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基于冲激噪声环境下宽带双基地 MIMO 雷达系统中 Sigmoid 变换的参数估计。

Parameter Estimation Based on Sigmoid Transform in Wideband Bistatic MIMO Radar System under Impulsive Noise Environment.

机构信息

College of Information Engineering, Dalian University, Dalian 116622, China.

Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS 39762, USA.

出版信息

Sensors (Basel). 2019 Jan 9;19(2):232. doi: 10.3390/s19020232.

DOI:10.3390/s19020232
PMID:30634522
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6359128/
Abstract

Since second-order statistics-based methods rely heavily on Gaussianity assumption and fractional lower-order statistics-based methods depend on a priori knowledge of non-Gaussian noise, there remains a void in wideband bistatic multiple-input/multiple-output (MIMO) radar systems under impulsive noise. In this paper, a novel method based on Sigmoid transform was used to estimate target parameters, which do not need a priori knowledge of the noise in an impulsive noise environment. Firstly, a novel wideband ambiguity function, termed Sigmoid wideband ambiguity function (Sigmoid-WBAF), is proposed to estimate the Doppler stretch and time delay by searching the peak of the Sigmoid-WBAF. A novel Sigmoid correlation function is proposed. Furthermore, a new MUSIC algorithm based on the Sigmoid correlation function (Sigmoid-MUSIC) is proposed to estimate the direction-of-departure (DOD) and direction-of-arrival (DOA). Then, the boundness of the Sigmoid-WBAF to the symmetric alpha stable () noise, the feasibility analysis of the Sigmoid-WBAF, and complexity analysis of the Sigmoid-WBAF and Sigmoid-MUSIC are presented to evaluate the performance of the proposed method. In addition, the Cramér⁻Rao bound for parameter estimation was derived and computed in closed form, which shows that better performance was achieved. Simulation results and theoretical analyses are presented to verify the effectiveness of the proposed method.

摘要

基于二阶统计量的方法严重依赖于高斯性假设,基于分数阶统计量的方法依赖于非高斯噪声的先验知识,因此在脉冲噪声环境下,宽带双基地多输入/多输出(MIMO)雷达系统仍然存在空白。本文提出了一种基于 Sigmoid 变换的新方法来估计目标参数,该方法不需要脉冲噪声环境中噪声的先验知识。首先,提出了一种新的宽带模糊函数,称为 Sigmoid 宽带模糊函数(Sigmoid-WBAF),通过搜索 Sigmoid-WBAF 的峰值来估计多普勒拉伸和时延。提出了一种新的 Sigmoid 相关函数。此外,提出了一种基于 Sigmoid 相关函数的新 MUSIC 算法(Sigmoid-MUSIC),用于估计到达角(DOA)和到达方向(DOD)。然后,给出了 Sigmoid-WBAF 对对称 α 稳定()噪声的有界性、Sigmoid-WBAF 的可行性分析以及 Sigmoid-WBAF 和 Sigmoid-MUSIC 的复杂度分析,以评估所提出方法的性能。此外,推导出参数估计的克拉美罗界,并以闭式形式计算,结果表明性能得到了提高。给出了仿真结果和理论分析,以验证所提出方法的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bd3/6359128/c0c50f335939/sensors-19-00232-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bd3/6359128/82834fc9be11/sensors-19-00232-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bd3/6359128/ee2e3ee2b228/sensors-19-00232-g003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bd3/6359128/fb1430a22ad6/sensors-19-00232-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bd3/6359128/eebba72b7ec1/sensors-19-00232-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bd3/6359128/c1fb4d49c614/sensors-19-00232-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bd3/6359128/c0c50f335939/sensors-19-00232-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bd3/6359128/82834fc9be11/sensors-19-00232-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bd3/6359128/77edb693cea2/sensors-19-00232-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bd3/6359128/ee2e3ee2b228/sensors-19-00232-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bd3/6359128/0da79f3da4d2/sensors-19-00232-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bd3/6359128/fb1430a22ad6/sensors-19-00232-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bd3/6359128/eebba72b7ec1/sensors-19-00232-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bd3/6359128/c1fb4d49c614/sensors-19-00232-g007.jpg
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