KEYWORDS: Sensors, Signal processing, Data communications, Image processing, Data processing, Telecommunications, Data fusion, Infrared sensors, 3D image processing, Unmanned aerial vehicles
In the electro-optical sensors and processing in urban operations (ESUO) study we pave the way for the European Defence Agency (EDA) group of Electro-Optics experts (IAP03) for a common understanding of the optimal distribution of processing functions between the different platforms. Combinations of local, distributed and centralized processing are proposed. In this way one can match processing functionality to the required power, and available communication systems data rates, to obtain the desired reaction times. In the study, three priority scenarios were defined. For these scenarios, present-day and future sensors and signal processing technologies were studied. The priority scenarios were camp protection, patrol and house search. A method for analyzing information quality in single and multi-sensor systems has been applied. A method for estimating reaction times for transmission of data through the chain of command has been proposed and used. These methods are documented and can be used to modify scenarios, or be applied to other scenarios. Present day data processing is organized mainly locally. Very limited exchange of information with other platforms is present; this is performed mainly at a high information level. Main issues that arose from the analysis of present-day systems and methodology are the slow reaction time due to the limited field of view of present-day sensors and the lack of robust automated processing. Efficient handover schemes between wide and narrow field of view sensors may however reduce the delay times. The main effort in the study was in forecasting the signal processing of EO-sensors in the next ten to twenty years. Distributed processing is proposed between hand-held and vehicle based sensors. This can be accompanied by cloud processing on board several vehicles. Additionally, to perform sensor fusion on sensor data originating from different platforms, and making full use of UAV imagery, a combination of distributed and centralized processing is essential. There is a central role for sensor fusion of heterogeneous sensors in future processing. The changes that occur in the urban operations of the future due to the application of these new technologies will be the improved quality of information, with shorter reaction time, and with lower operator load.
Recognition and identification ranges are limited to the quality of the images. Both the received contrast and the spatial resolution determine if objects are recognizable. Several aspects affect the image quality. First of all the sensor itself. The image quality depends on the size of the infrared detector array and the sensitivity. Second, also the intervening atmosphere, in particular over longer ranges, has an impact on the image quality. It degrades the contrast, due to transmission effects, as well as it influences the resolution, due to turbulence blur, of the image. We present studies in the field of infrared image enhancement. Several techniques are described: noise reduction, super resolution, turbulence compensation, contrast enhancement, stabilization. These techniques operate in real-time on COTS/MOTS platforms. They are especially effective in the army theatre, where long horizontal paths, and short line-of-sight limited urban operations are both present. Application of these techniques on observation masts, such as on military camp sites, and on UAVs and moving ground vehicles are discussed. Examples will be presented from several trials in which these techniques were demonstrated, including the presentation of test results.
Present-day naval operations take place in coastal environments as well as narrow straits all over the world. Coastal
environments around the world are exhibiting a number of threats to naval forces. In particular, a large number of
asymmetric threats can be present in environments with cluttered backgrounds as well as rapidly varying atmospheric
conditions. The automatic detection of small targets by electro-optical systems may be hampered by small surface
structure variations at the surface and near the horizon.
In current electro-optical sensor systems processing of imagery is seldom task-specific. Using task-specific settings of
sensors, processing and fusion, can improve the performance of electro-optical systems dramatically. This paper
discusses the effect of dynamic sensor settings as function of specific tasks and environmental parameters and how these
can play a role in the management of sensors in a naval application. In addition, a series of experiments with different
targets are presented to demonstrate the benefit of sensor management. Some sensor management approaches for
application in infrared systems are discussed.
KEYWORDS: LIDAR, Target detection, Receivers, Radar, Laser systems engineering, Surveillance, Optical parametric oscillators, Sensors, Visibility, Signal to noise ratio
Coastal surveillance and naval operations in the littoral both have to deal with the threat of small sea-surface targets.
These targets have a low radar cross-section and a low velocity that makes them hard to detect by radar. Typical threats
include jet skis, FIAC's, and speedboats. Previous lidar measurements at the coast of the Netherlands have shown a very
good signal to clutter ratio with respect to buoys located up to 10 km from the shore where the lidar system was situated.
The lidar clutter is much smaller than the radar clutter due to the smoothness of the sea surface for optical wavelengths,
thus almost all laser light is scattered away from the receiver. These results show that due to the low clutter a search lidar
is feasible that can detect small sea-surface targets. Based on these promising results a search-lidar demonstrator project
has started end of year 2008. The system set-up of the search lidar demonstrator is presented and experimental results
near the coast of Holland are presented. By using a high rep-rate laser the search time is limited in order to be useful in
the operational context of coastal surveillance and naval surface surveillance. The realization of a search lidar based on a
commercially available high power and high rep-rate laser is presented. This demonstrator is used to validate the system
modeling, determine the critical issues, and demonstrate the feasibility.
In a harbor environment threats like explosives-packed rubber boats, mine-carrying swimmers and divers must be
detected in an early stage. This paper describes the integration and use of a heterogeneous multiple camera system with
panoramic observation capabilities for detecting these small vessels in the Den Helder New Harbor in the Netherlands.
Results of a series of experiments with different targets are presented. An outlook to a future sensor package containing
panoramic vision is discussed. We also investigated several aspects of the use of electro-optical systems. As for
classification, this paper concentrates on discriminating classes of small vessels with different electro-optical systems
(visual and infrared) as part of the larger process involving an operator. It addresses both selection of features (based on
shape and texture) and ways of using these in a system to assess threats. Results are presented on data recorded in coastal
and harbor environments for several small targets.
In a harbor environment threats like explosives-packed rubber boats, mine-carrying swimmers and divers must be
detected in an early stage. This paper describes the integration and use of a heterogeneous multiple camera system with
panoramic observation capabilities for detecting these small vessels in the Den Helder New Harbor in the Netherlands.
Results of a series of experiments with different targets are presented. An outlook to a future sensor package containing
panoramic vision is discussed.
In modern warfare scenarios naval ships must operate in coastal environments. These complex environments, in bays and narrow straits, with cluttered littoral backgrounds and many civilian ships may contain asymmetric threats of fast targets, such as rhibs, cabin boats and jet-skis. Optical sensors, in combination with image enhancement and automatic detection, assist an operator to reduce the response time, which is crucial for the protection of the naval and land-based supporting forces. In this paper, we present our work on automatic detection of small surface targets which includes multi-scale horizon detection and robust estimation of the background intensity. To evaluate the performance of our detection technology, data was recorded with both infrared and visual-light cameras in a coastal zone and in a harbor environment. During these trials multiple small targets were used. Results of this evaluation are shown in this paper.
In harbour environments operators should perform tasks as detection and classification. Present-day threats of small
objects, as jet skis etc, should be detected, classified and recognized. Furthermore threat intention should be analysed.
As harbour environments contain several hiding spaces, due to fixed and floating neutral objects, correct assessment of
the threats is complicated when detection tracks are intermittently known. For this purpose we have analysed the
capability of our image enhancement and detection technology to assess the performance of the algorithms in a harbour
environment. Data were recorded in a warm harbour location. During these trials several small surfaces targets were
used, that were equipped with ground truth equipment. In these environments short-range detection is mandatory,
followed by immediate classification. Results of image enhancement and detection are shown. An analysis was made
into the performance assessment of the detection algorithms.
Present-day naval operations take place in coastal environments as well as narrow straits all over the world. Coastal
environments around the world are exhibiting a number of threats to naval forces. In particular a large number of
asymmetric threats can be present in environments with cluttered backgrounds as well as rapidly varying atmospheric
conditions. In these conditions the threat contrast may be low and varying, and the amount of background clutter can be
severe. These conditions require the electro-optical means of detection and classification to be optimized in order to
have more time to act against threats. In particular the assessment of classification means is an important issue. Beside
short-range coastal paths, long-range horizontal paths with variable atmospheric conditions are of interest. The small
differences between types of vessel can help us determine the classification of the vessel type. Different payloads and
people on-board can be clues to the classification of the vessel. Operations in warmer environments, limiting the
atmospheric transmission due to water vapour absorption, are challenging. Understanding of the impact of the different
environments on the optical characteristics of threats is of great importance. For this purpose a trial was planned to
assess the optical characteristics of different types of small surface vessels in a coastal environment. During this trial a
number of small targets were used during different parts of the day and night. Furthermore positional as well as
atmospheric characterisation was performed as ground truth information. From this data a first analysis was performed
showing strong intensity fluctuation in target as well as background signal levels. At longer ranges and in coastal
environments these target signals may well be hidden within the background clutter. This data is essential to feed
models for the assessment of sensor performance in coastal environment.
KEYWORDS: Compact discs, Image analysis, Video, Digital imaging, Detection and tracking algorithms, Electronics, Video processing, Real time image processing, Cameras, Digital recording
The analysis of video observation tapes can be tedious and tiring work. An analysis system can relieve this burden and create a compilation tape autonomously. Working unattended AVACS creates a tape and a Compact Disk (CD) with only the images-of-interest.
Observation of long sequences of video images in surveillance applications may encounter several problems due to camera motion or rotation, unexpected size and speed of objects, variation of color due to sunshine and shadowy areas. Robust tracking algorithms are needed to compensate for the variations of different recording conditions. In this paper we evaluate the detection probability of our tracking algorithm with ROC curves and with synthetic degradation methods. Recorded experimental multi-sensor data is used to compare the accuracy in different spectral bands. Moving object detection in a guarded area can produce many false alarms due to the moving environment such as trees and bushes, birds and animals. By applying tracking and classification, false alarms can be reduced avoiding unnecessary recordings and preventing the displacement of guards. Track speed, size, direction and range (distance to camera) are calculated. The objects are classified roughly into classes as person, vehicle, and fast moving object or simply as moving object. The results of the algorithm applied to the experimental data and the algorithm evaluation are presented.
Birds are a potential source of frequent false alarms in Infrared Search and Track (IRST) systems. One reason is that the signals, generated by birds at short ranges (1-2 km) in IR sensors may be of the same magnitude as the signals generated by real targets (missiles) at long ranges (10-20 km). Another reason is that new generations of IRSTs have more sensitivity which brings more birds within the detection range. Furthermore military operations tend to be held more and more in coastal zones, where the frequency of occurrence of birds is greater than in the open ocean. Finally, the variety in type of birds and their flight characteristics and signature is larger. In the paper attention is spent on the IR signatures of birds in various backgrounds, including rapid variations in signature due to wing motions. Basically, these fluctuations and the flight pattern of a bird provide opportunities to encounter bird alarms in next generation IRSTs, using multiple Focal Plan Array cameras with high frame rates. One has to take into account in this process the difference between signal variations due to wing motions and scintillation for long range targets above the horizon.
Wildfires in Europe are predominantly caused by people visiting natural areas. The hazards as a result of wildfires increase particularly in densely populated areas such as Europe, since more and more people visit natural areas. The circumstances for large wildfires to occur are predominantly located in countries surrounding the Mediterranean Sea. In these countries on average 1% of their natural area resources are affected by wildfires each year. Typically, a few percent of the total number of fires is responsible for more than 95% of the total area burned. The fire season is usually during the summer and early fall. The risks for wildfires in the northern European countries are generally much lower. Typically, 0.1 - 0.2% of the total natural area is burned each year. The main season for wildfires is early spring. The interest of the authorities, that are responsible for the natural areas, in the northern European countries for autonomous wildfire surveillance is high since the efficiency of the current wildfire surveillance, such as from airplanes and lookouts, is often unsatisfactory.
Autonomous wildfire detection systems may help to reduce hazards resulting from large wildland fires. In many situations wildfires start in the duff below trees and shrubs, which are hidden from direct view by groundbased sensors overlooking forests and wildlands. Mid- and thermal infrared measurements only detect wildfires when the fire has become a crownfire, and, by then, it usually has developed into a large wildfire. Therefore, the early discovery of wildfires using groundbased, autonomous sensors should be performed by detecting smoke clouds rather than the heat of the fire, since smoke becomes earlier visible above the trees as a result of convection than the heat of the fire. A demonstration sensor is being developed to show the feasibility of an affordable system for autonomous wildland fire detection. The system is designed to minimize false alarms by simultaneously analyzing the temporal, spatial and spectral information in the acquired imagery. The groundbased sensor will be horizon scanning and will employ linear CCD's for better contrast sensitivity in three different spectral bands.
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