Noise robust target identification based on the wave-coefficients-2dimension case

Abstract

To correctly identify a remote target in a noisy environment is very challenging. Usually, the accuracy of target recognition degrades under the condition of a low signal-to-noise ratio (SNR). Radar target identification based on wave-coefficients (WCs) is proposed and seems to be promising. We introduce the WCs of two-dimensional (2D) targets in this paper. The main problem of WC based target identification is that the extraction of wave-coefficients is an ill-posed problem. Thus the recognition results yielded in the presence of noise is not reliable. The regularization algorithm is exploited to extract the wave-coefficients, the regularization parameter is determined by the L-curve method. Simulation results using 4 2D targets show that the proposed scheme is effective and high target recognition rate is achieved in cases of low SNR scenarios.

Using Polarization-Diverse Wave-Coefficients for Aerospace Target Recognition

“…The targets' sensitivity to azimuth angle is totally embodied in the WCs. Simulation results in [22], [23] show that the WCs' sensitivity to azimuth angle is directly proportional to the working frequency. Due to the properties ofˆ( ) n J  and (2) ( ) n H  , the dimension of the WCs is augmented with increasing of the operating frequency.…”

“…In [21], the authors proposed a linear polarisation images based method for target recognition in passive millimeter-wave imaging system. Two-dimensional (2D) target identification with a feature vector termed wave-coefficients (WCs), was proposed in [22]. WC concept was extended to threedimensional (3D) targets in [23], where four aerospace targets were considered.…”