Constant False Alarm Rate Detection of Doppler-Distributed Targets in Low-Rank Partly Homogeneous Clutter

TY - JOUR

T1 - Constant False Alarm Rate Detection of Doppler-Distributed Targets in Low-Rank Partly Homogeneous Clutter

AU - Tian, Weiming

AU - Lin, Ruiqi

AU - Deng, Yunkai

AU - Chen, Youwang

AU - Fang, Delin

AU - Xie, Xin

N1 - Publisher Copyright: © 1965-2011 IEEE.

PY - 2026

Y1 - 2026

N2 - In the presence of Gaussian noise and low-rank, partly homogenous clutter, detectors based on the full-rank assumption lose the constant false alarm rate (CFAR) property, while those relying on clutter nulling perform poorly for targets within the clutter subspace. This article addresses the CFAR detection problem of Doppler-distributed targets via invariance theory. Assuming that the target lies in the target subspace, its detection problem is transformed into a canonical form by both the clutter and target subspaces. Then, the maximal invariant statistics and the conditions for CFAR detection are derived via invariance theory. Following this framework, the generalized likelihood ratio test is decomposed to obtain two CFAR components for the clutter subspace echo and the noise subspace echo. When the clutter subspace is known, a CFAR detector is constructed by combining the two components with the weight that maximizes detection probability. With an unknown clutter subspace, the test is further generalized into an asymptotic CFAR detector based on the clutter subspace estimate and the asymptotic distribution of the estimate. The CFAR properties and detection performances of these detectors are validated through simulations and measured clutter.

AB - In the presence of Gaussian noise and low-rank, partly homogenous clutter, detectors based on the full-rank assumption lose the constant false alarm rate (CFAR) property, while those relying on clutter nulling perform poorly for targets within the clutter subspace. This article addresses the CFAR detection problem of Doppler-distributed targets via invariance theory. Assuming that the target lies in the target subspace, its detection problem is transformed into a canonical form by both the clutter and target subspaces. Then, the maximal invariant statistics and the conditions for CFAR detection are derived via invariance theory. Following this framework, the generalized likelihood ratio test is decomposed to obtain two CFAR components for the clutter subspace echo and the noise subspace echo. When the clutter subspace is known, a CFAR detector is constructed by combining the two components with the weight that maximizes detection probability. With an unknown clutter subspace, the test is further generalized into an asymptotic CFAR detector based on the clutter subspace estimate and the asymptotic distribution of the estimate. The CFAR properties and detection performances of these detectors are validated through simulations and measured clutter.

UR - https://www.scopus.com/pages/publications/105034201462

U2 - 10.1109/TAES.2026.3677192

DO - 10.1109/TAES.2026.3677192

M3 - Article

AN - SCOPUS:105034201462

SN - 0018-9251

VL - 62

SP - 8256

EP - 8270

JO - IEEE Transactions on Aerospace and Electronic Systems

JF - IEEE Transactions on Aerospace and Electronic Systems

ER -