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

Chintagunta, Srinivasarao; Ponnusamy, Palanisamy

doi:10.2528/pierm19041705

Cited by 5 publications

(3 citation statements)

References 13 publications

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“…As such it has many applications in radar, sonar, wireless communications, etc. [1][2][3][4]. A large number of works have been conducted by extending the classical scalar array processing techniques to the vectorsensor case, such as MUSIC-like [5,6] and ESPRIT-like [7,8] methods dealing with multi-components of vector sensor array with different configurations.…”

Section: Introductionmentioning

confidence: 99%

Augmented Quaternion Music Method for a Uniform/Sparse Cold Array

Jiang¹,

Zhang²,

Chen³

et al. 2021

PIER Letters

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The quaternion multiple signal classification (Q-MUSIC) algorithm reduces the dimension of covariance matrix, which would result in performance degrading of DOA estimation. An augmented quaternion MUSIC algorithm (AQ-MUSIC) based on concentered orthogonal loop and dipole (COLD) array is presented in this paper. The proposed algorithm uses an augmented quaternion formalism to model the completely polarized signals, which allows a concise and novel way to an augmented covariance matrix. The fact reveals that more accurate DOA parameters could be extracted from an augmented covariance matrix. Even compared with the long vector MUSIC (LV-MUSIC) algorithm whose dimension of covariance matrix is the same as AQ-MUSIC, the accuracy of DOA parameter estimation is also improved. Simulation results verify the performance promotion of the proposed approach.

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Section: Introductionmentioning

confidence: 99%

Augmented Quaternion Music Method for a Uniform/Sparse Cold Array

Jiang¹,

Zhang²,

Chen³

et al. 2021

PIER Letters

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“…Accordingly, the transmitting and receiving nodes of the radar are individually configured as an antenna array, rendering the picture of a multiple-input multiple-output (MIMO) model. For instance, when the radar transmitters and receivers are modelled as electromagnetic vector sensors (EVSs), the work in [2] presents a solution for localization of mixed targets. Also, in this context, the work in [3] presents an approach for angle estimation for arbitrary array manifolds.…”

Section: Introductionmentioning

confidence: 99%

On the Role of Time-Frequency Analysis for Joint Dod-Doa Estimation for Bistatic Mimo Radars

Lakshminarasimhan¹,

Soundarapandian²,

Ponnusamy³

2021

PIER C

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RAdio Detection And Ranging (RADAR) is an essential tool used extensively to detect a target's presence within the vicinity characterized by the range of the RADAR. In order to localize the target, Direction of Departure (DOD) and Direction of Arrival (DOA) estimations are utilized. To make it more convenient, a bistatic multiple input multiple output (MIMO) configuration is exploited to deduce the position of a target through the triangulation method easily. Furthermore, due to the maneuvering of targets in space, more robust direction finding solutions can be derived using timefrequency (TF) representations. Thus, this paper aims to leverage the benefits of TF analysis to the estimation of DOD and DOA jointly for a bistatic MIMO radar by using Spatial Time-Frequency Distribution (STFD) matrices. The performance of the considered method is numerically evaluated through root mean square error (RMSE) and is compared against the conventional algorithms that do not use TF tools and as well compared against theĆramer Rao Lower Bound (CRLB). The results show that TF based approach may be a promising candidate in terms of its robustness against channel noise. Also, the performance of the TF based DOD-DOA estimates is studied in terms of their consistency and resolvability of targets which measures the performance in a multi-target environment. Finally, the use-case of TF based estimation to solve the problem in the presence of coherent targets is analysed through simulations and inferred.

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“…As a new type of radar system, multiple input multiple output (MIMO) radar has many potential advantages in enhancing spatial resolution, parameter identification, and improving target detection capability [1,2]. In MIMO radar, angle estimation is an important issue that has drawn significant attention in recent years [3,4].…”

Section: Introductionmentioning

confidence: 99%

Four Dimensional Strictly Noncircular Unitary Esprit Algorithm for L-Shaped Bistatic Mimo Radar

Liu¹,

Fang²,

Chen³

et al. 2020

PIER Letters

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In this paper, a joint two dimensional (2D) direction of departure (DOD) and 2D direction of arrival (DOA) strictly noncircular (NC) unitary estimation of signal parameters via rotational invariance techniques (ESPRIT) method is proposed for an L-shaped bistatic multiple input multiple output (MIMO) radar. In the case that the incident signals are NC signals, we first utilize the received data vector and its conjugate counterparts to construct a new data vector, and then the unitary ESPRIT method is adopted to estimate the 2D-DODs and 2D-DOAs, which can automatically pair the four dimensional (4D) angle parameters. Simulation results are included to verify the effectiveness of the proposed algorithm.

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

Cited by 5 publications

References 13 publications

Augmented Quaternion Music Method for a Uniform/Sparse Cold Array

Augmented Quaternion Music Method for a Uniform/Sparse Cold Array

On the Role of Time-Frequency Analysis for Joint Dod-Doa Estimation for Bistatic Mimo Radars

Four Dimensional Strictly Noncircular Unitary Esprit Algorithm for L-Shaped Bistatic Mimo Radar

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