KEYWORDS: Infrared countermeasures, Monte Carlo methods, Sensors, Data modeling, Data fusion, Performance modeling, Design, Data processing, Target detection, Mathematical modeling
A mathematical model has been developed to assess the performance of different multi-sensor systems for maritime targeting applications. This model simulates the performance of two imaging cameras (visible band and infrared) together with an RF sensor. Time-dependent sensor data streams are generated, and salient target detection information is extracted using a data fusion architecture, the output of which gives closed-loop guidance commands for use within an engagement trajectory model. Gaining confidence in the model was required at two levels. Firstly, there was the need to verify that the model was correctly implemented and, secondly, the validation of the model predictions against the anticipated behaviour of a real system. To achieve the required level of confidence, a Test, Verification, and Validation (TV&V) framework was developed based around sensitivity analysis. The sensitivity analysis used single and multiple parameter variations in either defined steps or else with random values within a Monte-Carlo engagement. Multiple parameter variation was found to be particularly effective in determining issues within both the implemented model and the efficacy of the proposed system design. To visualise large volumes of data, various methods were examined, with the presentation in a time-varying polar plot form being considered the most effective.
KEYWORDS: Sensors, Data modeling, Radar, Error analysis, Optical sensors, Monte Carlo methods, Image processing, Performance modeling, Design and modelling, Systems modeling
Targeting systems are subject to multiple sources of error when operating in complex environments. To reduce the effect of these errors, modern targeting systems generally include both imaging and RF sensors. Data processing then provides target detection and classification information, and the detection streams are combined using a data fusion scheme to produce an optimal target location estimate with an associated latency. In this paper, the performance of a multi-sensor system in a maritime application is investigated using a mathematical simulator that has been developed to provide the system performance error analysis for different engagement scenarios and test conditions. This simulator is described together with the sources of targeting error such as image motion blur and radar glint. Additionally, the impact of flare and chaff countermeasures on the targeting performance is reviewed in terms of different types of target recognition and tracking algorithms.
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