基于压缩感知的线性调频信号频率估计

基于压缩感知理论,测量了在不重构情况下线性调频信号的频率。算法根据信号的稀疏表示建立原子库,利用AIC(Analog-to-Information Conversion)技术完成对信号的压缩采样,在压缩域利用正交匹配追踪的算法进而优化重构稀疏系数,寻找出系数最大值所在的位置,而原子库中该位置原子的频率参量即为线性调频信号的频率参量。该方法在保证频率估计高成功率的前提下,大大减少了采样过程中的冗余和浪费,节省了存储空间,实验仿真验证表明该方法的可行性。

Frequency Estimation of LFM Signal with Compressed Sensing

Based on the compressed sensing theory, the frequency of linear frequency modulation sig- nal is estimated in no reconstruction cases. The atomic library based on the sparse representation of sisals is established and the compression of the signal is completed using the AIC （Analog-to-Infor-mation） conversion. In the compressed domain, sparse coefficient is optimized and reconstructed us- ing the orthogonal matching pursuit algorithm, and then the maximum position of the sparse coefficient is figured out, of which the position of the atomic frequency parameters for chirp signal in the libraryis the frequency of the parameter. Simulation verifies that the redundancies and wastes is cut down in sampling process greatly, storage space is saved under the premise of a high success rate of frequency estimation.