Abstract
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 1D slices and adaptive linear filters, an efficient algorithm is proposed to solve the problem and extended for non-stationary stochastic processes. In order to achieve accurate parameter estimation of direct sequence spread spectrum (DSSS) signals, the first 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. For the case of intercepted signals with enough large data samples, the estimator provides good performance in parameter 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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
