KEYWORDS: Sensors, 3D acquisition, 3D modeling, Detection and tracking algorithms, 3D image processing, Image sensors, Data modeling, Computer simulations, Laser imaging, Stereoscopy
This paper reports the successful application of automatic target recognition and identification (ATR/I) algorithms to
simulated 3D imagery of 'difficult' military targets. QinetiQ and Selex S&AS are engaged in a joint programme to build
a new 3D laser imaging sensor for UK MOD. The sensor is a 3D flash system giving an image containing range and
intensity information suitable for targeting operations from fast jet platforms, and is currently being integrated with an
ATR/I suite for demonstration and testing.
The sensor has been extensively modelled and a set of high fidelity simulated imagery has been generated using the
CAMEO-SIM scene generation software tool. These include a variety of different scenarios (varying range, platform
altitude, target orientation and environments), and some 'difficult' targets such as concealed military vehicles. The
ATR/I algorithms have been tested on this image set and their performance compared to 2D passive imagery from the
airborne trials using a Wescam MX-15 infrared sensor and real-time ATR/I suite.
This paper outlines the principles behind the sensor model and the methodology of 3D scene simulation. An overview of
the 3D ATR/I programme and algorithms is presented, and the relative performance of the ATR/I against the simulated
image set is reported. Comparisons are made to the performance of typical 2D sensors, confirming the benefits of 3D
imaging for targeting applications.
Airborne surveillance and targeting sensors are capable of generating large quantities of imagery, making it difficult for the user to find the targets of interest. Automatic target identification (ATI) can assist this process by searching for target-like objects and classifying them, thus reducing workload. ATI algorithms, developed in the laboratory by QinetiQ, have been implemented in real-time on ruggedised processing capable of flight. A series of airborne tests has been carried out to assess the performance of the ATI under real world conditions, using a Wescam EO/IR turret as the source of imagery. The tests included examples of military vehicles in urban and rural scenarios, with varying degrees of hide and concealment. Tests were conducted in different weather conditions to assess the robustness of the sensor and ATI combination. This paper discusses the tests carried out and the performance of the ATI achieved as a function of the test parameters. Conclusions are drawn as to the current state of ATI and its applicability to military requirements.
The Kalman filter, which is optimal with respect to Gaussian distributed noisy measurements, is commonly used in the Multiple Hypothesis Tracker (MHT) for state update and prediction. It has been shown that when filtering noisy measurements distributed with asymptotic power law tails the Kalman filter underestimates the state error when the tail exponent is less than two and overestimates it when the tail exponent is greater that two. This has severe implications for tracking with the MHT which uses the estimated state error for both gating and probability calculations. This paper investigates the effects of different tail exponent values on the processes of track deletion and creation in the MHT.
This paper describes a signal processing technique that has been developed for a vibration-sensing laser radar. The sensor has successfully acquired data from moving objects. Vibrations on the surface of the object can be induced by internal machinery and, when stationary, would normally be seen as modulations about a fixed carrier frequency. Thus a straightforward demodulation technique can be used to identify any important vibration characteristics. However, for a moving object, the laser transmit frequency is Doppler-shifted upon reflection by an amount proportional to the object's velocity resolved along the line-of-sight of the sensor. Therefore, the carrier frequency of the return signal is not known and the range of frequencies that it could occupy is large in comparison to the bandwidth of the modulations. The algorithm locates the carrier frequency within some large range (typically tens of Megahertz) and generates a synthetic mixing signal that allows the carrier to be down-shifted to baseband. Tracking is performed using a series of Kalman filters on all likely signal candidates and the synthetic mixing signal is made up of the set that scores highly in terms of carrier-to- noise ratio, for example. Following the mix, the resultant signal is decimated so that modulations corresponding to the surface vibration can be studied. This paper illustrates the signal tracking technique applied to a number of real data sets and discusses the benefits of using a predictive method.
The SPIRIT system is a spectrally agile IR imaging airborne camera, with the capability to select any of the multiple filters on a frame by frame basis. The implemented solution employs advanced, but proven, technology to meet the objectives, and achieved good spatial and thermal performance in all modes. Sophisticated electronic design has results in a flexible unit, which can respond to the changing requirements of the user. Initial SPIRIT flight trials were undertaken in summer 1998 with more scheduled to continue through 1999. The sensor was installed on to DERA's TIARA research platform, a modified Tornado F2. The flight trials to date have been conducted over a variety of scenarios, collecting spectral data in up to 12 bands, of other aircraft, tanks, and fixed targets. Further ground- based trials, with the sensor mounted on a pan and tilt tracking platform, have been performed on characterized targets and against further air targets. Data from these initial trials are currently being processed to assess whether sufficient spectral information is available to discriminate between target types at militarily significant ranges. Sample hyperspectral imagery form SPIRIT and some results are presented.
This paper describes algorithm development work undertaken out for the long-range detection and tracking of air targets in an air to air scenario. Algorithm developments to operate in the search, detect and track modes of an IR search and track equipment are described. In particular, recent work in a variation of the technique known as track before detect has demonstrated good performance in this role. The result of some of this work, derived from demonstration of the algorithms against imagery from airborne trials of flying IRST equipment are presented here.
The optimization of algorithms for an airborne infra-red search and track (IRST) demonstrator is described. Models of the detection and tracking algorithms have been produced and evaluated using real trails data. An automated process, using a genetic algorithm, was used to optimize the performance and significant improvements have been achieved. Various performance metrics have been developed to quantify performance of the algorithm.
The objective of the infrared search and track (IRST) program was to develop a demonstration system capable of long range detection and tracking of air targets in an airborne environment. This paper describes each of the major subsystems of the IRST equipment, which comprises a pointing and stabilization system, a thermal imaging system and a signal processing unit. The various modes of operation are outlined which provide the capability to search for, detect and track multiple targets; to track and display imagery of a selected target and to provide passive ranging information. A brief discussion of the installation and trials is given. Finally, a discussion of future system capabilities is given. The equipment is being flown by the Defence Research Agency in an experimental Tornado aircraft and further details are given in the paper titled 'Optimization of IRST algorithms,' P. N. Randall and A. J. Seedhouse, Defence Research Agency (Farnborough), UK.
A 3-dimensional kinematic ranging algorithm for IRSTs is described, capable of real-time operation at greater than 25 Hz. The algorithm implements two 2-dimensional extended Kalman filters to estimate range in azimuth and elevation which are then combined to give the 3-dimensional range. Also included are algorithms for target manoeuvre detection and for determining the confidence of the range estimate. Simulation results for the algorithm are presented, which show that accuracies of better than 20% can be achieved at long range, depending on the measurement accuracy.
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