Information-Theoretic Feature Selection for Human Micro-Doppler Signature Classification

Tekeli, Burkan
Gurbuz, Sevgi Zubeyde
Yüksel Turgut, Ayşe Melda
Micro-Doppler signatures can be used not only to recognize different targets, such as vehicles, helicopters, animals, and people, but also to classify varying activities, e.g., walking, running, creeping, and crawling. For this purpose, a plethora of features have been proposed in the literature; however, dozens of features are not required to achieve high classification performance. The topic of feature selection has been under addressed in micro-Doppler studies. Moreover, the optimal feature set is not static but varies under different operational conditions, such as signal-to-noise ratio (SNR), dwell time, and aspect angle. The mutual information of features relative to the classification problem at hand offers a measure for assessing the efficacy of features and thus sets a unique framework for feature selection. In this paper, information-theoretic (IT) feature selection techniques are used to identify essential features and minimize the total number of required features, while maximizing classification performance. It is seen that, although some features are consistently preferred, others are never selected. Results show that for SNRs over 10 dB and at least 1 s of data, this approach yields 96% correct classification when the target moves along the radar line-of-sight and over 65% correct classification for tangential motion.


Mutual Information of Features Extracted from Human Micro-Doppler
Tekeli, Burkan; Gurbuz, Sevgi Zubeyde; Yüksel Turgut, Ayşe Melda (2013-01-01)
The unique, bi-pedal motion of humans has been shown to generate a characteristic micro-Doppler signature in the time-frequency domain that can be used to discriminate humans from not just other targets, but also between different activities, such as walking and running. In the literature, many different features have been proposed for classification applications. However, it is not known which features have a greater impact on classification performance, or indeed how many features should be used to achiev...
Feature Selection for Classification of Human Micro-Doppler
Gurbuz, Sevgi Zubeyde; Tekeli, Burkan; Karabacak, Cesur; Yüksel Turgut, Ayşe Melda (2013-01-01)
Dozens of features have been proposed for the use in a variety of human micro-Doppler classification problems, such as activity classification, target identification, and arm swing detection. However, the issues of how many features are truly required, which features should be selected, and whether or how this selection will vary depending upon human activity has not yet been rigorously addressed in the context of human micro-Doppler analysis. Moreover, most classification results are present for the case w...
Micro-Doppler analysis of rotary-wing air vehicles using pulsed-Doppler radar
Aybar, Bahadir; Yılmaz, Ali Özgür (2018-07-05)
In this paper, micro-Doppler signatures of rotary-wing unmanned aerial vehicles (UAVs) are investigated in order to classify these air targets, to distinguish them from birds and clutter and to specify their types using experimental data. Radar parameters required for extracting the micro-Doppler signatures of rotary-wing air targets with different blade lengths are studied. Experimental data taken from different targets using a medium Pulse Repetition Frequency (PRF) pulsed-Doppler surveillance radar is an...
Parametric estimation of clutter autocorrelation matrix for ground moving target indication
Kalender, Emre; Tanık, Yalçın; Department of Electrical and Electronics Engineering (2013)
In airborne radar systems with Ground Moving Target Indication (GMTI) mode, it is desired to detect the presence of targets in the interference consisting of noise, ground clutter, and jamming signals. These interference components usually mask the target return signal, such that the detection requires suppression of the interference signals. Space-time adaptive processing is a widely used interference suppression technique which uses temporal and spatial information to eliminate the effects of clutter and ...
Optimization of vibration characteristics of a radar antenna structure
Baran, İsmet; Özgen, Gökhan Osman; Ciğeroğlu, Ender; Department of Mechanical Engineering (2011)
Radar antenna structures especially array antennas which are integrated onto structures of aerial vehicles are subject to dynamic structural and aerodynamic loads. Due to occurrences of these dynamic loads there will be certain dynamic deformations which affect the antenna’s performance in an adverse manner. The influence of deformations and vibrations are important on array antenna structures, since they cause a change in orientation of elements of the phased array antenna which affects the gain of the ant...
Citation Formats
B. Tekeli, S. Z. Gurbuz, and A. M. Yüksel Turgut, “Information-Theoretic Feature Selection for Human Micro-Doppler Signature Classification,” IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, vol. 54, no. 5, pp. 2749–2762, 2016, Accessed: 00, 2022. [Online]. Available: