声矢量圆阵宽带相干信号的方位估计
发布时间：2018-09-05 07:55
【摘要】：针对水下目标的远程被动探测问题,提出了一种声矢量圆阵的宽带相干目标方位估计方法.首先,基于子带分解原理将宽带划分为若干不重叠窄带,根据圆阵模式空间变换理论,将声矢量圆阵转换成与频率无关的虚拟直线阵,并采用声压P与振速(V_r+V_φ)联合处理方法构建了每个窄带的互协方差矩阵,通过求和平均实现了宽带接收信号的互协方差矩阵估计;其次,引入一种修正的矢量奇异值分解算法,对接收相干信号的互协方差矩阵进行重构处理,用于解决相干声源的空间分辨问题;最后,利用MUSIC算法实现了声矢量圆阵宽带相干目标的方位估计.理论分析及仿真结果表明,修正的矢量奇异值分解算法较修正前具有更强的空间分辨能力;P×(V_r+V_φ)声压振速联合处理方法较同阵型的声压阵及其他声压振速联合处理方法(即(P+V_c)×V_c、P×V_c)具有更好的背景噪声抑制能力;将P×(V_r+V_φ)声压振速联合处理方法与修正的矢量奇异值分解算法有机地结合起来,可提高宽带相干源的方位估计性能.水池实验结果进一步验证了算法的有效性.
[Abstract]:A wideband coherent target azimuth estimation method based on circular array of acoustic vectors is proposed to solve the problem of long range passive detection of underwater targets. Firstly, based on the principle of subband decomposition, the wideband is divided into several nonoverlapping narrow bands. According to the theory of mode space transformation of circular array, the circular array of acoustic vectors is converted into a virtual linear array independent of frequency. The cross covariance matrix of each narrow band is constructed by combining sound pressure P and vibration velocity (VStP), and the estimation of cross covariance matrix of wideband received signals is realized by summation. Secondly, a modified vector singular value decomposition algorithm is introduced. The cross-covariance matrix of received coherent signals is reconstructed to solve the spatial resolution problem of coherent acoustic sources. Finally, the azimuth estimation of wideband coherent targets of acoustic vector circular array is realized by using MUSIC algorithm. Theoretical analysis and simulation results show that, The modified vector singular value decomposition (VSVD) algorithm has stronger spatial resolution than that before the modification. P 脳 (VSV _ 蠁) combined processing method of sound pressure velocity is better than that of the same array and other combined processing methods (i.e. (P _ VVC) 脳 VV _ c 脳 V _ (C) of sound pressure and vibration velocity (i.e. (P _ V _ c) 脳 V _ c 脳 V _ (C). Scene noise suppression ability; The combination of the P 脳 (V _ (V _ 蠁) acoustic pressure and the modified vector singular value decomposition algorithm can improve the azimuth estimation performance of wideband coherent sources. The effectiveness of the algorithm is further verified by the experimental results of the pool.
【作者单位】： 哈尔滨工程大学水声工程学院;哈尔滨工程大学水声技术重点实验室;
【基金】：长江学者和创新团队发展计划(IRT_16R17) 国家自然科学基金(11404076)
【分类号】：TN911.23
[Abstract]:A wideband coherent target azimuth estimation method based on circular array of acoustic vectors is proposed to solve the problem of long range passive detection of underwater targets. Firstly, based on the principle of subband decomposition, the wideband is divided into several nonoverlapping narrow bands. According to the theory of mode space transformation of circular array, the circular array of acoustic vectors is converted into a virtual linear array independent of frequency. The cross covariance matrix of each narrow band is constructed by combining sound pressure P and vibration velocity (VStP), and the estimation of cross covariance matrix of wideband received signals is realized by summation. Secondly, a modified vector singular value decomposition algorithm is introduced. The cross-covariance matrix of received coherent signals is reconstructed to solve the spatial resolution problem of coherent acoustic sources. Finally, the azimuth estimation of wideband coherent targets of acoustic vector circular array is realized by using MUSIC algorithm. Theoretical analysis and simulation results show that, The modified vector singular value decomposition (VSVD) algorithm has stronger spatial resolution than that before the modification. P 脳 (VSV _ 蠁) combined processing method of sound pressure velocity is better than that of the same array and other combined processing methods (i.e. (P _ VVC) 脳 VV _ c 脳 V _ (C) of sound pressure and vibration velocity (i.e. (P _ V _ c) 脳 V _ c 脳 V _ (C). Scene noise suppression ability; The combination of the P 脳 (V _ (V _ 蠁) acoustic pressure and the modified vector singular value decomposition algorithm can improve the azimuth estimation performance of wideband coherent sources. The effectiveness of the algorithm is further verified by the experimental results of the pool.
【作者单位】： 哈尔滨工程大学水声工程学院;哈尔滨工程大学水声技术重点实验室;
【基金】：长江学者和创新团队发展计划(IRT_16R17) 国家自然科学基金(11404076)
【分类号】：TN911.23
【相似文献】
相关期刊论文 前10条
1 吴W，
本文编号：2223659
本文链接：https://www.wllwen.com/kejilunwen/xinxigongchenglunwen/2223659.html
