J Infrared Milli Waves (2008) 29: Fig. 2 The top view of BMCA. The reflector and deformation cantilever are composed of SiNx beam coating with gold, and isolation cantilever is SiNx beam without gold. 2.2 Optical read-out method Visible light that comes from the LED through the pinhole becomes parallel via collimating lens. Subsequently the parallel light is reflected by the reflectors of the BMCA and then passes through transforming lens. These reflected diffracting rays synthesize the spectra of the cantilever array on the rear focal plane of the transforming lens. Consequently the changes in the reflected visible light intensity distribution are collected and analyzed by CCD through the knife-edge filter placed in the focal plane of transforming lens. Thus, the inclinations of reflectors are converted to grey level changes in the CCD and imaged. To present this method clearly, a spatial mathematical model is created. In order to express the spectra at the rear focal plane of the transforming lens, the function of the BMCA is shown as x ðm 1=2T x Þ y t m;n ðx; yþ ¼rect ; ð n 1=2 ÞT y L x L y exp j 4p l ϑ ð m; n Þ y ð n 1 ÞT y ð1þ where (n-1)t y y nt; n=0,1,2,...; T x,t y are the length between two pixels, shown in Fig. 4; Lx, Ly are the width and the length of the micro-mirror; θ(m, n) is the inclination angle of the reflector (m, n). Fig. 3 The deforming of cantilever caused by temperature rises.

4 264 Int J Infrared Milli Waves (2008) 29: Fig. 4 The reflector in object plane. Then the field distribution at the rear focal plane of the transforming lens can be expressed as ZZ ~ S m;n x f ; y f ¼ t m;n ðx; yþexp 2π x f x þ y f y dxdy lf ¼ exp j 4π l ϑ ð m; n Þ ð n 1 ÞT y L x L y sin c L xx f ; L y y f 2ϑðm; nþ f jlf lf lf exp j 2π ðm 1=2ÞT x x f þ ðn 1=2ÞT y y f ð2þ lf where l is the light wave length; f is the focal length of the transforming lens; (x f,y f ) are the coordinates of the spectra plane. Therefore the intensities distribution is L x L 2 y S m;n x f ; y f ¼ sinc 2 L xx f ; L y y f 2ϑðm; nþf ð3þ lf lf lf It is shown that the intensities distribution is shifting with the changes of the inclination angle θ. The knife-edge filter is placed in the rear focal plane of the transforming lens to define two regions for light transmission: ON and OF, shown in Fig. 5. The knife-edge filter can be expressed as F x f ; y f ¼ sgn ðyf y f 0 Þ ¼ 0; y f y f 0 1; y f > y f 0 ð4þ

5 Int J Infrared Milli Waves (2008) 29: Fig. 5 The sketch map of filtering process. Thus the intensities of the reflectors image that CCD received is S 0 m;n ½ϑðm; nþš ¼ 2pI sl x L y ½sinðY 0 Þsin cy ð 0 Þ 2SiðY 0 ÞþpŠ ð5þ where I s is the intensity of the read-out light, Y 0 ¼ 2 Ly l ϑðm; nþ Lyyf 0 lf, SiðY 0 Þ ¼ R1 sin Y Y dy. Y 0 When the spectra intensity is shifting with the inclination of the reflector, the brightness of the image of this reflector is received by CCD changes, which as is shown in Fig. 6. Fig. 6 The relationship between inclination θ and intensity received by CCD.

6 266 Int J Infrared Milli Waves (2008) 29: Fig. 7 The micrography of BMCA. (the insert shows a single pixel). Although there is a non-linear map relationship between the inclination angle of the reflector and the reflected light intensity received by CCD when the knife-edge filter cutting the whole spectra, the map is linear when the knife-edge filter cutting the 0th order of the spectra. So with the CCD, the sensitivity of the optical read-out section is R dϑ S0 m;n ½ϑðm; nþš ¼ 4p I L sl x L y ½sin ðy 0 Þsin cy ð 0 Þ 2SiðY 0 ÞŠ ð6þ l dy when inclination angle θ is cutting the 0th order of the spectra, δy 0 ½sinðY 0 Þ sin cy ð 0 Þ 2SiðY 0 ÞŠ is a constant. Note that, to maximize the image intensity change, the predefined position of the knife-edge should be located at the 0th order of the spectra of cantilever and the read-out illumination should approach the full measuring rage of the CCD simultaneously. At the ideal condition, the sensitivity can be estimated by q min ¼ l rad ð7þ 2NL Y where N is the digitization of the CCD. It means the half length of the 0th order of the spectra is N parted by CCD quantizer. If each item is selected as the following feasible value: N=4096 (12-bit), l=0.5 μm, and L y =60 μm, the estimated sensitivity of the readout section can be grey/deg. Shown in the formula (6), the sensitivity of the read-out section is independent with the focal length of lens in the read-out section. It means the infrared imaging system we presented can be compacted to be palm portable. Table 1 BMCA s paramenters. Pixel area μm 2 Reflector area L y XL x μm 2 Cantilever length μm Cantilever width μm SiN x thickness μm Au thickness on cantileverer μm Au thickness on cantilever μm

7 Int J Infrared Milli Waves (2008) 29: Fig. 8 The image of nine reflectors in BMCA at 5 different inclination angles. (the inclination angles from 1 to 5 are: 0.065, , , , 0.007). 3 Experiment and results discussion In the experiment, a motorized precision rotary stage (MPRS), an f/0.7 IR lens, a 12 bit CCD (70 db) and a 100 X 100 BMCA are employed. The Fig. 7 shows the micrography of BMCA, and its parameters is shown in Table 1. To assess the validity of the modeling above, the BMCA is fixed on the MPRS as the read-out target. And the MPRS is set to deg per step. A series of reflector images were collected at different inclination angles. Figure 7 demonstrates the image of nine reflectors in BMCA at five different inclination angles. The intensities of nine reflectors correspond to inclination angle are shown in Fig. 8. It can be seen that the magnitudes of grey values experimentally measured are in good quantitative agreement with the results of modeling. Experimental data indicate that the read-out sensitivity of read-out section is about grey/deg, which matches well with modeling ( grey/deg). The tiny difference between experimental result and modeling result is caused by the deformation of micro-mirror, which reduces the sensitivity of the system [12]. As an infrared imaging system, its imaging ability is also tested. The thermal image of a person s hand at home temperature was obtained which is shown in Fig. 8. To define the performance of the infrared imaging system, the noise-equivalent temperature difference Fig. 9 The intensity of reflectors V.S inclination angles.

8 268 Int J Infrared Milli Waves (2008) 29: Fig. 10 The image of two fingers at V pose: (a) visible image, (b) IR image. (NETD) is introduced [11]. NETD is the equivalent temperature change in an IR source that can be detected with a signal-to-noise ratio of unity. It is expressed as NETD ¼ ð8þ $I=$T s where I noise is the grey level of the total noise andδi/δts is the thermal response sensitivity of the system and defined as the grey level change when there is a unit temperature change of the IR object. In the experiment, I noise was measured by picking 300 thermal pictures with no IR objects and the histogram was obtained. The histogram related to the noises is shown in Fig. 9. From the histogram, it clarifies that the average noises gray level is 7.2 gray levels. Therefore 8 was selected as the I noise for our system. To assess the ΔI/ΔTs, a black dyed hotplate (see Fig. 10) was used as an IR object. A series of thermal images were collected at different temperatures. Figure 11 demonstrates the distribution of the hotplate s image grey levels versus the hotplate s temperatures. It can be seen that the average value of ΔI/ΔTs of the IR detector can reach 43.6gray/K. For the I noise is 8, the average NETD of the IR imaging system can be 183 mk approx (Fig. 12 and Fig. 13). And the best pixel in the BMCA can reach 102gray/K, which means the best response can arrive at 78 mk. From the histogram, we can see the differences between pixels. It is due to the non-uniformity of the BMCA. Each pixel in the BMCA has its own stance, which causes the dispersion of the sensitivity. I noise Fig. 11 The image of black dyed hotplate: (a) visible image, (b) IR image.

9 Int J Infrared Milli Waves (2008) 29: Fig. 12 The histogram of noises. Although the current results are not comparable with pyroelectric detectors or thermopile detectors but this method has tremendous inherent ability that can be used to further improve the results. The improvement can be made in several ways: A. Decreasing the noise In the experiment the illumination (LED) was supported by a simple constant source that was composed of an operation amplifier and an audion. Testing of the CCD with the illumination shows that it can cause 5 gray level noises. Therefore the noise can be decreased, if more stable constant source is employed. Fig. 13 The distribution of the systemic sensitivity.

10 270 Int J Infrared Milli Waves (2008) 29: B. Improving the BMCA As has been tested, the BMCA in the experiment has several defects. That blind pixels, holes without pixels and its pixels are not in identical stance makes the image quality far below the extent of practical use. Improving the stability and uniformity of the fabrication equipment can solve this problem substantially. The micro-mirrors in BMCA are not ideally flat, thus the sensitivity of the system is decreased. It can be solved by employing stress matching technique in BMCA making process. C. Improving the read-out section Because of the mismatch of the pixels size of BMCA and those of CCD camera, the image reconstruction and manipulation is difficult to realize [13]. In the further work, the one-to-one correspondence between the pixels of the CCD and those of the BMCA can be built up to get high quality images. 4 Conclusion In this paper we have presented an optical readout method based uncooled infrared imaging system that contains a BMCA detector and optical read-out section. The said optical readout section is based on incoherence light spatial filter technique. The read-out section converts the deflection angles of BMCA caused by absorption of infrared (IR) radiation to a visible image through optical filtering operation of the BMCA with a knife-edge filter. The sensitivity of the read-out section is deduced to be grey/deg ideally, and tested to be grey/deg, which proved the validity of the spatial mathematical model. Notice that, the sensitivity of the read-out section is independent with the F of lens in the section, therefore the system can be compacted to be palm portable. Thermal image of a person s hand was obtained in the imaging experiment and the profile was clearly identified. The imaging results showed the system has the capability of detecting objects at about room temperature. The average NETD of this system was estimated at about 183 mk with some areas in the BMCA having a NETD as low as 78 mk. Although the current results are not comparable with bolometer detectors or thermopile detectors, the refining works are on the way to get further results. References 1. J. K. Gimzewski, Ch. Gerber, E. Meyer, and R. R. Schlittler, Observation of a chemical reaction using a micromechanical sensor. Chem. Phys. Lett. 217, 589 (1994). 2. J. R. Barnes, S. J. Stephenson, M. E. Welland, Ch. Gerber, and J. K. Gimzewski, Photothermal spectroscopy with femtojoule sensitivity based on micromechanics. Nature 372, 79 (1994). 3. J. Varesi, J. Lai, T. Perazzo, Z. Shi, and A. Majumdar, Photothermal measurements at picowatt resolution using nncooled micro-optomechanical sensors. Appl. Phys. Lett. 71, 306 (1997). 4. D. Sarid, Scanning Force Microscopy, (Oxford, New York, 1991), pp S. R. Manalis, S. C. Minne, C. F. Quate et al., Two-dimensional micromechanical bimorph arrays for detection of thermal radiation. Appl. Phys. Lett. 70, 3311 (1996). 6. Y. Zhao et al., Optomechanical uncooled infrared imaging system: design, microfabrication, and performance. J. Micromech. Sys. 11, 136 (2002). 7. T. Ishizuya, J. Suzuki, K. Akagawa et al., Optically readable bi-material infrared detector. J. Institute of Image Information & Television Engineers 55, 304 (2001).

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