To detect terrestrial application-specific messages (ASM-TER) signals from a satellite, a novel detection method based on the fast computation of the cross ambiguity function is proposed in this paper. The classic cross ambiguity function’s computational burden is heavy, and we transform the classic cross ambiguity function to a frequency domain version to reduce the computational complexity according to Parseval’s theorem. The computationally efficient sliding discrete Fourier transform (SDFT) is utilized to calculate the frequency spectrum of the windowed received signal, from which the Doppler frequency could be estimated coarsely. Those subbands around the Doppler frequency are selected to calculate the ambiguity function for reducing the computational complexity. Furthermore, two local sequences with half length of the training sequence are utilized to acquire a better Doppler frequency tolerance; thus, the frequency search step is increased and the computational complexity could be further reduced. Once an ASM-TER signal is detected by the proposed algorithm, a fine Doppler frequency estimation could be obtained easily from the correlation peaks of the two local sequences. Simulation results show that the proposed algorithm shares almost the same performance with the classic cross ambiguity function-based method, and the computational complexity is greatly reduced. Simulation results also show that the proposed algorithm is more resistant to cochannel interference (CCI) than the differential correlation (DC) algorithm, and the performance of fine Doppler frequency estimation is close to that of the Cramér–Rao lower bound (CRLB).

中文翻译：

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卫星改进的ASM-TER训练序列检测和精细多普勒频率估计方法

为了检测来自卫星的地面专用消息（ASM-TER）信号，提出了一种基于交叉歧义函数快速计算的新型检测方法。经典的交叉歧义函数的计算负担很重，我们根据Parseval定理将经典的交叉歧义函数转换为频域版本，以降低计算复杂度。计算有效的滑动离散傅立叶变换（SDFT）用于计算加窗接收信号的频谱，从中可以粗略估计多普勒频率。选择多普勒频率附近的那些子带来计算模糊度函数，以降低计算复杂度。此外，利用训练序列长度的一半的两个局部序列来获得更好的多普勒频率容限；因此，增加了频率搜索步骤，并且可以进一步降低计算复杂度。一旦所提出的算法检测到ASM-TER信号，就可以很容易地从两个局部序列的相关峰中获得精确的多普勒频率估计。仿真结果表明，该算法与经典的基于交叉歧义函数的算法具有几乎相同的性能，并且大大降低了计算复杂度。仿真结果还表明，与差分相关（DC）算法相比，该算法对同信道干扰（CCI）的抵抗力更高，