A new adaptive estimator for direct sequence spread spectrum （DSSS） signals using fourth-order cumulant based adaptive method is considered. The general higher-order statistics may not be easily applied in signal pr...A new adaptive estimator for direct sequence spread spectrum （DSSS） signals using fourth-order cumulant based adaptive method is considered. The general higher-order statistics may not be easily applied in signal processing with too complex computation. Based on the fourth-order cumulant with 1-D slices and adaptive filters, an efficient algorithm is proposed to solve the problem and is extended for nonstationary stochastic processes. In order to achieve the accurate parameter estimation of direct sequence spread spectrum （DSSS） signals, the fast step uses the modified fourth-order cumulant to reduce the computing complexity. While the second step employs an adaptive recursive system to estimate the power spectrum in the frequency domain. In the case of intercepted signals without large enough data samples, the estimator provides good performance in parameter estimation and white Gaussian noise suppression. Computer simulations are included to corroborate the theoretical development with different signal-to-noise ratio conditions and recursive coefficients.展开更多
To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. ...To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. By simplifying the objective function of maximum likelihood estimation, the algorithm can realize sequence synchronization and sequence estimation via adaptive iteration and sliding window. Since it avoids the correlation matrix computation, the algorithm significantly reduces the storage requirement and the computation complexity. Simulations show that it is a fast convergent algorithm, and can perform well in low signal to noise ratio (SNR).展开更多
针对高动态长时间积累情况下直扩信号能量无法有效积累的问题,提出了一种基于运动补偿的二倍分组块补零(Double Block Zero Padding,DBZP)算法。首先利用Keystone变换对输入信号与本地伪码在频域相乘后的结果进行处理,消除伪码自相关峰...针对高动态长时间积累情况下直扩信号能量无法有效积累的问题,提出了一种基于运动补偿的二倍分组块补零(Double Block Zero Padding,DBZP)算法。首先利用Keystone变换对输入信号与本地伪码在频域相乘后的结果进行处理,消除伪码自相关峰走动;再利用分段解线调技术同时补偿掉多普勒扩展和伪码自相关峰弯曲;最后对信号进行相干积累。仿真结果表明,基于运动补偿的DBZP算法能有效地消除动态的影响,大幅减小积累损耗,进而提升捕获灵敏度。该算法能广泛应用于基于直扩信号的高动态微弱目标捕获。展开更多
文摘A new adaptive estimator for direct sequence spread spectrum （DSSS） signals using fourth-order cumulant based adaptive method is considered. The general higher-order statistics may not be easily applied in signal processing with too complex computation. Based on the fourth-order cumulant with 1-D slices and adaptive filters, an efficient algorithm is proposed to solve the problem and is extended for nonstationary stochastic processes. In order to achieve the accurate parameter estimation of direct sequence spread spectrum （DSSS） signals, the fast step uses the modified fourth-order cumulant to reduce the computing complexity. While the second step employs an adaptive recursive system to estimate the power spectrum in the frequency domain. In the case of intercepted signals without large enough data samples, the estimator provides good performance in parameter estimation and white Gaussian noise suppression. Computer simulations are included to corroborate the theoretical development with different signal-to-noise ratio conditions and recursive coefficients.
基金supported by Joint Foundation of and China Academy of Engineering Physical (10676006)
文摘To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. By simplifying the objective function of maximum likelihood estimation, the algorithm can realize sequence synchronization and sequence estimation via adaptive iteration and sliding window. Since it avoids the correlation matrix computation, the algorithm significantly reduces the storage requirement and the computation complexity. Simulations show that it is a fast convergent algorithm, and can perform well in low signal to noise ratio (SNR).
文摘针对高动态长时间积累情况下直扩信号能量无法有效积累的问题,提出了一种基于运动补偿的二倍分组块补零(Double Block Zero Padding,DBZP)算法。首先利用Keystone变换对输入信号与本地伪码在频域相乘后的结果进行处理,消除伪码自相关峰走动;再利用分段解线调技术同时补偿掉多普勒扩展和伪码自相关峰弯曲;最后对信号进行相干积累。仿真结果表明,基于运动补偿的DBZP算法能有效地消除动态的影响,大幅减小积累损耗,进而提升捕获灵敏度。该算法能广泛应用于基于直扩信号的高动态微弱目标捕获。
