Data gathering trials remain an important part of the development and testing of imaging sensor systems. However, the role of trials has evolved to reflect emergent technology, engineering methodologies, operational requirements, and project constraints such as schedule and cost. The changing nature of data gathering trials is reviewed. Although trial programmes are still used for product acceptance, there has been an increased demand for trial data to support the design process. In this paper, the emphasis is on air-to-ground image-based military systems where the timely availability of relevant image data is critical to the development of advanced image processing software which, in turn, underpins the performance of the latest imaging systems. Other factors which affect the nature of trial programmes are also considered. These include the widespread availability of synthetic image generators and the use of low-cost drones as either targets or sensor platforms. Furthermore, the increasing use of AI data processing techniques demands a larger and more diverse image data set for training and evaluation purposes. Against this background of changing requirements, trial planning has become increasingly important. Although the great flexibility of low-cost commercial drones has resulted in them becoming a preferred solution for camera platforms, they present unique challenges, ranging from logistics through to image truthing of target locations. These issues are discussed, and recommendations made based on experience gained through multiple trial programmes.
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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