DOA estimation of mixed coherent and uncorrelated targets exploiting coprime MIMO radar

Qin, Si; Zhang, Yimin D.; Amin, Moeness G.

doi:10.1016/j.dsp.2016.06.006

Cited by 94 publications

(42 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…And hence, A can be easily obtained form (22). For the PARALIND decomposition above, according to (17), (18), and (19), we repeatedly update the estimation of A , A , S , and Γ until convergence. Define the sum of squared residuals (SSR) of the k-th iteration as [40].…”

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

“…Some other coherent estimation methods including traditional forward spatial smoothing (FSS) or forward backward spatial smoothing (FBSS) [15,16] algorithm have good estimation performance. Exploiting coprime multiple-input multiple-output (MIMO) radar, [17] has proposed the DOA estimation method for mixed coherent and uncorrelated targets and [18] obtained the DOA estimation of coherent sources via fourth-order cumulants.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Compressed Sensing PARALIND Decomposition-Based Coherent Angle Estimation for Uniform Rectangular Array

Zhang

et al. 2019

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

In this paper, the topic of coherent two-dimensional direction of arrival (2D-DOA) estimation is investigated. Our study jointly utilizes the compressed sensing (CS) technique and the parallel profiles with linear dependencies (PARALIND) model and presents a 2D-DOA estimation algorithm for coherent sources with the uniform rectangular array. Compared to the traditional PARALIND decomposition, the proposed algorithm owns lower computational complexity and smaller data storage capacity due to the process of compression. Besides, the proposed algorithm can obtain autopaired azimuth angles and elevation angles and can achieve the same estimation performance as the traditional PARALIND, which outperforms some familiar algorithms presented for coherent sources such as the forward backward spatial smoothing-estimating signal parameters via rotational invariance techniques (FBSS-ESPRIT) and forward backward spatial smoothing-propagator method (FBSS-PM). Extensive simulations are provided to validate the effectiveness of the proposed CS-PARALIND algorithm.

show abstract

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Compressed Sensing PARALIND Decomposition-Based Coherent Angle Estimation for Uniform Rectangular Array

Zhang

et al. 2019

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

show abstract

“…Herein, the data model is similar to that in [9] where clutter is absent. Let K denote the number of reflective signals of K far-field uncorrelated targets which are with unit power and can be denoted as s…”

Section: B Data Modelmentioning

confidence: 99%

2D MIMO Radar with Coprime Arrays

Liu

Ling

2018

2018 IEEE 10th Sensor Array and Multichannel Signal Processing Workshop (SAM)

View full text Add to dashboard Cite

In this contribution, a new class of planar coprime MIMO radar systems based on quadratic integers is proposed where the antenna locations are represented by lattice points generated by prime integers in quadratic number fields. By exploiting the coprimality of certain quadratic integers, the virtual coarrays of proposed structures enjoy a quadratic gain in parameter identifiability according to the Chinese Remainder Theorem (CRT). To avoid holes in the coarray, we present Hole-free CRT arrays with guaranteed full-rank autocorrelation matrices for subspace-based target estimation. The ring of Gaussian integers and the ring of Eisenstein integers are chosen as examples of designing coprime MIMO radar systems. It is shown that the proposed arrays achieve enhanced angular resolutions and improve the side lobe suppression. In the context of target estimation, simulations show the superior performance of the coprime MIMO structures based on CRT.

show abstract

“…However, this ESPRIT-based method fails under the coherent target scenario due to the rank deficiency of received signal covariance matrix. In practice, the received signals are coherent or partially correlated or may be a combination of coherent and partially correlated [13][14][15]. Therefore, in this paper, we formulate a model for mixed targets which are the combination of uncorrelated, partially correlated, and groups of coherent targets, and estimate both spatial and polarization angles.…”

Section: Introductionmentioning

confidence: 99%

Spatial and Polarization Angle Estimation of Mixed-Targets in Mimo Radar

Chintagunta¹,

Ponnusamy²

2019

PIER M

View full text Add to dashboard Cite

This paper proposes an approach for estimating the spatial and polarization angles of mixed-targets in bistatic MIMO radar. Mixed-targets mean the combination of uncorrelated, partially correlated, and groups of coherent targets. The approach resolves rank deficiency of received signal covariance matrix and then exploits the ESPRIT-based method for estimating the angles of directionof-departure (DOD) and direction-of-arrival (DOA). This paper also presents an analytical review and necessary conditions for resolving the rank deficiency under various scenarios of the MIMO radar. Simulation results show the effectiveness of the proposed approach.

show abstract

DOA estimation of mixed coherent and uncorrelated targets exploiting coprime MIMO radar

Cited by 94 publications

References 31 publications

Compressed Sensing PARALIND Decomposition-Based Coherent Angle Estimation for Uniform Rectangular Array

Compressed Sensing PARALIND Decomposition-Based Coherent Angle Estimation for Uniform Rectangular Array

2D MIMO Radar with Coprime Arrays

Spatial and Polarization Angle Estimation of Mixed-Targets in Mimo Radar

Contact Info

Product

Resources

About