摘要
在水声多普勒因子和时延估计研究实用化的进程中,利用多分量线性调频(LFM)信号实现估计的算法研究越来越普遍。针对多分量LFM信号时频域存有交叉项时各分量参数估计不准确的问题,提出基于非完全残差与脊线段匹配的自适应模态分解方法。该方法采用非完全残差函数保留了交叉点处的部分时频信息,利用脊线段匹配方法提供更精确的预设时频脊线,改进了各分量LFM信号调频斜率和起始频率的估计精度。联合两个估计量进一步给出了多普勒因子和时延估计的算法。仿真结果表示,较现有模态分解算法,所提改进方法有效解决了估计分量过程中交叉区间断裂带来的估计误差;水声多径的条件下,该方法的多普勒因子和时延估计精度优于对比的现有方法。
The use of the multicomponent Linear Frequency Modulated(LFM)signals for estimating the underwater acoustic Doppler factor and time delay estimation is increasingly common in the practical process.An adaptive chirp-mode-decomposition algorithm based on incomplete residual and ridge segment matching is proposed to solve the problem of inaccurate parameter estimation for multicomponent LFM with cross-terms in the time–frequency domain.The incomplete residual function is used to retain part of the time-frequency information at the intersection point,and the ridge segment matching method is used to provide a more accurate time-frequency ridge,improving the estimation accuracy of the frequency modulation slope and starting frequency of each component of LFM signal.A combination of these two estimators provides the algorithm for estimating the Doppler factor and time delay.The results showed the proposed method effectively solves the estimation error induced by the break of cross-interval,compared with the existing modedecomposition algorithms.The accuracy of the proposed method for estimating the Doppler factor and time delay is better than that of the existing methods in underwater acoustic multipath propagation.
作者
宁更新
肖若君
谢靓
NING Gengxin;XIAO Ruojun;XIE Liang(School of Electronic&Information Technology,South China University of Technology,Guangzhou 510641,China;School of Civil Engineering&Transportation,South China University of Technology,Guangzhou 510641,China)
出处
《电子与信息学报》
EI
CAS
CSCD
北大核心
2024年第2期688-696,共9页
Journal of Electronics & Information Technology
基金
国家自然科学基金(61871191,62192712,62171187)
广东省基础与应用基础研究基金(2023A1515011139)。
关键词
时频分析
多普勒因子
时延估计
多分量LFM信号
自适应模态分解
Time-frequency analysis
Doppler factor
Time delay estimation
Multi-component LFM signal
Adaptive chirp mode decomposition
