Volume 38, Number 1, February 2020
|Page(s)||6 - 13|
|Published online||12 May 2020|
MIMO Sonar DOA Estimation with Joint Matched-Filtering Based on Transmission Diversity Smoothing
School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China
There is a class of methods based on transmission diversity smoothing by multiple-input multiple-output(MIMO) sonar called MIMO-TDS which is considered as one of the most effective methods for estimation of direction-of-arrival(DOA) using MIMO sonar systems. MIMO-TDS produced by orthogonal signal transmission for active sonar can be immediately implemented with high resolution algorithms such as MVDR to estimate the direction of received signals. However, the orthogonal transmission mode of MIMO-TDS is doomed to a loss of transmission array gain indirectly leading to the problem that the echoes are not equipped with as high SNR as enough for an accurate target localization, especially in scenarios in which the targets are far away from array. In order to solving the "low SNR" problem, a solution using all transmitted signals simultaneously to design a joint matched-filter intended for received signal is proposed to improve the performance of MIMO-TDS, which is inspired by the match-filtering concept of "MIMO sonar virtual array method" simplified as MIMO-VA. And accordingly, the unit impulse response function of proposed joint matched-filter is the equivalent of linear sum of all orthogonal transmitted signals and the modified MIMO-TDS is named as "joint matched-filtering MIMO sonar transmission diversity smoothing DOA estimation method", which could be simplified as MIMO-TDS-MF. The characteristic of proposed method is analyzed theoretically and compared to MIMO-TDS and MIMO-VA in this paper:Compared with MIMO-TDS, the proposed method not only retains the advantage of transmission diversity smoothing but also improves the SNR by joint match-filtering; What's more, compared with MIMO-VA, MIMO-TDS-MF is equipped with substantially less computation than the former due to an employment of much fewer matched-filters and is in possession of a superior robustness to that of MIMO-VA. Numerical experiments demonstrate the efficiency of proposed MIMO-TDS-MF.
MIMO声呐发射分集平滑（transmission diversity smoothing，TDS）法（简称为MIMO-TDS）是一类重要的多输入多输出（multiple-input multiple-output，MIMO）声呐DOA估计方法。该方法利用发射正交波形来获得发射分集平滑特性，保证了MVDR等自适应高分辨算法的直接应用，但也因此牺牲了发射端的阵增益，在对较远距离的目标进行探测定位时，该方法常会面临回波信噪比不足、性能损失严重等问题。针对该缺点，借鉴了MIMO声呐虚拟阵列（virtual array，VA）法（简称为MIMO-VA）中的匹配滤波思想，提出同时利用所有发射信号对回波进行联合匹配滤波处理的方式提高信噪比，该联合匹配滤波器的单位脉冲响应函数由所有正交发射信号经线性叠加构成。研究表明，所提出的匹配滤波器不仅能够提高接收信噪比，改善MIMO-TDS在低信噪比条件下的性能，还保留了MIMO声呐的发射分集平滑特性。与MIMO-VA相比，所提方法大幅减少了所需匹配滤波通道数量，具有较低的运算量；且存在发射阵列流形误差、发射信号同步误差时，具有更优的稳健性。利用计算机仿真对所提方法的有效性进行了验证。
Key words: MIMO sonar / DOA estimation / match-filtering / transmission diversity smoothing / numerical experiment
关键字 : MIMO声呐 / 目标方位估计 / 匹配滤波 / 发射分集平滑
© 2020 Journal of Northwestern Polytechnical University. All rights reserved.
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