Paper
25 August 2003 Aircraft recognition using high-resolution radar range profiles
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Abstract
The classification of aircraft into types is an important aspect of the problem of air picture compilation and is required if good situation awareness is to be maintained. If this can be achieved when the aircraft are at long range (significantly beyond visual range) then these processes may be significantly enhanced. This paper examines methods for exploiting high-resolution radar range profiles of aircraft using statistical pattern recognition techniques to produce classifications into types. The paper describes the data available, and covers pre-processing steps and the development of a range of classifiers of increasing complexity. The classifiers applied in the target recognition process include simple parametric and non-parametric methods based on single range profile samples, approaches which fuse classifications from a temporal sequence of measurements, and methods that use a sub-classing based approach. The latter technique uses multiclassifier system methods that cope well with the small training set sizes. As the assumptions in the model, and the complexity of the classifiers, increases so does the performance of the target recognition system, with error rates as low as 6% being achieved for a problem with three aircraft types. One issue with the available experimental data is that only a limited number of samples of each aircraft type are available. Care is taken to ensure the results produced using this limited data are achievable in an equivalent real-world application.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Christopher J. Willis "Aircraft recognition using high-resolution radar range profiles", Proc. SPIE 5096, Signal Processing, Sensor Fusion, and Target Recognition XII, (25 August 2003); https://doi.org/10.1117/12.488849
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Cited by 1 scholarly publication.
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KEYWORDS
Radar

Target recognition

Error analysis

Image classification

Pattern recognition

Sensors

Classification systems

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