非重构压缩样值跳频信号时频联合估计算法

Time-Frequency Joint Estimation Algorithm for Frequency Hopping Signal with Unreconstructed Compressive Samplings

针对宽带跳频信号的参数进行精确快速的估计,提出一种非重构压缩样值跳频信号时频联合估计算法。首先在非重构原始信号的前提下,通过研究信号的压缩数字特征,发现信号频率发生改变的位置,然后对该位置所在的数据段进行重构得到其频域系数,即可达到估计跳频频率、跳频周期以及跳频跳变时刻的目的。仿真结果表明,当信噪比为10d B,压缩比为1/4时,该算法估计出跳频信号的跳变时刻与Wigner算法达到相同误差条件下,所需处理的采样点个数为Wigner算法的1/4;比完全重构信号后估计算法误差小,所需重构的采样点个数为完全重构的1/4。该算法相对于传统的时频特征算法和基于压缩感知的完全重构估计算法,运算复杂度低,实时性较好。

In order to make a precise and quick estimation of the wide-band frequency-hopping signal, a time-frequercy joint estimation algorithm for frequency hopping signal with unreconstructed compressive samplings is proposed in this paper. First, the compressed numeral characteristics of the signal on the premise of non-reconstructing the original signal was studied to detect the hopping of signal frequency. Then, these data sections were reconstructed to get the frequency domain coeffi- cients. Estimations could be achieved with jump frequency, frequency hopping cycles and the frequency hopping moment based on the frequency domain coefficients. Simulation results show that this algorithm can achieve the same error conditions as Wigner algorithm when SNR is 10dB and compression rate is 1/4. The number of sampling points required for processing is 1/4 as the Wigner algorithm. The estimation error is smaller as the sampling points needed for reconstruction is 1/4 as the complete reconstruction algorithm. So this algorithm has the advantages of lower computation complexity and better real-time performance compared with the traditional time-frequency analysis algorithm and the estimation algorithm through complete reconstruction.