Motion Parameter Estimation and Detection for High-Speed Weak Target in Clutter Environment

In this article, we investigate parameter estimation and detection for high-speed weak targets in cluttered environments, considering both the range migration (RM) of the target and the disturbance caused by clutter. To effectively capture the echo characteristics of the target, a “parameter estimation–detection” procedure based on the target’s echo matrix is introduced. This procedure utilizes the target’s echo matrix in the range domain, thereby preserving more detailed information about the target. Specifically, one-step and two-step maximum likelihood estimates (1S-/2S-MLE) are derived for parameter estimation, and corresponding one-step and two-step generalized likelihood ratio tests (1S-/2S-GLRT) are developed for detection purposes. Furthermore, the Cramér–Rao lower bound (CRLB) for parameter estimation is derived, providing a benchmark for analyzing the factors that influence performance. Results from simulated data as well as real unmanned aerial vehicle (UAV) target measurements demonstrate that the proposed method achieves superior performance compared to existing methods, thus validating its effectiveness.