Performance of sequential estimation for direct sequence spread spectrum code acquisition

Abstract

The Sequential Estimation (SE) technique introduced by Ward was designed for the acquisition of pseudo-noise (PN) signals. It proves to be an effective model in medium SNRs as long as inverted PN sequences are not encountered. Recognizing that negative data bits invert PN sequences in spread spectrum transmissions, Chiu and Lee developed an Improved Sequential Estimator (ISE) that processes both types of sequences. The ISE design, however, erroneously despreads the incoming signal by inverting it during negative bit acquisitions. In some applications, this could be a problem, hence a Dual Correlating Sequential Estimator (DCSE) is proposed in this paper. The DCSE detects modulation errors by gathering correlation measurements from resident SE and ISE subsystems and corrects for them with an inverting mechanism. Key performance parameters such as mean timing and the variance of acquisition for the sequential estimator designs are derived via the generalized signal flow graph method and verified through simulation. In an additive White Gaussian noise (AWGN) environment, the DCSE design is shown to outperform the SE for every tested signal-to-noise ratio (SNR).