We present a novel backside-illuminated single photon avalanche diode (SPAD) which is compatible with standard CMOS technology. The structure of SPAD is based on p-i-n junction which is the first time to be used to backsideilluminated structure, thus enabling a significantly low dark count rate (DCR). In order to get better photon detection efficiency (PDE) in near-infrared , we optimized the junction width and thickness of the device. The structure of SPAD is designed by the TCAD Devedit tool, and some important characteristic parameters are extracted by the Atlas tool. We calculate DCR and PDE using the extracted parameters. At 5 V excess bias voltage, the DCR of 0.81 Hz/μm2 is achieved at room temperature. The PDE at 5 V excess bias voltage is 20%. The fill factor is up to 53%. The DCR of the structure has reached the international advanced level.
In this paper, a dual-parameter measurement scheme based on a fiber loop mirror (FLM) assisted reflective long period fiber grating (LPFG) is proposed and experimentally demonstrated. Due to the Sagnac fiber loop mirror, a reflective long period fiber grating was generated resulting in a compact sensing routing design. Moreover, the refractive index and temperature could be simultaneously determined through monitoring two dips’ wavelength shifts of the FLM assisted reflective LPFG. Experimental results show that the RI sensitivity of the sensor is from 34.48nm/RIU to 241.12nm/RIU in the RI range from 1.3467 to 1.4526, and the temperature sensitivity can reach 1.5274 nm / °C.
The working principle of LPFG(Long-Period Fiber Grating) is based on coupling effect between propagating core-mode
and co-propagating cladding-modes. The effective refractive index of cladding-modes could be obviously influenced by the environmental changes resulting in LPFG more sensitive than FBG (Fiber Bragg Grating) in sensing areas, such as temperature, strain, concentration, bending and etc. LPFG should have more potential in the field of sensors compared with FBG. One of the challenges in using LPFG for environmental sensing is how to interrogate the signal from the LPFG transmission spectrum, due to the large spectral range of the resonant dip. Nowadays the application of LPFG is normally limited in signal interrogation of FBG as optical edge filter. The signal interrogation of LPFG itself needs further research. Presently research on signal interrogation of fiber grating focuses on wavelength interrogation. The aim of wavelength interrogation is to get the wavelength shift caused by environmental change. To solve these problems, a kind of strain sensing interrogation technique for LPFG with low-cost based on tunable FBGs has been developed. Comparing with the method using Fabry-Perot cavity, tunable FBGs can lower the cost with the guarantee of sensing precision. The cost is further lowered without using expensive optical instruments such as optical switch. The problem of temperature cross-sensitivity was solved by using reference gratings. An experiment was performed to demonstrate the interrogation system. And in the experiment, the sensing signal of LPFG applied 0-1300με was successfully interrogated. The results of the interrogation system and OSA are similar.
Noise in the optical fiber sensing system, produced in laser, transmission, demodulation and environment, reduces the
Signal-to-Noise Ratio (SNR) and the measuring accuracy of the whole system . In this paper, a statistical approach based
on Kalman-filter is undertaken to removal noise of the measured object real time, and then to improve the accuracy of
the fiber sensing system. The temperature induced by fiber sensing is modeled as a discrete-time state variable by a
Gauss-Markov random process with the Gaussian white and additive noise in the linear dynamic system. Based on
Bayesian MAP Inference and minimum mean-square error criterion (MMSE), gain of the kalman-filter and the state
error covariance can be regulated by Measurement Update equations to correct posteriori state estimate. Such recursive
algorithm can finally get the optimum estimator of the state through time.
The performances of the model and the algorithm are investigated in the DOFS temperature sensing system. Variance is
used to evaluate its performance in noise removal. At the same time, the experimental results of the method proposed is
compared with original measurement data analysis. The algorithm performs more improvement in accuracy of the fiber
sensing system, and implements the real-time measurement.
When the size of a needing scene is beyond the scope of an optical sensor, it is difficult to take the whole scene at the same time. In this case, the needing scene can be captured by several optical sensors at one time, the overlapped images can be taken. Using the images, the whole scene is reproduced. This paper presents a robust image mosaics method that employs wavelet transform technique. The new developed registration and fusion algorithm implemented automatically and simultaneously without known camera motion and focal length. Wavelet transform guarantees not only a global optimal solution, but also scale and transform invariance for image alignment. This feature guarantees that the scheme has higher performance than the traditional mosaic techniques. In the same time, the hardware structure and the software designing principle of the Image Mosaics System (IMS) based on the Digital Signal Processor are expounded. To further improve the image mosaics quality, an image enhancement approach is also employed. In the paper, the concept, algorithm and experiments are described. The test results showed that the IMS is efficient and accurate for acquisition of seamless mosaic of the overlapped images, and at the same time, is adaptive to the real-time requirements. An adaptive resolution, seamless and a wide field of view image can be acquired.
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