Model-based adaptive detection and DOA estimation using separated sub-arrays

C. Engdahl, P. Sunnergren
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引用次数: 8

Abstract

The potential performance of adaptive detection and direction-of-arrival (DOA) estimation using a certain class of sparse linear arrays, characterized by two widely separated sub-arrays, in combination with model-based techniques, is investigated. With this array structure, a large baseline is obtained with a limited amount of hardware. It is found that the very narrow main-lobe obtained by separating the sub-arrays can be utilized to obtain accurate DOA estimates, high angular resolution, and good detection performance even in close vicinity of a localized interference source. However, the presence of grating lobes deteriorates the performance at low SNR and also when the angular separation between two targets, or between a target and an interfering source, corresponds to an integer times the distance between the grating lobes.
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基于模型的分离子阵列自适应检测和DOA估计
结合基于模型的技术,研究了一类稀疏线性阵列的自适应检测和到达方向估计的潜在性能。使用这种阵列结构,可以在有限的硬件数量下获得较大的基线。通过分离子阵列得到的极窄的主瓣可以获得准确的DOA估计,高角分辨率,即使在局域干扰源附近也能获得良好的检测性能。然而,在低信噪比条件下,当两个目标之间的角距或目标与干扰源之间的角距对应于光栅瓣间距的整数倍时,光栅瓣的存在会降低性能。
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