Bugra Ozcan, Mustafa and Gurbuz, Sevgi Zubeyde and Persico, Adriano Rosario and Clemente, Carmine and Soraghan, John (2016) Performance analysis of co-located and distributed MIMO radar for micro-doppler classification. In: European Radar Conference 2016, EuRAD 2016, 2016-10-03 - 2016-10-07.
Ozcan_etal_EURAD2016_performance_analysis_co_located_distributed_MIMO_radar.pdf - Accepted Author Manuscript
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Over the past few years, the use of Multiple Input Multiple Output (MIMO) radar has gained increased attention as a way to mitigate the degredation of micro-Doppler classification performance incurred when the aspect angle approaches 90 degrees. In this work, the efficacy of co-located MIMO radar is compared with that of distributed MIMO. The performance anaylsis is accomplished for three different classification problems: 1) discrimination of a walking group of people from a running group of people; 2) identification of individual human activities, and 3) classification of different types of walking. In the co-located configuration each radar is placed side by side so as to form a line. In the distributed configuration, the radar positions are separated to observe the subjects from different angles. Starting from the cadence velocity diagram (CVD), the Pseudo-Zernike moments based features are extracted because of their robustness with respect to unwanted scalar and angular dependencies. Two different approaches to integrate the features obtained from multi-aspect data are compared: concatenation and principal component analysis (PCA). Results show that a distributed MIMO configuration and use of PCA to fuse multiperspective features yields higher classification performance as compared to a co-located configuration or feature vector concatenation.
|Item type:||Conference or Workshop Item (Paper)|
|Keywords:||MIMO radar, micro-doppler classification, distributed MIMO, co-located MIMO, Electrical engineering. Electronics Nuclear engineering, Physics, Electrical and Electronic Engineering, Physics and Astronomy(all)|
|Subjects:||Technology > Electrical engineering. Electronics Nuclear engineering
Science > Physics
|Department:||Faculty of Engineering > Electronic and Electrical Engineering
Technology and Innovation Centre > Sensors and Asset Management
|Depositing user:||Pure Administrator|
|Date Deposited:||14 Apr 2016 15:43|
|Last modified:||18 Apr 2017 19:48|