In this paper we present a numerical method able to compute atmospheric radiance based on ray path. In this way is possible to evaluate relevant features of Infrared Search & Track (IRST) such as the so called Target Contrast Irradiance, i.e. difference between irradiance received with and without an obstacle towards a fixed Line-Of-Sight. The proposed model evaluates propagation of electromagnetic waves in parametric spectral band by means of computational procedure that relies on integral solution of radiative transfer differential equation defined in inhomogeneous domain such as atmosphere. Atmospheric properties are reconstructed by agile offline usage of MODTRAN® tool and then summarised in synthetic data structure that can be easily loaded in simulation initialization. Atmospheric data structure is devised to resume macroscopic properties of homogeneous layers, among which we mention temperature, absorption, scattering and uniform angular average of incoming radiance. Furthermore atmospheric propagation is fully described by accounting spherical/ellipsoidal geometry, extinction and emission terms, i.e. thermal and scattering radiance sources. Specifically computational algorithm has two main functions, one that reconstructs slant path individuating local delta in atmospheric layers, the other that compute incoming radiation on the basis of ray path, allowing to compute both background and target radiance. In other words the core algorithm constitutes a discrete functional that take as input local path delta in respective layers and returns radiance and transmittance. Moreover, setting electro-optics sensor resolution and target features, it is possible to evaluate theoretical performances of parametric IRST by means of TCI evaluation. Numerical approach described in this paper, called IR-ART (InfraRed Atmospheric Radiative Transfer), constitutes an accurate, fast and versatile algorithm, based on full physical description, that can be used to evaluate ideal performances or integrated in real-time simulative contest to reconstruct realistic electro-optical flux in several operative mode (e.g. IRST and FLIR) and IR spectral band. Furthermore it can be enforced with 3D target modelling to better evaluate cross-section and emission.
IRST systems development for aircraft is based on strong theoretical foundations about IR physics, on accurate management of each component and on advanced signal and data processing. Although the expected performance can be analytically estimated using detector and optics data, atmospheric models and algorithms simulations, the check in real environment remains a must for the assessment of system behaviors. In this paper, we propose an IRST product cycle named M3T which guides the system development up to the final desired performance. The process goes from theory and models to the gathering of real data during flight trials, which are used to tune the signal processing routines and test the system from all the angles. The labeling and organisation of recorded data, the calculation of metrics and the design of tools for replicating the real system behavior on ground all contribute to minimize the number of flights necessary to get the requested level of performance. Moreover, the approach described in this paper can be tailored to the user needs, driving to a proactive collaboration between industry and customers.
Cognitive radar systems adapt processing, receiver and transmitted waveform parameters by continuously learning and interacting with the operative environment. IRST systems are passive; as such no RF emission is involved. Nevertheless, the cognitive paradigm can be applied to passive sensors in order to optimize operational modes choice, platform and processing parameters on the fly. A cognitive based IRST, while enhancing the overall performance of the system, would also reduce the crew workload during the mission. In this paper, steps and challenge toward cognitive IRST are described, along with a proof-of-concept example of improved tracking capabilities using reinforcement learning methods.
Passive ranging is the process of estimating the distance between an observer (own-ship) and one or more objects (targets) by using passive sensors and angle measurements only, without electromagnetic or acoustic emissions. It is the baseline technique to complete the three dimensional tracking capability of IRST systems, able to automatically search, detect and track targets with generally higher angular resolution than Radars in completely silent mode. As well-known from literature, range is univocally linked to angle only data, when specific relative dynamics occur. In other cases, when such univocal relation does not hold, range estimation is still considered an open research topic. In this paper we select a set of informative cases, derived from our experience in analyzing real sorties data and compare four popular algorithms on the basis of a set of new metrics that, in our opinion, captures the system performance in terms of usability and reliability. Ranging algorithms performance is usually evaluated by means of distance-based metrics (as RMSE) which focus on accuracy of the estimation. Usability and reliability are taken into account here by introducing what we call the Average Range Declaration Length (ARDL) and the Truth-Representative Score (TRS).
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