Wang, LingyuHuang, PenghuiXia, Xiang-GenLiu, YanyangZhang, XuepanLiu, XingzhaoLiao, Guisheng2022-09-302022-09-302022-09-08L. Wang et al., "A New Sampling Mismatch Compensation Method for Moving Target Detection Based on Hooke–Jeeves Optimization Processing," in IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2022, Art no. 4026905, doi: 10.1109/LGRS.2022.3205157.1558-0644https://udspace.udel.edu/handle/19716/31426© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This article was originally published in IEEE Transactions on Geoscience and Remote Sensing. The version of record is available at: https://doi.org/10.1109/LGRS.2022.3205157In this letter, we propose a novel range and Doppler sampling mismatch compensation method for moving target detection, which can effectively improve the output signal-to-noise ratio (SNR) of a moving target. In the proposed method, after performing the target coherent integration by using the well-known Keystone transform (KT), the range and Doppler sampling mismatch errors (SMEs) are estimated and compensated based on the constructed optimization model with the consideration of the change rate of a moving target peak amplitude. In order to improve the computational efficiency, the Hooke–Jeeves method is applied to achieve the optimal solution of the constructed optimization problem, thus efficiently solving the target energy diffusion problem caused by the SMEs. Simulated experiment is presented to verify the effectiveness and feasibility of the proposed method.en-USCoherent integration detectionsampling mismatch compensationsampling mismatch errors (SMEs)Article