摘要
研究了一种新型的空速测量方法。通过引入大气声学中的有效声速概念,建立了稳定气流作用下声矢量传感器阵列的近场输出模型,模型的阵列流形矢量中包含了待估计的空速信息。在此基础上提出了一种基于多重信号分类(multiple signal classification,MUSIC)的空速估计(airspeed estimation,ASE)算法,该算法可用于对空速的高精度估计。为了降低计算复杂度,进一步提出了一种快速的空速估计(fast airspeed estimation,FASE)算法,该算法虽然在ASE的精度上不如MUSIC-ASE算法,但无需谱搜索,具有更强的实时性。最后,对算法的估计性能进行分析,推导了ASE的克拉美-罗界表达式。仿真实验验证了算法的有效性。
A novel airspeed measuring method is proposed. According to the concept of effective sound velocity in the field of atmospheric acoustics, the near-field output model of acoustic vector sensor array is constructed in a stable air flow. Then a multiple signal classification algorithm for airspeed estimation （MUSIC-ASE） is presented, which can be used to estimate the airspeed with a high degree of accuracy. To reduce the computational com- plexity, a fast airspeed estimation （FASE） algorithm is addressed. Though the estimation accuracy is not so high as the MUSIC-ASE algorithm, the FASE method enable to avoid spectral peak search, and must be more stronger than the MUSIC-ASE algorithm in real-time. Finally, the performance of the proposed algorithms is analyzed, and a compact expression for the Cramer-Rao bound on the estimation error of the airspeed is derived. Computer simulations are implemented to verify the efficacy of the proposed algorithms.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2015年第5期1060-1065,共6页
Systems Engineering and Electronics
基金
国家自然科学基金(61172126
61203355)
吉林省自然科学基金(20140101073JC)资助课题
关键词
声矢量传感器阵列
多重信号分类
克拉美-罗界
空速估计
阵列信号处理
嵌入式大气数据传感
acoustic vector sensor array
multiple signal classification （MUSIC）
Cram6r-Rao bound（CRB）
airspeed estimation （ASE）
array signal processing
flush air data sensing
