On the Design of a Compact Neural Network-Based DOA Estimation System

被引：25

作者：

Fonseca, Nelson Jorge G. ^{[1
]}

Coudyser, Michael ^{[2
]}

Laurin, Jean-Jacques ^{[2
]}

Brault, Jean-Jules ^{[2
]}

机构：

[1] Poly Grames Res Ctr, Montreal, PQ H3C 3A7, Canada

[2] Ecole Polytech, Dept Elect Engn, Montreal, PQ H3C 3A7, Canada

来源：

IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION | 2010年 / 58卷 / 02期

关键词：

Array feeding network; direction finding antenna; monopulse radar; neural network; ANTENNA; ARRAYS;

D O I：

10.1109/TAP.2009.2037766

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

A system to measure the direction of arrival (DOA) of a signal within a 45-degree conical sector is demonstrated. The system is compact and uses only four circularly polarized patch elements. A printed beamforming network is used to create a set of partially overlapping beams allowing DOA estimation without ambiguity. Neural networks are used to first classify the antenna signals and then estimate the DOA. The proposed system was validated experimentally in C band and, in spite of the highly disturbed beams caused by the finite size of the antenna platform, it was shown that DOA estimation errors in the order of one degree were achievable under signal-to-noise ratios of 10 dB.

引用

页码：357 / 366

页数：10

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