The paper describes a Mid-wave Infrared (MWIR) Panoramic Sensor using existing focal plane array (FPA)
technologies and commercially available IR optics, and packaged in a relatively simple and rugged manner to provide a
360° azimuth and 60° elevation field-of-view (FOV) coverage, without any scanning mirror. This sensor can be
deployed for initial target tracking, situational awareness, perimeter security, and other applications. The basic
performance and parameters of the Sensor, such as mechanical, electrical interfaces, optical parameters, etc. are also
included. Some basic sensor performance analysis (such as target signal-to-noise ratio verses range and background
level), and field testing results are also presented and compared for some simple levels of processing.
This paper presents an end-to-end physics based performance model for a passive infrared (IR) sensor using the
Mathcad® spreadsheet. This model will calculate both temporal and spatial noise of a staring focal plane array (FPA) IR
sensor, the signal-to-noise ratio (SNR) of the sensor against different targets at different ranges (with atmospheric
effects, both turbulence and extinction considered). Finally, probability of detection (Pd) based on SNR results, against
these targets, are also discussed. This model will allow the user to easily define basic sensor parameters such as spectral
band, detector FPA format & size, field of view (FOV), optics F/#, etc. In addition, target and environmental parameters
are also considered for the analyses. This performance model will allow the user to determine if a particular IR sensor
design would meet the requirements of its operational specifications, and would help the user to refine the various
parameters of the IR sensor at the early design stage.
This paper documents the Matlab routines used to conduct infrared focal plane array (IR-FPA) sensor data analysis. Matlab is a commercially available software package that enables users to conduct a multitude of data analysis, file I/O, and generation of graphics with little or no computer programming skills. This effort was conducted in support of the US Army Tank-automotive and Armaments Command-Armament Research, Development and Engineering Center's (TACOM-ARDEC) 120 mm Precision Guided Mortar Munition (PGMM). PGMM's sensor included a 256 X 256 mid-band IR-FPA. This paper summarizes a primer generated to help train PGMM sensor engineers to use Matlab for conducting IR-FPA image analysis. A brief system description of the PGMM IR sensor will be presented, and follow by discussion on the Matlab IR-FPA image analysis, such as measurement of; FPA operability, Noise Equivalent Temperature Difference, temporal noise, spatial noise, as well as gain and offset calibration for non-uniformity correction.
As staring focal plane array (FPA) detectors become more readily available, imaging IR sensors can be constructed in more compact packages that are lighter and consume less power than first or second generation scanning IR sensor packages. However, FPA detector-based imagers typically demonstrate reduced resolution when compared to scanning systems with similar instantaneous-field-of-view. This resolution limitation is created by a the active pixel size and the spatially synchronous scene sampling native to staring FPA systems. A technique called microscanning can be used to improve the resolution of staring systems by over-sampling the scene; moving the image of the scene on the detector in a controlled fashion. This paper presents a compact MWIR staring FPA airborne forward looking infrared sensor design using microscanning for resolution improvement.
Often FLIR system performances are predicted using standard models such as FLIR92 and ACQUIRE from the US Army NIght Vision and ELectronic Sensor DIrectorate. These models typically produce results such as MRTD verses spatial frequency, NETD, and probability of detection and/or recognition ranges, etc. This paper presents and end-to-end FLIR system performance model using actual IR scene as an input, and produces visual output. This model is developed and run using a commercially available PC based scientific spreadsheet, and it can predict how an actual target would appear on the display of a particular FLIR sensor under a given atmospheric condition and range. It serves as a helpful supplement to the FLIR92 and ACQUIRE models.
In continuation of the authors previous work, this paper presents a complete two-dimensional model for a serial scan FLIR sensor. This model, developed using a commercially available scientific spreadsheet (i.e., MathCAD ver. 4.0), and taking into account of all the basic parameters of the sensor as well as the 4-bar target, can predict how any 4-bar target would appear on a display.
In recent years, with the advance in analytical and calculating ability of scientific spreadsheets and the increasing speed of PC machines, it is now possible for any sensor system designer to carry out basic performance analysis without always having to refer to special purpose performance models. The designer can use these spreadsheets to custom-make any system and subsystem models for his own purpose. The spreadsheet models presented in this paper will demonstrate the analysis of horizontal and vertical 4- bar target responses of a serial scan FLIR system by using a commercially available scientific spreadsheet (i.e., MathCAD version 4.0). The results from the model have shown excellent correlation with actual measured data. Finally, this ability to accurately predict subsystem performances have proven to be extremely useful not only during the design phase, but also during the prototyping and preproduction integration phase. Because during trouble-shooting efforts, it provides the engineers the ability to understand subsystem problems in an almost real time fashion.
Infrared imaging systems have increased in number rapidly since the early 1960's; however, system insertion has been almost entirely in military and paramilitaryapplications. In the future, infraredimaging systems wilifind increasedacceptance in commercial applications provided that system costs are reduced. FLIR Systems, Inc. was founded in response to a recognized world wide need for high quality, affordable infrared systems. In this paper we present the salient features of a serial scan forward looking infrared (FUR) system which has been developed to achieve high sensitivity and resolution in systems which are less complex and are inherently less expensive to manufacture, operate and maintain. Specifically our systems utilize an 8 to 12 micron band HgCdTe detector array consisting of two or more rows of detectors in parallel with four to six detector elements in series summed in Time Delay and Integration (TDI). The serial scan approach greatly reduces the complexity and cost of the amplification and scan conversion when compared to parallel scanned systems while a small amount ofparallel scanning reduces the scan rate to a practical level. Design considerations and manufacturing methods are reviewed with emphasis on high performance and system affordability.
Proc. SPIE. 1488, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing II
KEYWORDS: Target detection, Long wavelength infrared, Signal to noise ratio, Infrared sensors, Spatial frequencies, Sensors, Black bodies, Analytical research, Modulation transfer functions, Systems modeling
In the past, a substantial amount of engineering analyses were performed using standard office-style spreadsheets. However, advanced engineering and scientific software such as MathCAD are now available. This paper demonstrates the ease and simplicity of creating powerful workfiles using this software. As an example, a workfile is described which is used to perform basic IR sensor system analyses and development. Several system parameters are analyzed, including blackbody radiation for radiometry, diffraction-limited blur spot and MTF estimation, and arbitrary figure of merit (i.e., target-to-background signal contrast). The paper also discusses the application of the method to more complicated optical systems and analyses.