A GEF-based algorithm for blind estimation of PN sequence in lower SNR DSSS signals

In this paper, we propose a generalized energy function (GEF) algorithm to search for the optimum weights to estimate the PN spreading sequence in a non-cooperative context by introducing a weighting matrix. The GEF algorithm can work in real-time and be easily implemented in both synchronization and asynchronization signal modes. Computer simulations show that this algorithm can estimate PN spreading sequence quickly and accurately at lower signal-to noise ratio (SNR), largely reducing the computational complexity and storage requirement versus the eigenvalue decomposition (EVD) algorithm. Furthermore, its properties of convergence, correlation and computational storage are better than the projection approximation subspace tracking (PAST) and modified Hebbian rule (MHR) algorithms.