Parameter Estimation of DSSS Signals with Modified Fourth-Order Cumulants

An asymptotic estimating technique for direct sequence spread spectrum signals using modified fourth-order statistics is considered. The general higher-order cumulants may not be easily applied in signal processing with too complex computation. Based on the fourth-order cumulants with 1D slices and adaptive linear filters, an efficient algorithm is proposed to solve this problem. In order to achieve accurate frequency estimation, the first step uses the modified fourth-order cumulants to reduce the computing complexity. While the second step employs an adaptive recursive system. The fourth-order cumulants is a function of the frequency parameters and is obtained in an iterative manner. For the case of received signals with sufficient large data samples, the estimator provides good performance in frequency estimation and the white Gaussian noise suppression. Computer simulations are included to corroborate the theoretical development with different signal-to-noise ratio conditions and iterative coefficients