The fast estimation of synchronization parameters plays an extremely important role in the demodulation of burst signals. In order to solve the problem of high computational complexity in the implementation of traditional algorithms, a synchronization parameter (frequency offset, phase offset, and timing error) estimation algorithm based on Offset Quadrature Phase Shift Keying (OQPSK) burst signal detection is proposed in this article. We first use the Data-Aided (DA) method to detect where the burst signal begins by taking the segment correlation between the receiving signals and the known local Unique Word (UW). In the sequel, the above results are adopted directly to estimate the synchronization parameters, which is obviously different from the conventional algorithms. In this way, the complexity of the proposed algorithm is greatly reduced, and it is more convenient for hardware implementation. The simulation results show that the proposed algorithm has high accuracy and can track the Modified Cramer–Rao Bound (MCRB) closely.

In recent years, distributed unique word (DUW) has been widely used in satellite single carrier TDMA signals, such as very small aperture terminal (VSAT) satellite systems. Different from the centralized structure of traditional unique word, DUW is uniformly dispersed in a burst signal, where the traditional unique word detection methods are not applicable anymore. For this, we propose a robust burst detection algorithm based on DUW. Firstly, we allocated the sliding detection windows with the same structures as DUW in order to effectively detect it. Secondly, we adopt the method of time delay conjugate multiplication to eliminate the influence of frequency offset on detection performance. Due to the uniform dispersion of DUW, it naturally has two different kinds of time delays, namely the delay within the group and the delay between the two groups. So, we divide the traditional dual correlation formula into two parts to calculate them separately and obtain a dual correlation detection algorithm, which is suitable for DUW. Simulation and experimental results demonstrate that when the distribution structure of DUW changes, detection probability of the proposed algorithm fluctuates little, and its variance is 1.56×10−5, which is 99.83% lower than the existing DUW detection algorithms. In addition, its signal to noise ratio (SNR) threshold is about 1 dB lower than the existing algorithms under the same circumstance of the missed detection probability.