针对空气中基于时延的任意阵列被动定向问题，提出了一种基于最小二乘法的统一模型，并对影响该模型定向精度的几种因素进行了深入的分析。由于可以用于任意结构阵形，该统一模型能够方便地分析阵元位置误差引起的定向误差，能够避免实际系统由于更换阵形而带来的较大的软件变化；并且，当实际阵列与设计模型存在较大误差时，可以方便地改变模型参数使其与实际的阵列匹配。对影响定向误差的各种因素的分析和计算机仿真，为确定和提高被动声定向的精度提供了有价值的参考。

The generalized steering vector is blindly estimated from the CM array, where the steering vectors to all coherent signals are reconstructed directly by using the property of sub-array shift-invariance. When used as the array weighting, the steering vectors will provide recovered signals in corresponding beams. DOAs can be estimated from the angular spectrum subsequently. esults from the computer simulations and the real data analysis.are in good agreement with theoretical analysis. Our method not only can resolve closely spaced coherent signals, but also is shown to be more robust to system errors compared to some other DOA estimation algodthms.

本文内容分理论研究和实验研究两部分。首先，对高分辨目标方位估计算法IMP提出了两种改善其收敛速度的方法。利用这两种改进方法，可将原算法的收敛速度提高一倍。计算机仿真验证了改进方法的有效性。其次，针对该算法进行了水池实验研究，实验分析结果显示，IMP算法能够有效地分辨和估计非等功率的两个相干信号源。

The problem of beamforming and related beamspace high resolution direction-of-arrival (DOA) estimation is studied in this paper. All beamspace processing methods are based on the beam outputs and the beampattern design plays an important role in providing high quality beam output data for further processing. Three typical situations which are frequently encountered in practical sonar system working environment and the most widely studied MUSIC algorithm are considered herein. First, when isotropic noise is the dominant noise at sensors, conventional beamforming techniques provide the optimum performance in the sense that DOA estimate is the ML estimate. Good DOA estimates are obtainable by applying MUSIC to the beam outputs directly. Then, uncorrelated interferes with much higher strength than the wanted signals are assumed to be present in the sidelobe region, and low sidelobe Dolph-Chebyshev and adaptive MVDR beampatterns are designed to guarantee the performance of MUSIC. And finally, the robustness of conventional techniques is combined with the adaptivity of MVDR beamforming to deal with the situation when the interfere in the sidelobe region is strongly correlated with one of the wanted sources. Performance in all three situations is studied with numerical examples.

To overcome the azimuth sampling constraints imposed in synthetic aperture sonar (SAS), many SAS systems employ a single transmitter and multiple-receiver configuration, which can be regarded as a system containing many bistatic transmit-receive pairs. In traditional reconstruction, the multiple receiver system data is often preprocessed into an equivalent single receiver (monostatic) data by using the phase center approximation (PCA) and along track interpolation, and then followed by standard image reconstruction algorithms. But a blurring will occur at the edge of the target area as the length of the receiver array increasing. In this paper, a novel approach is proposed to overcome the blurring problem caused by PCA based on the bistatic model. In this method, an image is firstly reconstructed with the data of each hydrophone independently, and then all the images are coherently added to give the high quality imagery. Simulation results show the feasibility and availability by applying this algorithm.