Title :
Location independent radar target classification method with strategy specific late-time intervals
Author :
Poyraz, S. ; Secmen, Mustafa
Author_Institution :
Dept. of Electr. & Electron. Eng., Yasar Univ., Izmir, Turkey
Abstract :
This work expounds a target classification method in the resonance scattering region having reduced target´s distance, aspect angle and noise dependencies. In the given method, crucial optimum late-time intervals of the scattered signals are determined by using time-frequency representations. The time instants belonging to maximum and mean power values in time-frequency distributions are used, which are independent from targets´ positions. Then, the feature vectors are formed for each target by using the given time-frequency distributions over these selected late-time regions at several different reference aspects, and they are eventually used for the classification in test stage. In this study, two different strategies having target-specific and signal-specific late-time intervals are designed. The simulations are carried out with lossless dielectric spheres being challenging targets in terms of scattering mechanism. The performances of designed strategies as well as other similar methods in the literature are compared for different popular time-frequency representations. It is found the strategy with target-specific late-time intervals combined with the Wigner-Ville distribution have better results such that it gives more than 70 percent accuracy for the noisy signals of SNR = 5 dB.
Keywords :
electromagnetic wave scattering; radar signal processing; radar target recognition; radar tracking; signal classification; time-frequency analysis; vectors; Wigner-Ville distribution; designed strategies performances; dielectric spheres; location independent radar target classification; mean power values; noise dependencies; resonance scattering region; scattering mechanism; signal-specific late-time intervals; strategy specific late-time intervals; target feature vectors formation; target positions; time-frequency distributions; Accuracy; Feature extraction; Indexes; Signal to noise ratio; Support vector machine classification; Time-frequency analysis; Vectors; late-time interval; radar target classification; resonance scattering region; time-frequency representation;
Conference_Titel :
Radar Symposium (IRS), 2014 15th International
Conference_Location :
Gdansk
Print_ISBN :
978-617-607-552-3
DOI :
10.1109/IRS.2014.6869295