The T-Mixture Model Approach for Radar HRRP Target Recognition

Abstract

Abstract-This paper addresses the problem of automatic radar target recognition using high-resolution range profile (HRRP). We develop a t-mixture model (TMM) to model radar echoes from each target as the t-distribution forms. Estimation of the model parameters is achieved using a modified expectation-maximization (EM), i.e., fuzzy EM (FEM) algorithm. Numerical simulation results show that the proposed approach can achieve good performance of robustness and higher recognition rate. It is helpful for real-time identification and the engineering implements of automatic target recognition using HRRP.Index Terms-High-resolution range profile (HRRP), radar automatic target recognition (RATR), t-mixture model (TMM), statistical model, expectation-maximization (EM).

Orthogonal maximum margin projection subspace for radar target HRRP recognition

“…X. J. Liao et al [14] use sequential HRRPs to identify the ground targets. C. Y. Wang et al [15] model the radar echoes for radar HRRP recognition by T-mixture model. M. Li et al [16] propose a sparse representation-based denoizing method for improving recognition performance using HRRP.…”