Low-Grazing Angle Target Detection and System Configuration of Mimo Radar

Ding, Jincan; Chen, Hao Wen; Wang, Hongqiang; Li, Xiang; Zhuang, Zhihao

doi:10.2528/pierb12120201

Cited by 7 publications

(9 citation statements)

References 27 publications

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“…In rich multipath environments, time reversal technique combined with MIMO radar was used to improve the detection performance [16] while a space-time adaptive processing (STAP) method was developed to mitigate the multipath clutter [17,18]. In [19], the authors demonstrated that the detection performance could be significantly improved through multipath utilization with statistical MIMO radar. The detection performances of two kinds of generalized likelihood ratio test (GLRT) detectors with hybrid MIMO radar in low grazing angel were discussed in [20].…”

Section: Introductionmentioning

confidence: 99%

“…The solutions of other variables (such as r 1 , h r ) are omitted for brevity, see [19,21] for more details. The complex reflection coefficient is calculated by [22] ρ = Γ (ν,h) DS (7) where Γ (ν,h) is vertical polarization or horizontal polarization reflection coefficient for a plane surface; D is the divergence factor due to a curved surface; S is root-mean-squared (RMS) specular scattering coefficient which represents the roughness of surface.…”

Section: Multipath Propagation Modelmentioning

confidence: 99%

“…is shown in Figure 2. R e denotes the effective radius of the imaginary earth and can be represented as [19] R e = R 0 1 + R 0 dN dh 10…”

Section: Multipath Propagation Modelmentioning

confidence: 99%

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Target Detection in Low Grazing Angle With Ofdm Mimo Radar

Xia¹,

Song²,

Lu³

et al. 2016

PIER M

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Abstract-In low grazing angle scenario, target detection performance is seriously deteriorated due to multipath effect. This paper deals with moving target detection in low grazing angle with orthogonal frequency division multiplexing (OFDM) multi-input multi-output (MIMO) radar. We show that the detection performance can be improved through utilizing the multipath effect. Realistic physical and statistical effects such as refraction of the lower atmosphere and the Earth's curvature are incorporated into the multipath propagation model. Then, we derive a generalized likelihood ratio test (GLRT) detector by taking advantage of the frequency diversity of OFDM and MIMO configuration. Based on the fact that the target responses resonate at different frequencies and statistical characteristics of the test, we propose an algorithm which adaptively allocates the transmitted energy to improve the detection performance. The effectiveness of the GLRT detector as well as the adaptive design method is demonstrated via numerical examples.

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Section: Introductionmentioning

confidence: 99%

Section: Multipath Propagation Modelmentioning

confidence: 99%

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Target Detection in Low Grazing Angle With Ofdm Mimo Radar

Xia¹,

Song²,

Lu³

et al. 2016

PIER M

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“…Numerous methods, such as spatial smoothing techniques, proposed removing the coherency [13,14]. It had been demonstrated in [15] that the detection performance could be enhanced via multipath utilization with a statistical multiple-input multiple-output (MIMO) radar. The authors have further investigated a hybrid MIMO radar for detecting low grazing angle targets in multipath propagation scenarios [16].…”

Section: Introductionmentioning

confidence: 99%

An edge computing framework based on OFDM radar for low grazing angle target tracking

Karimi

Mohseni

Khosravi

2020

J Wireless Com Network

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In this paper, a novel adaptive algorithm to detect and track targets with low grazing angle is addressed. For this purpose, an orthogonal frequency division multiplexing (OFDM) radar signal is employed through an edge computing framework over the radar platform. However, detecting the targets in the low grazing angle area is a great challenge due to severe multipath reflection effects. The Earth's curvature geometry model is presented as the multipath propagation model. Based on the fact that the different scattering centers of a target resonate at different frequencies, we use the optimized OFDM waveform and propose a novel target tracking procedure for low grazing angle target tracking scenarios. The obtained results show that using an OFDM radar waveform provides a more uniform detection coverage in the presence of multipath propagation such that this will fill in the nulls. Finally, simulations are used to compare the performance of the proposed OFDM waveform with the conventional equal-power, the generalized likelihood ratio (GLR)-based and single-carrier waveforms.

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“…MIMO radar is categorized into two classes: the statistical MIMO radar and colocated MIMO radar, depending on their antenna placement [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Fluctuating Target Detection in Low-Grazing Angle With Mimo Radar

Ding¹,

Chen²,

Li³

et al. 2013

PIER

Self Cite

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Abstract-This paper focuses on the fluctuating target detection in low-grazing angle using Multiple-input Multiple-output (MIMO) radar systems with widely separated antennas, where the multipath effects are very abundant. The performance of detection can be improved via utilizing the multipath echoes, which is equivalent to improve the signal-to-noise ratio (SNR) by using multipath echoes. First, the reflection coefficient considering the curved earth effect is derived. Then, the general signal model for MIMO radar is introduced for fluctuating target in low-grazing angle. Using the Neyman-Pearson sense, the detectors of fluctuating targets, i.e., Swerling 1-4, with multipath are analyzed. Finally, the simulation results show that the performance can be enhanced markedly when the multipath effects are considered.

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Low-Grazing Angle Target Detection and System Configuration of Mimo Radar

Cited by 7 publications

References 27 publications

Target Detection in Low Grazing Angle With Ofdm Mimo Radar

Target Detection in Low Grazing Angle With Ofdm Mimo Radar

An edge computing framework based on OFDM radar for low grazing angle target tracking

Fluctuating Target Detection in Low-Grazing Angle With Mimo Radar

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