Beamspace Multiple Signal Classification Research Articles

Antenna Pattern Calibration Method for Phased Array of High-Frequency Surface Wave Radar Based on First-Order Sea Clutter

The problem of accurate source localization has been an area of focus in high-frequency surface wave radar (HFSWR) applications. However, antenna pattern distortion (APD) decreases the direction-of-arrival (DOA) estimation performance of the multiple signal classification (MUSIC) algorithm. Up to now, limited studies have been conducted on the calibration of antenna pattern distortion for phased arrays in HFSWR. In this paper, we first analyze the effect of APD on the performance of the MUSIC algorithm through estimation of accuracy and angular resolution. We demonstrate that using the actual pattern (or say APD) can improve DOA estimation performance. Based on this proposition, we propose a novel iterative calibration method that employs the first-order sea clutter data and can jointly estimate DOA and APD in an iterative way. To obtain available calibration points, we introduce the extraction methods of the first-order sea clutter spectrum and single-DOA spectrum points. Meanwhile, in each iteration, the Beamspace MUSIC algorithm and artificial hummingbird algorithm (AHA) are utilized to estimate the DOA and APD, respectively. Numerical results reveal a good coincidence between the actual pattern and the estimated APD. We also apply this method to process the experimental data of HFSWR. We obtain the APD vector of the real phased array and improve the direction-finding performance of several real ship targets using this vector. Both numerical and experimental results prove the correctness of our proposed calibration method.

High-Performance Channel Estimation for mmWave Wideband Systems With Hybrid Structures

In this paper, a channel estimation problem for millimeter-wave (mmWave) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems with hybrid structures is studied. Firstly, a beamspace multiple signal classification (MUSIC) algorithm for mmWave wideband channels is proposed to simultaneously estimate the angles of arrival (AOAs), angles of departure (AODs) and transmission delays. Since the traditional spectral peak search method has high complexity, a multi-spectral peak search method is skillfully designed to search for multiple spectral peaks on the MUSIC spatial spectrum more quickly and accurately. Then, the proposed channel estimator is extended to more actual systems equipped with uniform planar arrays (UPAs). Finally, the Cramér–Rao bound (CRB) results of these channel parameters are derived for evaluating the performance of the proposed channel parameter estimator. Simulation results demonstrate that the proposed channel estimator has greatly high channel estimation accuracy.

DOA Estimation of Indoor Sound Sources Based on Spherical Harmonic Domain Beam-Space MUSIC

The Multiple Signal Classification (MUSIC) algorithm has become one of the most popular algorithms for estimating the direction-of-arrival (DOA) of multiple sources due to its simplicity and ease of implementation. Spherical microphone arrays can capture more sound field information than planar arrays. The collected multichannel speech signals can be transformed from the space domain to the spherical harmonic domain (SHD) for processing through spherical modal decomposition. The spherical harmonic domain MUSIC (SHD-MUSIC) algorithm reduces the dimensionality of the covariance matrix and achieves better DOA estimation performance than the conventional MUSIC algorithm. However, the SHD-MUSIC algorithm is prone to failure in low signal-to-noise ratio (SNR), high reverberation time (RT), and other multi-source environments. To address these challenges, we propose a novel joint spherical harmonic domain beam-space MUSIC (SHD-BMUSIC) algorithm in this paper. The advantage of decoupling the signal frequency and angle information in the SHD is exploited to improve the anti-reverberation property of the DOA estimation. In the SHD, the broadband beamforming matrix converts the SHD sound pressure to the beam domain output. Beamforming enhances the incoming signal in the desired direction and reduces the SNR threshold as well as the dimension of the signal covariance matrix. In addition, the 3D beam of the spherical array has rotational symmetry and its beam steering is decoupled from the beam shape. Therefore, the broadband beamforming constructed in this paper allows for the arbitrary adjustment of beam steering without the need to redesign the beam shape. Both simulation experiments and practical tests are conducted to verify that the proposed SHD-BMUSIC algorithm has a more robust adjacent source discrimination capability than the SHD-MUSIC algorithm.

Cascade AOA estimation technology based on combined array antenna with computational complexity analysis

Since most studies for estimating an angle-of-arrival (AOA) based on the antenna array have considered the antenna array with a single configuration, they are not proper to simultaneously estimate AOAs of multiple signals with various frequencies. In this paper, we introduce a cascade AOA estimation technique consisting of CAPON and Beamspace Multiple Signal Classification (MUSIC), based on a Combined Array Antenna (CAA) with Uniform Rectangular Frame Array (URFA) and Uniform Circular Array (UCA), for enhancing the above problem. In addition, we provide the computational complexity analysis for showing the low computational complexity of this technique comparing to the conventional technique.

Cascade AOA Estimation Algorithm Based on Flexible Massive Antenna Array.

The Angle-of-Arrival (AOA) has a variety of applications in civilian and military wireless communication fields. Due to the rapid development of the location-based service (LBS) industry, the importance of the AOA estimation technique has increased. Although a large antenna array is necessary to estimate accurate AOA information of many signals, the computational complexity of conventional AOA estimation algorithms, such as Multiple Signal Classification (MUSIC), is dramatically increased. In this paper, we propose a cascade AOA estimation algorithm employing CAPON and Beamspace MUSIC, based on a flexible (on/off) antenna array. First, this approach roughly finds AOA groups, including several signal AOAs using CAPON, by applying some of the antenna elements. Then, it estimates each signal AOA in the estimated AOA groups using Beamspace MUSIC by applying the full size of the antenna array. In addition to extremely low computational complexity, the proposed algorithm also has similar estimation performance to that of MUSIC. In particular, the proposed cascade AOA estimation algorithm is highly efficient when employing a massive antenna array. Representative computer simulation examples are provided to illustrate the AOA estimation performance of the proposed technique.

High-Resolution Angle-of-Arrival and Channel Estimation for mmWave Massive MIMO Systems With Lens Antenna Array

Lens antenna array (LAA), as a promising architecture in millimeter-wave (mmWave) massive MIMO systems, which can considerably reduce the number of required radio-frequency (RF) chains. In this article, we propose a high-resolution channel or angle-of-arrival (AoA) estimation scheme while taking into account the power leakage problem. Specifically, the criterion function is constructed based on DFT beam difference (DBD) to infer the real position of arrived signal. Subsequently, the novel antenna selection and path number estimation algorithms are proposed without prior knowledge of channel. A few groups of antennas are selected to connect to the RF chains, where each group contains only a small number of antennas. Thus, the beamspace multiple signal classification (MUSIC) algorithm can be implemented in low dimensional space to estimate the AoA(s) for each group. Then the channel estimation can be obtained by least square method after the reconstructions of steering vectors using the AoA estimations. Furthermore, the corresponding spatial smoothing algorithm is leveraged to tackle rank deficient problem at the scenario of constant path gains. Simulation results verify the effectiveness of the proposed scheme.

Enhanced beamspace MUSIC for cost‐effective FMCW automotive radar

As one important sensor for automotive applications, frequency modulated continuous wave (FMCW) radars working at millimetre wave frequency, e.g. 24 or 77 GHz, are drawing much attention in recent years. Compared with range and radial velocity measurement, direction of arrival (DOA) estimation is more challenging in FMCW automotive radars due to the space limitation and computational complexity constraint. The feature of the signal processing procedure further results in the problem of single snapshot and relatively low signal-to-noise ratio (SNR) level. In this study, the authors propose a low-complexity beamspace multiple signal classification (MUSIC) scheme to improve the DOA estimation performance, where (i) the prior information is exploited to improve beamformer design, (ii) a modified MUSIC estimator is formulated to alleviate the performance degradation due to low SNR, (iii) a joint sub-matrix averaging and Toeplitz structure recovery processing is utilised to compensate the sample covariance estimation error resulted from single snapshot, especially for closely located targets. Simulations are given to demonstrate the efficiency of the authors' proposed enhanced beamspace DOA estimation for cost-effective FMCW automotive radar.

Direction-of-Arrival Estimation for Circulating Space-Time Coding Arrays: From Beamspace MUSIC to Spatial Smoothing in the Transform Domain.

As a special type of coherent collocated Multiple-Input Multiple-Output (MIMO) radar, a circulating space-time coding array (CSTCA) transmits an identical waveform with a tiny time shift. It provides a simple way to achieve a full angular coverage with a stable gain and a low sidelobe level (SLL) in the range domain. In this paper, we address the problem of direction-of-arrival (DOA) estimation in CSTCA. Firstly, we design a novel two-dimensional space-time matched filter on receiver. It jointly performs equivalent transmit beamforming in the angle domain and waveform matching in the fast time domain. Multi-beams can be formed to acquire controllable transmit freedoms. Then, we propose a beamspace multiple signal classification (MUSIC) algorithm applicable in case of small training samples. Next, since targets at the same range cell show characteristics of coherence, we devise a transformation matrix to restore the rotational invariance property (RIP) of the receive array. Afterwards, we perform spatial smoothing in element domain based on the transformation. In addition, the closed-form expression of Cramer-Rao lower bound (CRLB) for angle estimation is derived. Theoretical performance analysis and numerical simulations are presented to demonstrate the effectiveness of proposed approaches.

Millimeter-Wave Channel Estimation Based on 2-D Beamspace MUSIC Method

Due to the spatial sparsity caused by severe propagation loss, mm-wave channel estimation can be performed by estimating the directions and gains of the paths that have significant power. In this paper, we apply the beamspace 2-D multiple signal classification (MUSIC) method to estimate the path directions (the angles of departure and arrival) and use the least-squares method to estimate the path gains. Different from its element-space counterpart, the beamspace MUSIC method may exhibit spectrum ambiguity caused by the beamformers. In this paper, we therefore analyze the sufficient conditions on the beamformers under which the MUSIC spectrum has no ambiguity which also leads to the maximum number of resolvable path directions. Moreover, based on the uniform linear array with half-wavelength spacing, we show that the discrete Fourier transform beamformers, which are naturally analog and often employed in the mm-wave communication systems with hybrid precoding structure, can avoid the spectrum ambiguity and maximize the number of resolvable path directions. Simulation results demonstrate that the proposed 2-D beamspace MUSIC mm-wave channel estimator significantly outperforms existing estimators that are based on beam training and sparse recovery; and in the meantime, it requires much less training slots than these existing methods.

Biquaternion beamspace with its application to vector-sensor array direction findings and polarization estimations

In this paper, a biquaternion beamspace, constructed by projecting the original data of an electromagnetic vector-sensor array into a subspace of a lower dimension via a quaternion transformation matrix, is first proposed.To estimate the direction and polarization angles of sources, biquaternion beamspace multiple signal classification (BB-MUSIC) estimators are then formulated. The analytical results show that the biquaternion beamspaces offer us some additional degrees of freedom to simultaneously achieve three goals. One is to save the memory spaces for storing the data covariance matrix and reduce the computation efforts of the eigen-decomposition. Another is to decouple the estimations of the sources’ polarization parameters from those of their direction angles. The other is to blindly whiten the coherent noise of the six constituent antennas in each vector-sensor. It is also shown that the existing biquaternion multiple signal classification (BQ-MUSIC) estimator is a specific case of our BB-MUSIC ones.The simulation results verify the correctness and effectiveness of the analytical ones.

Implementation of High-Resolution Angle Estimator for an Unmanned Ground Vehicle

We implemented a real-time radar system for an unmanned ground vehicle designed to run on unpaved or bumpy roads. The system must be able to detect slow targets in a cluttered environment and cover wide angular sections with high resolution at the same time. The system consists of array antennas, preprocessors for digital beam forming, and digital signal processors for the detection process which uses sawtooth waveforms and high-resolution estimation, and is called forward/backward spatial smoothing beamspace multiple signal classification (FBSS BS-MUSIC). We show that the sawtooth waveforms enhance the angular estimation capability of FBSS BSMUSIC in addition to their well-known advantages of removing the ambiguity of targets and detecting slow targets with improved velocity resolution.

Study on Resolution Capability of Beam Space MUSIC Estimation Algorithm

Hydrophone arrays are generally used in modern sonar systems in which beam forming plays an important role. This paper analyzes the beam space MUSIC (multiple signal classification) algorithm for the weakly correlated sources according to changes in the statistical properties of signal and noise, then estimates the azimuth of multi-sources using array element space MUSIC algorithm and beam space MUSIC algorithm accurately, respectively. Finally, problems such as the computation cost of the algorithms, SNR resolution threshold and estimation deviation are discussed based on simulation tests. A conclusion could be drawn that beam space MUSIC algorithm is an effective way to resolve multiple targets in small angle domain.

Two-stage DOA estimation for CDMA multipath signals

This paper mainly estimates the direction-of-arrival (DOA) of the code-division multiple access (CDMA) signal in a multipath environment using a two-stage procedure. In general, in a multipath environment, signal DOA would nominally be a DOA phenomenon, causing the DOA estimation method to be biased. However, if the received signal is first projected onto an appropriate beamspace, then the multipath effect will decrease. Therefore, we have proposed a two-stage method to address this issue. The procedure that we used is as follows: first, we used the received signal and particle swarm optimization (PSO) to estimate the signal DOA. Second, the DOA estimated in stage I was used to set up the beamspace multiple signal classification (BMUSIC) method, after which Taylor expansions were used to expand the stage I DOA and to set up a first-order iteration BMUSIC (IBMUSIC) method, the purpose of which was to reduce the multipath effect and the search complexity. This method was a DOA estimation method that combined PSO/IBMUSIC and aimed to reduce the search complexity and estimation bias for multipath signals. Finally, several simulation examples were used to illustrate the designed procedure and confirm the performance of this method.

Improved beamspace MUSIC for finding directions of BPSK and QPSK coherent arrivals

Coherence is often encountered in sonar, radar or mobile communications. Performance of the beamspace MUSIC (MUltiple Signal Classification) deteriorates as coherent arrivals become closely space. ...

Beam-Space MUSIC DOA System Using Phase Shifter

This paper presents a low cost and portable DOA (Direction Of Arrival) estimation system for surveillance using a modifed beamspace MUSIC (MUltiple Signal Classification) by a quasi-orthogonal multi-beam. This is instead of DFT processing and hardware system consisting of chip-sized phase shifters, a single ADC (Analogue to Digital Converter) and a single TR (TRanceiver) module for an antenna array. In the beamspace MUSIC, generated beampattems have orthogonal properties. This proposed system cannot make such a beampattern due to the variable range limitation of phase shifter, then we use the quasi-orthogonal beam obtained by the calculation of correlation coefficient for beampattern. We demonstrate the proposed system using 4-element microstrip array antenna and chip-sized phase shifters. The DOA experiment in anechoic chamber confirms the proposed system performance.