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.
A microbolometer is an uncooled thermal sensor of infra-red radiation. In thermal imaging, microbolometers organized
in arrays called focal plane arrays (FPA) are used. Because of technological process microbolometric FPAs features
unwanted detector gain and offset nonuniformity. Because of that, the detector matrix, being exposed to uniform infrared
radiation produces nonuniform image with superimposed fixed pattern noise (FPN). To eliminate FPN, nonuniformity
correction (NUC) algorithms are used. The offset of detector in array depends from mean temperature of FPA. Every
single detector in matrix has its temperature drift, so the characteristic of every detector changes over temperature. To
overpass this problem, a temperature stabilization of FPA is commonly used, however temperature stabilization is a
relatively power demanding process. In this article a method of offset calculation and correction for every detector in
array in function of mean array temperature is described. The method of offset temperature characteristic estimation is
shown. The elaborated method let to use unstabilized microbolometric focal plane array in thermographic camera. Method of offset correction was evaluated for amorphous silicon based UL 03 04 1 detector array form ULIS.
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.
The paper presents design and principle of operation of a passive IR detector of large detection range. Significant virtue of the described PIR detector is highly efficient detection of very slowly moving or crawling people. High signal-to-noise ratio was obtained by using larger number of pyroelectric sensors or by increasing number of detection zones (channels). Larger number of pyroelectric sensors forces development of a complex optical system. The presented optical system of PIR detector consists of one lens (germanium or amtir) and mirror concentrators. The optical system ensures continuity of detection zones (no "blind" area between particular detection zones).
Original electronic system for PIR detector was described in which direct current amplifiers of a signal from pyroelectric sensors were applied. Electronic system automatically reduces a voltage drift from pyroelectric sensors, thus significantly decreases low limit frequency of a conduction band of amplification channel. Together with a fulfillment of this condition, low-frequency noises enhancement is observed and next detector sensitivity diminishes. To ensure large detection ranges, a new method of signals analysis was applied.
PIR detector has been equipped with a channel of RS 485 standard data transmission. For registration of measurement results, special software was developed for detector diagnostics allowing registration of signals from particular detection zones. The investigation results for various ranges of PIR detector were presented. The signals from PIR detector were shown which were caused by crawling people being at the distance of 140 meters and walking, running people being at the distance more than 200 meters.