用于飞机系统辨识的多正弦峰因子最小化算法比较
Comparison of Multisine Peak Factor Minimization Algorithms for Aircraft System Identification
浏览论文内容
中文总结 AI 辅助
本文比较了两种多正弦峰因子最小化算法与单纯形算法，发现削峰和无穷范数算法峰因子更低，且削峰算法速度更快，可重复运行以进一步降低峰因子。
中文摘要 AI 辅助
本文提出并评估了两种相位优化的多正弦峰因子最小化算法。第一种算法通过迭代削去所生成多正弦信号的峰值来最小化峰因子。第二种算法通过最小化多正弦信号无穷范数的近似值来间接优化峰因子。算法性能作为不同信号属性的函数进行评估，这些属性包括谐波数量、谐波间隔以及雪谐波（为进一步降低峰因子而额外包含的谐波）的数量。将这两种算法与使用单纯形算法直接最小化峰因子的结果进行比较，后者一直是设计用于系统辨识飞行试验的相位优化多正弦信号时的常用方法。示例结果表明，削峰算法和无穷范数算法产生的多正弦信号具有与单纯形算法相当的峰因子，且峰因子更低。然而，削峰算法的运行速度比其他两种算法快一个数量级，这也使得重复运行该算法多次以获得更低峰因子变得切实可行。
英文摘要
Two phase-optimized multisine peak factor minimization algorithms are presented and evaluated. The first algorithm minimizes peak factor by iteratively clipping the peaks of generated multisine signals. The second algorithm optimizes peak factor indirectly through minimization of an approximation of the infinity norm of the multisine. Algorithm performance was evaluated as a function of different signal properties, including the number of harmonics, harmonic spacing, and number of snow harmonics (extra harmonics included for further reduction of the peak factor). The two algorithms are compared against results obtained by minimizing peak factor directly using a simplex algorithm, which has been a common approach when designing phase-optimized multisines for system identification flight tests. Sample results show that the clipping and infinity norm algorithms produced multisine signals with comparable peak factors that were lower than that of the simplex algorithm. However, the clipping algorithm runs an order of magnitude faster than the other two algorithms, which also makes it practical to repeat the algorithm multiple times to achieve even lower peak factors.
发表机构
- Langley Research Center（兰利研究中心）
机构由 AI 辅助整理，请以论文原文为准。
