一种数据辅助的前向位定时估计算法

以平方法为代表的非数据辅助(NDA)类前向位定时估计算法在低信噪比和小成性系数场合估计性能严重恶化，而采用数据辅助(DA)类估计是值得考虑的选择。但传统的数据辅助类算法需要大量的搜索以获取位定时的精确估计，运算量大实现困难。本文将三角内插技术应用于位定时估计，提出了一种新的数据辅助前向位定时估计算法，该算法简单、便于实现。仿真结果表明，本文算法估计性能逼近修正卡美罗界(MCRB)，且对成形滚降系数不敏感，适合于低信噪比突发通信。最后，本文针对突发信号给出了前导码捕获与位定时估计一体化的实现结构。 

A Feedforward Data-Aided Timing Estimation Algorithm

The non-data aided feedforward symbol timing estimators such as squiring timing recovering are seriously deteriorated at low signal-to-noise ratio or at small roll-off factors. Then， the data aided are considerable. But the traditional data aided estimators need huge searching operations to get precise estimation， which results in complicated implement. In this paper， a new feedforward data-aided symbol timing estimator which employs trigonometric interpolation technology is proposed. It is very simple and can be easily implemented. Simulations indicate that it not only closely approaches the modified Cramer-Rao bound (MCRB)， but exhibits stability with the roll-off factors. Furthermore， a new structure for bursting signal is also provided here where acquisition of pilot codes and timing recovery is combined implemented.