CAJ | 학술논문

微动参数估计是提高雷达识别舰船目标能力的重要途径。针对目前复杂运动舰船微动特征参数估计困难和实时性差的问题，在分析舰船目标回波信号时频特征基础上，提出了一种基于回波信号时频矩阵稀疏后移位互相关的微动周期快速估计新方法。通过求解稀疏时频矩阵的后移位互相关系数矩阵和检测其 k阶对角阵的平均相关系数峰值位置，进而快速估计目标微动周期。相比已有方法，该方法能够准确估计出舰船的微动周期，且运算效率明显提高。仿真实验验证了文中方法的有效性。
미동삼수고계시제고뢰체식별함선목표능력적중요도경。침대목전복잡운동함선미동특정삼수고계곤난화실시성차적문제，재분석함선목표회파신호시빈특정기출상，제출료일충기우회파신호시빈구진희소후이위호상관적미동주기쾌속고계신방법。통과구해희소시빈구진적후이위호상관계수구진화검측기 k계대각진적평균상관계수봉치위치，진이쾌속고계목표미동주기。상비이유방법，해방법능구준학고계출함선적미동주기，차운산효솔명현제고。방진실험험증료문중방법적유효성。
Micro‐motion parameter estimation is an important way to improve ability of radar to detect the ship target . Focusing on the difficulty and speed problems existing in the current parameter estimation method of a complex moving ship , based on the analytical result of the echo's time‐frequency features , a novel method to estimate the micro‐motion period by calculating the backward shift cross‐correlation coefficients of the echo's sparse time‐frequency matrix is proposed in this paper . Firstly , the backward shift cross‐correlation coefficients of the echo's sparse time‐frequency matrix are calculated using the FFT ( fast Fourier transform) algorithm . The peaks positions of the cross‐correlation coefficients matrix are then detected . Finally , the period can be figured out quickly . Compared with the general method , the proposed method can estimate the micro‐motion period accurately and quickly . A computer simulation is given to illustrate the effectiveness of the proposed method .