Position Estimation of Automatic-Guided Vehicle Based on MIMO Antenna Array

Chen, Zhimin; He, Xinyi; Cao, Zhenxin; Jin, Yi; Li, Jingchao

doi:10.3390/electronics7090193

Cited by 15 publications

(15 citation statements)

References 32 publications

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“…After a very careful peer-review process, a total of 32 papers were accepted. These works include SAR/ISAR [2][3][4][5][6][7][8][9], polarimetry [10][11][12], MIMO [13,14], direction of arrival (DOA)/direction of departure (DOD) [13][14][15], sparse sensing [5,14,16], ground-penetrating radar (GPR) [17][18][19], through-wall radar [20,21], coherent integration [22,23], clutter suppression [24,25], and meta-materials, among others [26][27][28][29][30][31]. All of these accepted papers are the latest research results and are expected to be further advanced, applied, and diverted.…”

Section: The Present Issuementioning

confidence: 99%

Special Issue on “Advanced Technology Related to Radar Signal, Imaging, and Radar Cross-Section Measurement”

Kobayashi

Moriyama

2020

Electronics

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Section: The Present Issuementioning

confidence: 99%

Special Issue on “Advanced Technology Related to Radar Signal, Imaging, and Radar Cross-Section Measurement”

Kobayashi

Moriyama

2020

Electronics

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“…Many papers have investigated the DOA estimation problem [15][16][17][18]. Traditionally, the discrete Fourier transform In the MIMO radar system, the multiple measurements are obtained from the multiple pulses, where the measurements are obtained from the output of the pulse compression.…”

Section: Introductionmentioning

confidence: 99%

A Super-Resolution DOA Estimation Method for Fast-Moving Targets in MIMO Radar

Liu

Tang

Bai

et al. 2020

Mathematical Problems in Engineering

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Direction of arrival (DOA) estimation is an essential problem in the radar systems. In this paper, the problem of DOA estimation is addressed in the multiple-input and multiple-output (MIMO) radar system for the fast-moving targets. A virtual aperture is provided by orthogonal waveforms in the MIMO radar to improve the DOA estimation performance. Different from the existing methods, we consider the DOA estimation method with only one snapshot for the fast-moving targets and achieve the superresolution estimation from the snapshot. Based on a least absolute shrinkage and selection operator (LASSO), a denoise method is formulated to obtain a sparse approximation to the received signals, where the sparsity is measured by a new type of atomic norm for the MIMO radar system. However, the denoise problem cannot be solved efficiently. en, by deriving the dual norm of the new atomic norm, a semidefinite matrix is constructed from the denoise problem to formulate a semidefinite problem with the dual optimization problem. Finally, the DOA is estimated by peak-searching the spatial spectrum. Simulation results show that the proposed method achieves better performance of the DOA estimation in the MIMO radar system with only one snapshot.(DFT) [19] is used to estimate the DOA, where the received signals are sampled by the antennas in the spatial domain, and then the DOA estimation is equal to a corresponding frequency estimation in the transformed domain. erefore, the frequency (DOA) in the spatial domain is obtained by the DFT methods, but the resolution of DFT method is limited by Rayleigh criterion. e methods that can break through the Rayleigh criterion are called super-resolution methods. Multiple signal classification (MUSIC) method [20][21][22], Root-MUSIC [23], and the estimation of signal parameters via rotational invariant techniques (ESPRIT) method [24][25][26] are three most essential super-resolution methods. e noise subspace and signal subspace are obtained in the MUSIC and ESPRIT methods to estimate the DOA, respectively. A TOD-MUSIC algorithm is proposed in [27] to estimate the DOA in the scenario with low signal-to-noise ratio (SNR) with diversity bistatic MIMO radar.However, the subspaces are obtained from the estimated covariance matrix of the received signals, so the multiple measurements are needed in MUSIC and ESPRIT methods to achieve a reasonable estimation of the covariance matrix.

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“…Although this method is mature and it was widely used in early AGVs, it only works for a fixed path and can be easily affected by the magnetic and electric fields in the environment. With the increasing demand for flexibility and adaptability of the AGV navigation system, positioning methods free of path constraints are constantly being researched and promoted, including inertial, radio, laser, and visual positioning, among others [2]. The inertial navigation system (INS) can provide high-frequency velocity and attitude estimation by using inertial sensors installed on the vehicle.…”

Section: Introductionmentioning

confidence: 99%

“…The laser positioning system uses laser scanning to obtain the location information of reflection signs to provide vehicle position. It has high precision, but it is susceptible to weather and needs a large number of reflective signs [2]. The visual positioning system provides localization services by processing images collected by visual sensors.…”

Section: Introductionmentioning

confidence: 99%

Distributed Multi-Antenna Positioning for Automatic-Guided Vehicle

Zhao

Cui

et al. 2020

Sensors

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Radio-based positioning systems are typically utilized to provide high-precision position information for automatic-guided vehicles (AGVs). However, the presence of obstacles in harsh environments, as well as carried cargoes on the AGV, will degrade the localization performance, since they block the propagation of radio signals. In this paper, a distributed multi-antenna positioning system is proposed, where multiple synchronous antennas are equipped on corners of an AGV to improve the availability and accuracy of positioning. An estimator based on the Levenberg–Marquardt algorithm is introduced to solve the nonlinear pseudo-range equations. To obtain the global optimal solutions, we propose a coarse estimator that utilizes the displacement knowledge of the antennas to provide a rough initial guess. Simulation results show a better availability of our system compared with the single antenna positioning system. Decimeter accuracy can be obtained under a Gaussian measurement noise with a standard deviation of 0.2 m. The results also demonstrate that the proposed algorithm can achieve positioning accuracy close to the theoretical Cramer–Rao lower bound. Furthermore, given prior information of the yaw angle, the same level of accuracy can be obtained by the proposed algorithm without the coarse estimation step.

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Position Estimation of Automatic-Guided Vehicle Based on MIMO Antenna Array

Cited by 15 publications

References 32 publications

Special Issue on “Advanced Technology Related to Radar Signal, Imaging, and Radar Cross-Section Measurement”

Special Issue on “Advanced Technology Related to Radar Signal, Imaging, and Radar Cross-Section Measurement”

A Super-Resolution DOA Estimation Method for Fast-Moving Targets in MIMO Radar

Distributed Multi-Antenna Positioning for Automatic-Guided Vehicle

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