摘要
基于基函数向量矩阵的二维离散余弦变换(2D-DCT),本文提出了一种改进的时变自回归(TVAR)模型辨识算法。然后用改进的TVAR模型对多分量Chirp信号进行建模,结合Radon变换和逐次消去技术,提出一种称为Radon-TVAR的新算法,用于多分量Chirp信号的检测和参数估计。仿真结果表明新算法能有效检测多分量Chirp信号,性能优越于传统方法。
In this paper, we first proposed a modified algorithm for time-varying autoregressive （TVAR） model identification based on 2D-DCT of basis functions vector matrix. Through 2D-DCT, the redundancy of basis functions vector matrix＇ correlation was reduced, and the condition coefficient of coefficient matrix was decreased consequently, which avoided the appearance of ill-conditioned equation and the computation complexity was greatly decreased. Then Multi-component chirp signal was modeled with the modified model, and by combining the Radon transformation and the CLEAN method, a new technique for multi-component chirp signal detection and parameter estimation in terms of Radon-TVAR was presented. Simulation results show that the new algorithm can detect the parameters of multi-component chirp signal more effectively than the traditional methods.
出处
《电子测量与仪器学报》
CSCD
2006年第5期1-5,共5页
Journal of Electronic Measurement and Instrumentation
基金
国家自然科学基金资助项目(编号:60271023)。
