Temporal coherent adaptive target detection for multi-input multi-output radars in clutter

Sheikhi, A.; Zamani, Ali

doi:10.1049/iet-rsn:20070024

Cited by 33 publications

(24 citation statements)

References 12 publications

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“…Comparing Equations (17) and (12) shows that the MIMO radar problem can be considered as an ICA problem in which A = αA(θ, φ), S =S(f d ) and N = N. So, the estimation of αA (θ, φ) andS (f d ) can be derived using ICA techniques. In this problem, the two ambiguities mentioned above cannot be ignored and should be solved in the MIMO radar problem.…”

Section: Ica Modelmentioning

confidence: 99%

“…The ability to exploit these improvements is limited by the realizable number of receiver elements. Recently, researchers tend to develop a new radar structure known as multiple-input multiple-output (MIMO) radar [3][4][5][6][7][8][9][10][11][12][13][14][15][16]. In the concept of MIMO radars, multiple antennas are used to transmit several waveforms and employed to receive the echoes reflected by the targets.…”

Section: Introductionmentioning

confidence: 99%

“…In the first type, in order to use spatial diversity of target reflection, the distances between antenna elements are very large compared to the signal wavelength [4]. The diversity of Radar Cross Section (RCS) improves the detection performance in this type [12]. Different works are presented in signaling and target detection of widely separated MIMO radars [13,17,18].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Target Detection in Pulse-Train Mimo Radars Applying Ica Algorithms

Hatam¹,

Sheikhi²,

Masnadi-Shirazi³

2012

PIER

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Abstract-In this paper, the problem of target detection in colocated "multi-input multi-output" (MIMO) radars is considered. A pulse-train signaling is assumed to be used in this system. As the doppler effect should be considered for the pulse-train signaling, we are confronted by a compound hypothesis testing problem, so in this paper a Generalized Likelihood Ratio (GLR) detector is derived. The high complexity of this detector makes us derive a new detector based on the theory of Independent Component Analysis (ICA). It is shown that the computational load of the ICA-based detector is much less than the GLR detector. It is also shown that the sensitivity of the ICA-based detector to the doppler effect is very low. According to this approach, an appropriate signal design method is presented, based on the separation performance of the ICA algorithms. It is shown that independent random sequences are proper signals in the sense of detection performance.

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Section: Ica Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Target Detection in Pulse-Train Mimo Radars Applying Ica Algorithms

Hatam¹,

Sheikhi²,

Masnadi-Shirazi³

2012

PIER

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“…MIMO radars are often divided into two categories based on antenna placement. In the first one, the transmit and receive antennas are widely separated, and thus, the targets are observed from different directions dealing with target fluctuation fading [4][5][6][7]. In the second category, however, antennas are collocated so that the different phases from received signals can be extracted by the receivers.…”

Section: Introductionmentioning

confidence: 99%

Two-dimensional SLIM with application to pulse Doppler MIMO radars

Jabbarian-Jahromi

Kahaei

2015

EURASIP J. Adv. Signal Process.

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A two-dimensional (2D) sparse signal model is developed for pulse Doppler MIMO radars. Using this model, we develop the 2D sparse learning via iterative minimization (2D SLIM) algorithm. Simulation results show that the 2D SLIM compared to the 1D SLIM drastically reduces the computational burden while both of them have the same performance. Also, for estimation of range-angle-Doppler parameters, the 2D SLIM outperforms the matched filter (MF), smoothed L0-norm (SL0), iterative adaptive approach (IAA), and spectral projected gradient for l 1 -norm minimization (SPGL1) algorithms.

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“…In general, MIMO radar can be divided into two types, based on the configuration of the antennas, the statistical MIMO radar and colocated MIMO radar. The aim of statistical MIMO radar is to resist the scintillation influence encountered in radar systems [9,10,[14][15][16]23]. The colocated MIMO radar can achieve flexible spatial transmit beampattern design, provide high-resolution spatial spectral estimates, and significantly improve the parameter identifiability [11,17,19,24].…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of Colocated MIMO Radars with Randomly Distributed Arrays in Compound-Gaussian Clutter

Cui

Kong

Yang

2011

Circuits Syst Signal Process

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This paper focuses on the target detection problem for colocated MIMO radar with randomly distributed arrays in the presence of compound-Gaussian clutter with unknown Power Spectral Density (PSD). First, we derive the Generalized Likelihood Ratio Test (GLRT) assuming known covariance structure, and then, three different covariance estimation strategies, i.e., Sampled Covariance Matrix (SCM), Normalized Sampled Covariance Matrix (NSCM), and Fixed Point Estimation (FPE) Matrix, are introduced in place of the exact one to make the derived GLRT fully adaptive. Thorough numerical evaluations of the detection performance are provided and discussed.

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Temporal coherent adaptive target detection for multi-input multi-output radars in clutter

Cited by 33 publications

References 12 publications

Target Detection in Pulse-Train Mimo Radars Applying Ica Algorithms

Target Detection in Pulse-Train Mimo Radars Applying Ica Algorithms

Two-dimensional SLIM with application to pulse Doppler MIMO radars

Performance Analysis of Colocated MIMO Radars with Randomly Distributed Arrays in Compound-Gaussian Clutter

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