Computer Simulation of Compensation Method for Infrared Focal Plane Array

A major motivation for this work is to investigate a method of computer simulation for compensating fixed pattern noise of the infrared focal plane arrays. A mathematical model of the output signal of focal plane array was established; a compensating algorithm utilizing reference source was derived and simulating programs were designed. The images of compensating process verify the influence of nonuniformity of responsibility and offset on fixed pattern noise. The result show that simulating method of investigating compensation technology for focal plane arrays is feasible, the generated images and methods can be used to the study of image recognition.

Testing System Based on Virtual Instrument for Readout Circuit of Infrared Focal Plane Array

Readout integrated circuit(ROIC) is one of the most important components for hybrid-integrated infrared focal plane array(IRFPA). And it should be tested to ensure the product yield before bonding. This paper presents an on-wafer testing system based on Labview for ROIC of IRFPA. The quantitative measurement can be conducted after determining whether there is row crosstalk or not in this system. This low-cost system has the benefits of easy expansion, upgrading, and flexibility, and it has been employed in the testing of several kinds of IRFPA ROICs to measure the parameters of saturated output voltage, non-uniformity, dark noise and dynamic range, etc.

A monolithic integrated medium wave Mercury Cadmium Telluride polarimetric focal plane array

A medium wave(MW)640×512(25μm)Mercury Cadmium Telluride(HgCdTe)polarimetric focal plane array(FPA)was demonstrated.The micro-polarizer array(MPA)has been carefully designed in terms of line grating structure optimization and crosstalk suppression.A monolithic fabrication process with low damage was explored,which was verified to be compatible well with HgCdTe devices.After monolithic integration of MPA,NETD<9.5 mK was still maintained.Furthermore,to figure out the underlying mechanism that dominat⁃ed the extinction ratio(ER),specialized MPA layouts were designed,and the crosstalk was experimentally vali⁃dated as the major source that impacted ER.By expanding opaque regions at pixel edges to 4μm,crosstalk rates from adjacent pixels could be effectively reduced to approximately 2%,and promising ERs ranging from 17.32 to 27.41 were implemented.

MBE HgCdTe:A Challenge to the Realization of Third Generation Infrared FPAs

Some results on the molecular-beam epitaxial growth of HgCdTe focusing on the requirements of the 3rd generation infrared focal plane arrays are described. Good uniformity is observed over 75mm HgCdTe epilayers,and the deviation in cutoff wavelength is within 0. 1μm at 80K. A variety of surface defects are observed and the formation mechanism is discussed. The average density of surface defects in 75mm HgCdTe epiluyers is found to be less than 300cm^-2. It is found that the surface sticking coefficient of As during HgCdTe growth is very low and is sensitive to growth temperature, being only -1 × 10^-4 at 170℃. The activation energy of As in HgCdTe was determined to be 19.5meV,which decreases as （Na - Nd）^1/3 with a slope of 3.1 × 10^-5 meV · cm. The diffusion coefficients of As in HgCdTe of 1.0 ± 0,9 × 10^-16,8 ± 3 × 10^- is, and 1.5 ± 0.9 × 10^-13 cm^2/s are obtained at temperatures of 240,380, and 440℃, respectively under Hg-saturated pressure. The MBE-grown HgCdTe is incorporated into FPA fabrications,and the preliminary results are presented.

QPSO-based algorithm of CSO joint infrared super-resolution and trajectory estimation

The midcourse ballistic closely spaced objects（CSO） create blur pixel-cluster on the space-based infrared focal plane,making the super-resolution of CSO quite necessary.A novel algorithm of CSO joint super-resolution and trajectory estimation is presented.The algorithm combines the focal plane CSO dynamics and radiation models,proposes a novel least square objective function from the space and time information,where CSO radiant intensity is excluded and initial dynamics（position and velocity） are chosen as the model parameters.Subsequently,the quantum-behaved particle swarm optimization（QPSO） is adopted to optimize the objective function to estimate model parameters,and then CSO focal plane trajectories and radiant intensities are computed.Meanwhile,the estimated CSO focal plane trajectories from multiple space-based infrared focal planes are associated and filtered to estimate the CSO stereo ballistic trajectories.Finally,the performance（CSO estimation precision of the focal plane coordinates,radiant intensities,and stereo ballistic trajectories,together with the computation load） of the algorithm is tested,and the results show that the algorithm is effective and feasible.

Infrared modeling and imaging simulation of midcourse ballistic targets based on strap-down platform

An infrared （IR） imaging simulation framework based on the strap-down platform is proposed for midcourse ballistic targets. It overcomes the shortcoming of the existing algorithms, which cannot simulate IR imaging from the entire midcourse process. The proposed framework includes three steps, target characteristic modeling, motion modeling, and imaging modeling. In imaging modeling, the staring focal plane is taken into account due to its wide employment. In order to obtain IR images of high fidelity, especially that the fluctuation of the target signal-to-noise ratio （SNR） is reasonably similar to the actual one, this paper proposes an improved IR imaging simulation method. The proposed method considers two critical factors of the pixel plane, occupy-empty ratio and defect elements, which affect the imaging of targets markedly but are neglected in previous work. Finally, the IR image sequence of high fidelity is obtained. And the correlative parameters of simulation can be set according to the given scene. Thus the generated images can satisfy the needs of algorithms validation for tracking and recognition.

New Dynamic Algorithm for IRFPA Bad Pixel Detection and Compensation Based on Statistics

Based on the analysis to the behavior of bad pixels, a statistics-based auto-detecting and compensation algorithm for bad pixels is proposed. The correcting process is divided into two stages： bad pixel detection and bad pixel compensation. The proposed detection algorithm is a combination of median filtering and statistic method. Single frame median filtering is used to locate approximate map, then statistic method and threshold value is used to get the accurate location map of bad pixels. When the bad pixel detection is done, neighboring pixel replacement algorithm is used to compensate them in real-time. The effectiveness of this approach is test- ed by applying it to I-IgCATe infrared video. Experiments on real infrared imaging sequences demonstrate that the proposed algorithm requires only a few frames to obtain high quality corrections. It is easy to combine with traditional static methods, update the pre-defined location map in real-time.

A substrate-free optical readout focal plane array with a heat sink structure

A substrate-ffee optical readout focal plane array （FPA） operating in 8-12 um with a heat sink structure （HSS） was fabricated and its performance was tested. The temperature distribution of the FPA with an HSS investigated by using a commercial FLIR IR camera shows excellent uniformity. The thermal cross-talk effect existing in traditional substrate-free FPAs was eliminated effectively. The heat sink is fabricated successfully by electroplating copper, which provides high thermal capacity and high thermal conductivity, on the frame of substrate-free FPA. The FPA was tested in the optical-readout system, the results show that the response and NETD are 13.6 grey/K （F / # = 0.8） and 588 inK, respectively.

Adaptive nonuniformity correction for IRFPA sensors based on neural network framework

For infrared focal plane graded during signal acquisition array sensors, imagery is departicularly nonuniformity. In this paper, an adaptive nonuniformity correction technique is proposed which simultaneously estimates detector-level and readout- channel-level correction parameters using neural network approaches. Firstly, an improved neural network framework is designed to compute the desired output. Secondly, an adaptive learning rate rule is used in the gain and offset parameter estimation process. Experimental results show the proposed algorithm can achieve a faster convergence speed and better stability, remove nonuniformity and track parameters drift effectively, and present a good adaptability to scene changes and nonuniformity conditions.