Morris Zakayo Ndiku, Wong Kainam Thomas, Wu Yue Ivan
Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hong Kong, China.
School of General Engineering, Beihang University, Beijing, China.
J Acoust Soc Am. 2020 May;147(5):3209. doi: 10.1121/10.0001138.
The linear array's one-dimensional spatial geometry is simple but suffices for univariate direction finding, i.e., is adequate for the estimation of an incident source's direction-of-arrival relative to the linear array axis. However, this nominal one-dimensional ideality could be often physically compromised in the real world, as the constituent sensors may dislocate three-dimensionally from their nominal positions. For example, a towed array is subject to ocean-surface waves and to oceanic currents [Tichavsky and Wong (2004). IEEE Trans. Sign. Process. 52(1), 36-47]. This paper analyzes how a nominally linear array's one-dimensional direction-finding accuracy would be degraded by the three-dimensional random dislocation of the constituent sensors. This analysis derives the hybrid Cramér-Rao bound (HCRB) of the arrival-angle estimate in a closed form expressed in terms of the sensors' dislocation statistics. Surprisingly, the sensors' dislocation could improve and not necessarily degrade the HCRB, depending on the dislocation variances but also on the incident source's arrival angle and the signal-to-noise power ratio.
线性阵列的一维空间几何结构简单,但足以用于单变量测向,即足以估计入射源相对于线性阵列轴的到达方向。然而,在现实世界中,这种名义上的一维理想情况常常会在物理上受到影响,因为组成传感器可能会从其标称位置发生三维位移。例如,拖曳阵列会受到海面波浪和洋流的影响[蒂查夫斯基和黄(2004年)。《IEEE信号处理汇刊》52(1),36 - 47]。本文分析了组成传感器的三维随机位移如何降低名义线性阵列的一维测向精度。该分析以传感器位移统计量表示的封闭形式推导了到达角估计的混合克拉美 - 罗界(HCRB)。令人惊讶的是,传感器的位移可能会改善而不一定会降低HCRB,这取决于位移方差,还取决于入射源的到达角和信噪功率比。