Sinusoidal frequency-modulated (SFM) signal is widely applied in radar, and wireless communication. Therefore, there is significant importance in studying the estimation of SFM signal parameters. However, traditional estimation algorithms have high computational complexity while the corresponding estimation performance degrades when either modulation index or modulation frequency of SFM signals increases. To address these problems of computational complexity as well as the performance degradation, a two-branch two-stage estimation algorithm is proposed in this paper. In the first stage, received signals are passed through two different branches: one for the modulation index not greater than $\pi /2$, and the other for that larger than $\pi /2$. This two-branch strategy is derived from the spectrum properties of SFM signals with respect to modulation index, where the first branch utilizes the Jacobi-Anger expansion, and the second one employs an iterative estimation algorithm. In the second stage, precisions of the parameter estimates obtained from the two branches are compared, and the estimates with higher precision correspond to the final estimates of SFM signal parameters. Both theoretical analysis, and numerical results show that the proposed algorithm outperforms the current state-of-the-art algorithms, while yielding significantly lower computational complexities.

中文翻译：

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两支路两级正弦调频信号参数估计

正弦调频 (SFM) 信号广泛应用于雷达和无线通信。因此，研究SFM信号参数的估计具有重要意义。然而，传统的估计算法具有较高的计算复杂度，而当SFM信号的调制指数或调制频率增加时，相应的估计性能会下降。针对这些计算复杂度和性能下降的问题，本文提出了一种两分支两阶段估计算法。在第一阶段，接收信号通过两个不同的分支：一个用于调制指数不大于 $\pi /2$，另一个用于大于 $\pi /2$ 的调制指数。这种双分支策略源自 SFM 信号相对于调制指数的频谱特性，其中第一个分支利用 Jacobi-Anger 展开，而第二个分支利用迭代估计算法。在第二阶段，比较从两个分支得到的参数估计的精度，精度较高的估计对应于SFM信号参数的最终估计。理论分析和数值结果都表明，所提出的算法优于当前最先进的算法，同时显着降低了计算复杂度。比较从两个分支得到的参数估计的精度，精度较高的估计对应于SFM信号参数的最终估计。理论分析和数值结果都表明，所提出的算法优于当前最先进的算法，同时显着降低了计算复杂度。比较从两个分支得到的参数估计的精度，精度较高的估计对应于SFM信号参数的最终估计。理论分析和数值结果都表明，所提出的算法优于当前最先进的算法，同时显着降低了计算复杂度。