A Channelization-Based DOA Estimation Method for Wideband Signals.

Rui Guo,Yue Zhang,Zengping Chen,Qianqiang Lin

doi:10.3390/s16071031

Rui Guo, Yue Zhang + Show 2 more

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https://doi.org/10.3390/s16071031

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Abstract

In this paper, we propose a novel direction of arrival (DOA) estimation method for wideband signals with sensor arrays. The proposed method splits the wideband array output into multiple frequency sub-channels and estimates the signal parameters using a digital channelization receiver. Based on the output sub-channels, a channelization-based incoherent signal subspace method (Channelization-ISM) and a channelization-based test of orthogonality of projected subspaces method (Channelization-TOPS) are proposed. Channelization-ISM applies narrowband signal subspace methods on each sub-channel independently. Then the arithmetic mean or geometric mean of the estimated DOAs from each sub-channel gives the final result. Channelization-TOPS measures the orthogonality between the signal and the noise subspaces of the output sub-channels to estimate DOAs. The proposed channelization-based method isolates signals in different bandwidths reasonably and improves the output SNR. It outperforms the conventional ISM and TOPS methods on estimation accuracy and dynamic range, especially in real environments. Besides, the parallel processing architecture makes it easy to implement on hardware. A wideband digital array radar (DAR) using direct wideband radio frequency (RF) digitization is presented. Experiments carried out in a microwave anechoic chamber with the wideband DAR are presented to demonstrate the performance. The results verify the effectiveness of the proposed method.

Highlights

The problem of locating wideband emitters with sensor arrays is of growing interest in many applications such as sonars, radars, advanced satellites and cellular communication systems.we cannot apply narrowband signal subspace methods such as multiple signal classification (MUSIC) [1] and estimation of signal parameters via rotation invariance techniquesESPRIT [2] on wideband sources because the phase difference between sensor outputs is no longer just dependent on the direction of arrival (DOA) alone, and depends on the temporal frequency, which has a wide range.The incoherent signal subspace method (ISM) [3] decomposes wideband signals into many narrowband signals and uses narrowband methods on each decomposed narrowband signals.the results from all the frequency bins are combined to create the final DOA estimation
The main purpose of this paper is to present a hardware-efficient wideband DOA estimation method
Inspired by the digital channelization receiver, we propose a new DOA estimate flow shown in Figure 1, which is composed of intermediate frequency (IF) digitization, digital channelization, channel selection and DOAs estimation

Summary

Introduction

The problem of locating wideband emitters with sensor arrays is of growing interest in many applications such as sonars, radars, advanced satellites and cellular communication systems.we cannot apply narrowband signal subspace methods such as multiple signal classification (MUSIC) [1] and estimation of signal parameters via rotation invariance techniquesESPRIT [2] on wideband sources because the phase difference between sensor outputs is no longer just dependent on the direction of arrival (DOA) alone, and depends on the temporal frequency, which has a wide range.The incoherent signal subspace method (ISM) [3] decomposes wideband signals into many narrowband signals and uses narrowband methods on each decomposed narrowband signals.the results from all the frequency bins are combined to create the final DOA estimation. ESPRIT [2] on wideband sources because the phase difference between sensor outputs is no longer just dependent on the direction of arrival (DOA) alone, and depends on the temporal frequency, which has a wide range. The incoherent signal subspace method (ISM) [3] decomposes wideband signals into many narrowband signals and uses narrowband methods on each decomposed narrowband signals. The results from all the frequency bins are combined to create the final DOA estimation. The ISM method is simple and effective, but it cannot resolve coherent sources and suffers from low signal noise ratio (SNR). The coherent signal-subspace method (CSM) [4] uses a transformation matrix to transform the correlation matrices from many frequency bins into one general correlation matrix at one focusing frequency. Narrowband signal subspace methods can be applied to estimate the DOA

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