Classification of airborne radar signals based on pulse feature estimation using time-frequency analysis
This paper describes the realization of an airborne radar signal type analysis and classification (ARTAC) system that uses spectrograms to obtain time-frequency representation ((t,f) representation) and then apply the related analysis tools, such as the instantaneous energy and frequency, and time-f...
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| Main Authors: | , |
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| Format: | Article |
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Science and Technology Research Institute for Defence
2015
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| Online Access: | http://eprints.utm.my/id/eprint/58052/ https://www.researchgate.net/publication/283819076_Classification_of_airborne_radar_signals_based_on_pulse_feature_estimation_using_time-frequency_analysis |
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| Summary: | This paper describes the realization of an airborne radar signal type analysis and classification (ARTAC) system that uses spectrograms to obtain time-frequency representation ((t,f) representation) and then apply the related analysis tools, such as the instantaneous energy and frequency, and time-frequency marginal, to estimate the various signal characteristics. The estimated parameters are used as input to a rule-based classifier that classifies the signal appropriately. Monte-Carlo simulation is then conducted to quantify the accuracy of signal classification at various signal-to-noise ratios (SNRs) in additive white Gaussian noise (AWGN). The methodology used achieves 90% classification accuracy at SNR of 6 dB irrespective of the identity of the signal. The performance and computational complexity (CC) of the system are also addressed in an electronic support (ES) operating scenario. |
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