低空目标声测无源定向理论与算法研究
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摘要
由于武装直升机等低空目标位于雷达探测的盲区活动,近年来采用声学探测方法受到了重视。低空目标无源定向是低空目标无源声探测系统研究中的一项关键技术。本文根据低空目标无源声定向的研究现状、存在的主要问题,对目前该领域的研究方法进行改进和完善的同时,在低空目标声测无源定向的新理论和新算法方面进行了深入研究。主要研究内容与成果如下:
     1.研究了目标声源和声场特性。分析了低空目标声源的产生机理、目标辐射噪声在大气中的传播特性以及影响其传播的几个主要因素。对实测的直升机辐射噪声数据进行了分析,获得了目标辐射噪声谱特性。
     2.研究了基于时延估计的低空目标声测无源定位理论与算法。针对广泛采用的平面四元十字阵定位方法存在的固有缺点,提出了基于五元十字阵的低空目标声测无源定位算法。推导了五元十字阵目标定位方程,分析了影响五元十字阵目标定位精度的主要因素,研究了时延估计误差、有效声速误差以及阵尺寸测量误差等对目标定位精度的影响,并分别进行了理论分析和数值计算。
     3.结合低空目标无源声定向问题,主要研究了基于频域自适应滤波的时延估计算法和基于双谱的时延估计算法。(1) 分析了频域自适应时延估计算法的性能,推导了算法收敛的条件,揭示了算法达到稳态解时的本质。(2) 提出了基于维纳加权的频域自适应时延估计算法,对算法的性能进行了理论分析。为改善低信噪比时的时延估计性能,提出了一种改进算法性能的方法。采用实测的直升机辐射噪声数据进行了仿真,分别在静态时延和动态时延情况下验证了算法的有效性。(3) 研究了基于双谱的时延估计算法,提出了基于双谱切片的最小二乘时延估计算法。实测直升机辐射噪声数据的仿真表明,对于不相关和相关高斯噪声背景,该方法的性能均优于基于双谱的时延估计算法,并且计算复杂度也小于基于双谱的时延估计算法。
     4.首次深入研究了基于压差式矢量传感器的低空目标声测无源定向理论与算法,为小尺寸基阵和低频条件下实现对低空目标的精确定向提供了一种新的技术途径。(1) 提出了基于二维压差式矢量传感器的低空目标声测无源定向算法。给出了算法的工程实现途径,从理论上分析了声场计算误差、通道幅度和相位不一致性等因素对算法性能的影响。采用实测的直升机辐射噪声数据对算
It is of engineering importance to detect low altitude moving targets such as helicopters, due to the blindness of the traditional radar. The passive acoustical direction finding methods is the one of the key technologies of the detection system for low altitude targets. Based on the current research status and the main problems, this dissertation not only improved the methods now available, but also carried out a deep study on new ones for direction finding of low altitude moving targets. The main contributions are as follows:1. The characteristics of target sound sources and sound field are reviewed, respectively. The mechanism of the produce of target noise, its transmission characteristics in air and several main factors that influence the sound transmission are analyzed. By the analysis of the noise data radiated by a helicopter, the noise characteristics of low altitude targets are presented.2. The theory and algorithm for low altitude target localization based on time delay estimation (TDE) is studied. Considering the problems facing by the localization method for widely used four-element cross array, a five-element cross array scheme is proposed. The localization equation is derived, followed by the location accuracy analysis. The influence of TDE error, effective sound speed error and array size measurement error to target location accuracy is discussed respectively, both in theoretical and numerical sense.3. TDE algorithms based on frequency domain adaptive filtering and higher-order spectrum are investigated, respectively. (1) The performance of the frequency domain adaptive TDE algorithm is analyzed, and its convergence condition is also derived. (2) A Wiener weighting based frequency domain adaptive TDE approach is proposed. In order to improve the performance of the new algorithm in low signal to noise ratio (SNR), a method for weighting the phase data is also given. The effectiveness of the algorithms is evaluated by the simulation experiments on real helicopter noise both in static and dynamic environments. (3) A bispectrum slice based least squares TDE algorithm is proposed. The simulation results show that the method outperforms the bispectrum based TDE method both in uncorrelated Gaussian noise and correlated one, and the computation load for the new one is less than that of bispectrum based TDE method.4. This dissertation studied firstly the passive acoustic direction finding approaches based on pressure difference vector sensor (PDVS), it is a beneficial explore in accurate direction finding with a small size array under condition of low frequency band. (1) A two-dimensional PDVS based direction finding algorithm is proposed, followed by the presentation of the procedures for engineering realization.
    The direction finding accuracy error due to sound field calculation error, channel variances in amplitude and phase characteristics are analyzed, respectively. Numerical simulations and analysis with real helicopter noise are studied. The relationships between the direction finding accuracy and sensor size, time of integration and SNR are presented, respectively. Under the same array size, the performance of proposed method is compared with that of the TDE based one. (2) A new DOA (Direction of Arrival) estimation algorithm based on complex intensity measurements using a three-dimensional PDVS is proposed. The influence of sound field calculation error to the direction finding accuracy is analyzed. The relationships between the direction finding accuracy and sensor size, time of integration and SNR are investigated by the simulations on real helicopter noise data, respectively. The influence of channel variances in amplitude and phase characteristics to the direction finding accuracy are also analyzed. The theoretical analysis show that the performance of proposed method outperforms that of the TDE based one under the same small size.5. The acoustic vector sensor array (VSA) based wideband passive direction finding problem is studied. (1) Based on the established wideband array signal model for VSA, A VSA based wideband coherent signal subspace optimal beamforming algorithm is proposed. The wideband focusing is firstly introduced to VSA array processing, and the relationship between the focusing matrixes of pressure sensor array and VSA is derived. The spatial spectrum for the VSA wideband optimal beamforming is derived herein, this method need no pre-estimation for the direction of sources by wideband focusing with spatial re-sampling technology. The performance of proposed beamformer is assessed by simulation results. The influence of array amplitude and phase error to performance of the wideband optimal beamformer is analyzed. (2) A new two-dimensional DOA estimation algorithm based on VSA is proposed. This method suffers no difficult problems of two-dimensional parameter search and paring usually encountered by some two-dimensional DOA estimation approaches. The simulation results show that the proposed method can decide the number of sources reliably and has a better DOA estimation accuracy, even there are variances in amplitude and phase characteristics among array channels.
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