KEYWORDS: Sensors, Temperature metrology, Nonuniformity corrections, Signal detection, Detector arrays, Microbolometers, Cameras, Calibration, Black bodies, Camera shutters
Because of a significant impact of the microbolometer array temperature on the infrared image quality, it is necessary to compensate the influence of the temperature on the NUC process. In the most common applications two approaches are used: the first is a stabilization of the microbolometer array temperature by a thermoelectric cooler, the second is updating correction coefficients obtained from reference source, for example a shutter [14]. Both of the most common approaches have theirs disadvantages. The first case needs a considerable amount of energy for temperature stabilisation. The second one needs a reference target and a mechanical procedure to place the target at the front of the detector. Additionally, during calibration the reference target is blocking radiation from the scene, thus interrupting measurements with the thermal camera. In the article a non-uniformity correction method is presented which allows to compensate for the influence of detector’s temperature drift. For this purpose, dependency between output signal value and the temperature of the detector array was investigated. Additionally the influence of the temperature on the Offset and Gain coefficients was measured. Presented method utilizes estimated dependency between output signal of detectors and their temperature. In the presented method, the dependency between output signal value and the temperature of the detector is estimated during time of starting detector. The coefficients are estimated for every pixel. In the article proposed method allows to compensate the influence of detectors temperature fluctuation and increase a time between shutter actuation process.
Contemporary infrared detector arrays suffers from technological imprecision which causes that the response to uniform radiation results in nonuniform image with superimposed fixed pattern noise (FPN). In order to compensate this noise there is a need to evaluate detectors characteristics like responsivity and offset of every detector in array. In article the method of determining the responsivity of detectors in a microbolometer array is described. In the method geometrical and optical parameters of the detector array and the measurement system are taken into account. A special test bench was constructed and is consisting of: two precise surface black bodies, aperture limiter, an electronic interface for data acquisition and software for measurement and correction of results with optical parameters of the measuring stand taken into account. Constructed aperture limiter enables evaluation of optical paths in measurement stand with equivalent relative aperture F# from 0.5 to 16.1 In order to evaluate the impact of optical path to radiation distribution in the measurement system, special radiation model was elaborated and evaluated in Zemax software. Incident radiation intensity distribution on the detector surface was calculated using Monte-Carlo method for various parameters of the optical path in the measurement system. Calculated radiation maps were used to compensate radiation intensity nonuniformity of optical measurement system giving more precise responsivity evaluation of detector array parameters. The obtained values of voltage responsivity of the detectors in the array, can be used in algorithms like nonuniformity correction and radiometric calibration of the infrared camera. In article results of responsivity evaluation is presented for microbolometer infrared arrays from ULIS company (France).
A modification of Sum-of-Squared-Differences algorithm is proposed to improve tracking efficiency of small objects in
infra-red image sequences. The reason to use SSD algorithm is its better performance in tracking small objects, than in
model based tracking algorithms. However traditional Sum-of-Squared-Differences (SSD) algorithm is sensitive to
partial or full occlusions, background clutter and changes in object appearance. To increase immunity to this kind of
noises the modification in model update procedure was developed. The experimental results illustrate that the proposed
modification to SSD algorithm can improve overall algorithm performance in infrared operation. The paper describes the
Sum-of-Squared Differences algorithm and its principal features in tracking objects on thermal image sequences. Next
modification to SSD algorithm is described. Finally the experimental results are presented with comparison between
traditional and modified SSD algorithm.
The paper discusses technical possibilities to build an effective electro-optical sensor unit for sniper detection using
infrared cameras. This unit, comprising of thermal and daylight cameras, can operate as a standalone device but its
primary application is a multi-sensor sniper and shot detection system. At first, the analysis was presented of three
distinguished phases of sniper activity: before, during and after the shot. On the basis of experimental data the
parameters defining the relevant sniper signatures were determined which are essential in assessing the capability of
infrared camera to detect sniper activity. A sniper body and muzzle flash were analyzed as targets and the descriptions of
phenomena which make it possible to detect sniper activities in infrared spectra as well as analysis of physical limitations
were performed. The analyzed infrared systems were simulated using NVTherm software. The calculations for several
cameras, equipped with different lenses and detector types were performed. The simulation of detection ranges was
performed for the selected scenarios of sniper detection tasks. After the analysis of simulation results, the technical
specifications of infrared sniper detection system were discussed, required to provide assumed detection range. Finally
the infrared camera setup was proposed which can detected sniper from 1000 meters range.
The paper presents some practical aspects of sniper IR signature measurements. Description of particular signatures
for sniper shot in typical scenarios has been presented. We take into consideration sniper activities in the open area
as well as in urban environment. The measurements were made at field test ground. High precision laboratory
measurements were also performed. Several infrared cameras were used during measurements to cover all
measurement assumptions. Some of the cameras are measurement-class devices with high accuracy and frame rates.
The registrations were simultaneously made in UV, NWIR, SWIR and LWIR spectral bands. The infrared cameras
have possibilities to install optical filters for multispectral measurement. An ultra fast visual camera was also used
for visible spectra registration. Exemplary sniper IR signatures for typical situation were presented. LWIR imaging
spectroradiometer HyperCam was also used during the laboratory measurements and field experiments. The
signatures collected by HyperCam were useful for the determination of spectral characteristics of shot.
Infrared cameras are used in various military applications for early detection and observation. In applications where very
fast image acquisition is needed the so called cooled detectors are used. Cooled detectors are a kind of detectors that
demands cryogenic cooling, but in return provide exceptional performance and temperature sensitivity with low
integration times. These features predestinate cooled detectors for special purposes like airborne systems, where fast and
precise infrared radiation measurement is needed. Modern infrared cooled detector arrays like HgCdTe Epsilon detector
from Sofradir with spectral range of 3.5μm-5μm can provide high frame rate reaching 140Hz with full frame readout.
Increasing frame rates of cooled infrared detectors demands fast and efficient image processing modules for necessary
operations like nonuniformity correction, bad pixel replacement and visualization. For that kind of detector array a fast
image processing module was developed.
The module is made of two separate FPGA modules and configuration processor. One FPGA was responsible for
infrared data processing, and was performing nonuniformity correction, bad pixel replacement, linear and nonlinear
filtering in spatial domain and dynamic range compression. Second FPGA was responsible for interfacing infrared data
stream to standard video interfaces. It was responsible for frame rate conversion, image scaling and interpolation, and
controlling ASICs for video interface realization. Both FPGAs use several external resources like SRAM and DRAM
memories. The input interface was developed to connect with Epsilink board which is a standard proximity board
provided by Sofradir for this kind of detector. The image processing chain is capable of performing real-time processing
on data stream of volume up to about 40 Megapixels per second.
In article a digital system for high resolution infrared camera control and image processing is described. The camera is
built with use of bolometric focal plane array of size 640 by 480 detectors. Single detector in array has size of 25 μm and
can detect incident radiation from the spectral range of 8÷12 μm thanks to the special filter installed in specially designed
entrance window. The most important tasks of infrared image processing system are array readout and correction of
detectors offset and responsivity variations. The next tasks of the system are conversion of analog voltage signals from
microbolometers in array to digital form and then composition of a thermal image. Microbolometer array needs to be
controlled via several signals. The signal generator for readout circuit is capable of changing various timing parameters
like frame rate or integration time of the detector array. The changes in these parameters can be done via special set of
memory mapped registers. The infrared data received from detector array is transferred via data bus to modules
performing image processing, for example techniques for image enhancement. Image processing algorithms necessary
for infrared image generation are nonuniformity correction, bad pixel replacement and radiometric calibration.
Optionally an additional image processing techniques can be performed like edge enhancement, dynamic range
compression or object identification. The elaborated architecture of the system allowed easy change of parameters of the
system and to adopt many new algorithms without significant hardware changes. Scientific work funded from science
fund for years 2009-2011 as a development project.
Rapid development of infrared detector arrays caused a need to develop robust signal processing chain able to perform
operations on infrared image in real-time. Every infrared detector array suffers from so-called nonuniformity, which has
to be digitally compensated by the internal circuits of the camera. Digital circuit also has to detect and replace signal
from damaged detectors. At the end the image has to be prepared for display on external display unit. For the best
comfort of viewing the delay between registering the infrared image and displaying it should be as short as possible. That
is why the image processing has to be done with minimum latency. This demand enforces to use special processing
techniques like pipelining and parallel processing.
Designed infrared processing module is able to perform standard operations on infrared image with very low latency.
Additionally modular design and defined data bus allows easy expansion of the signal processing chain. Presented image
processing module was used in two camera designs based on uncooled microbolometric detector array form ULIS and
cooled photon detector from Sofradir. The image processing module was implemented in FPGA structure and worked
with external ARM processor for control and coprocessing. The paper describes the design of the processing unit, results
of image processing, and parameters of module like power consumption and hardware utilization.
In areas like military systems, surveillance systems, or industrial process control, more and more often there is a need to
operate in limited visibility conditions or even in complete darkness. In such conditions vision systems can benefit by
using thermal vision cameras. In thermal imaging an infrared radiation detector arrays are used. Contemporary infrared
detector arrays suffers from technological imprecision which causes that the response to uniform radiation results in
nonuniform image with superimposed fixed pattern noise (FPN). In order to compensate this noise there is a need to
evaluate detectors characteristics like responsivity and offset of every detector in array. Some of the detectors in cooled
detector arrays can be also defective. Signal from defective pixels has to be in such system replaced. In order to replace
defective pixels, there is a need to detect them. Identification of so-called blinking pixels needs long time measurement,
which in designed calibration stand is also possible. The paper presents the design of infrared detector array
measurement stand allowing measurement of mentioned parameters. Measurement stand was also used to evaluate
temporal noise of infrared detection modules. In article there is a description of optical system design and parameters of
used reference blackbodies. To capture images from camera modules a specially designed digital image interface was
used. Measurement control and calculations were made in specially written IRDiag software. Stand was used to measure
parameters for cameras based on cooled focal plane arrays from Sofradir. Results of two-point nonuniformity correction
are also presented.
KEYWORDS: Acoustics, Signal detection, Land mines, Signal analysis, Signal analyzers, Sensors, Reconnaissance systems, Classification systems, Signal generators, Mining
The methods of detection and identification of objects based on acoustic signal analysis are used in many applications, e.g., alarm systems, military battlefield reconnaissance systems, intelligent ammunition, and others. The construction of technical objects such as vehicle or helicopter gives some possibilities to identify them on the basis of acoustic signals generated by those objects. In this paper a method of automatic detection, classification and identification of military vehicles and helicopters using a digital analysis of acoustic signals is presented. The method offers a relatively high probability of object detection in attendance of other disturbing acoustic signals. Moreover, it provides low probability of false classification and identification of object. The application of this method to acoustic sensor for the anti-helicopter mine is also presented.
KEYWORDS: Sensors, Signal detection, Signal to noise ratio, Sun, Signal processing, Detection and tracking algorithms, Signal analysis, Infrared detectors, Infrared sensors, Interference (communication)
PIR detectors used in security systems for people detection operate in far IR range (8÷14) mm. These detectors most frequently employ pyroelectric sensors. Application of a single pyroelectric sensor does not ensure distinguishing the phenomena of alarm character from, so-called, false alarms caused by, e.g., air turbulences or changes in a background temperature resulting from sun radiation. Thus, in PIR detectors, the sensors with two active elements are used (two sensors) and an alarm signal is determined on the basis of analysis of a difference (or a sum) and their output signals. Essential drawback of currently available PIR detectors is low efficiency of detection of slowly moving or crawling people. Efficiency of detection of slowly moving objects is low because radiation from such objects is close to background thermal noises.
The presented signal analysis is based on determination of average moving value in three "time windows" of a defined wavelength. Moreover, a principle of "time windows" creation is given and an algorithm for determination of detection thresholds is described. In PIR detector, an adaptation detection threshold was taken following thermal changes of a background. Influence of sun radiation is taken into account in the algorithm of determination of adaptation detection threshold.
The paper presents the LPP series of biostimulative systems which are based on semiconductor lasers. These devices are characterized by the following properties: microprocessor controlling, modulus structure, and three wavelength of operation.
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