Robust airborne target recognition based on recurrence plot quantification of micro-Doppler radar signatures

A robust target recognition method proposed based on recurrence plot and recurrence quantification analysis (RQA) to generate robust features against noise, target velocity and aspect angle from micro-Doppler (m-D) signatures. The proposed method is tested on simulated data of three different targets using multiclass support vector machine (MSVM) and classification rate of about 95 % is achieved. Also, effect of noise and coherent processing time (CPT) on classification rate is investigated.