A New Sampling Mismatch Compensation Method for Moving Target Detection Based on Hooke-Jeeves Optimization Processing

Lingyu Wang, Penghui Huang*, Xiang Gen Xia, Yanyang Liu, Xuepan Zhang, Xingzhao Liu, Guisheng Liao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

In 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.

Original languageEnglish
Article number4026905
JournalIEEE Geoscience and Remote Sensing Letters
Volume19
DOIs
Publication statusPublished - 2022
Externally publishedYes

Keywords

  • Coherent integration detection
  • sampling mismatch compensation
  • sampling mismatch errors (SMEs)

Fingerprint

Dive into the research topics of 'A New Sampling Mismatch Compensation Method for Moving Target Detection Based on Hooke-Jeeves Optimization Processing'. Together they form a unique fingerprint.

Cite this