Performance Analysis Of Co-Located And Distributed Mimo Radar For Micro-Doppler Classification
| Autor: | Mustafa Bugra Ozcan, Sevgi Zubeyde Gurbuz, Adriano Rosario Persico, Carmine Clemente, John Soraghan |
|---|---|
| Rok vydání: | 2016 |
| Předmět: | |
| Zdroj: | Scopus-Elsevier European Radar Conference 2016, EuRAD 2016 University of Strathclyde |
| Popis: | 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 multi-perspective features yields higher classification performance as compared to a co-located configuration or feature vector concatenation. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|