A new MIMO clutter model for cognitive radar

Guerci, J.R.; Bergin, J.S.; Guerci, R. J.; Khanin, M.; Rangaswamy, M.

doi:10.1109/radar.2016.7485157

Cited by 35 publications

(23 citation statements)

References 8 publications

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“…In an attempt to overcome the trade-off between angular resolution and aperture size, the large number of proposed approaches can be categorized majorly into: Synthetic Aperture Radar (SAR) and Multiple-Input-Multiple-Output (MIMO) radar. While SAR approaches exploit the physical motion of the radar platform to span up a synthetic antenna array [2], MIMO approaches exploit the diversity offered by different antenna elements [3], [4]. Since SAR approaches work well only when the radar platform trajectory is precisely measured using another sensor [2], we focus on MIMO approaches, where imaging and classification can be performed with a standalone radar system.…”

mentioning

confidence: 99%

Generalized Multiplexed Waveform Design Framework for Cost-Optimized MIMO Radar

Hammes

Shankar

Ottersten

2021

IEEE Trans. Signal Process.

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Cost-optimization through the minimization of hardware and processing costs with minimal loss in performance is an interesting design paradigm in evolving and emerging Multiple-Input-Multiple-Output (MIMO) radar systems. This optimization is a challenging task due to the increasing Radio Frequency (RF) hardware complexity as well as the signal design algorithm complexity in applications requiring high angular resolution. Towards addressing these, the paper proposes a low-complexity signal design framework, which incorporates a generalized time multiplex scheme for reducing the RF hardware complexity with a subsequent discrete phase modulation. The scheme further aims at achieving simultaneous transmit beamforming and maximum virtual MIMO aperture to enable better target detection and discrimination performance. Furthermore, the paper proposes a low-complexity signal design scheme for beampattern matching in the aforementioned setting. The conducted performance evaluation indicates that the listed design objectives are met.

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mentioning

confidence: 99%

Generalized Multiplexed Waveform Design Framework for Cost-Optimized MIMO Radar

Hammes

Shankar

Ottersten

2021

IEEE Trans. Signal Process.

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“…Though other clutter sources exist, like large discrete objects, vegetation, and targets not currently being surveilled, the specific stochastic model we apply here only concerns ground clutter. However, we note that a later formulation in this paper may be amenable to considering those other sources in a manner that recalls efforts in the literature on channel estimation (see, for example, [16]). For now, let us assume we have a number of clutter patches (say, Q) each comprising P distinct scatterers.…”

Section: Stap Modelmentioning

confidence: 99%

“…The rest of the paper continues as follows: First, we will outline the general signal model and relate it to the work on transfer functions by [16]. Next, we will define the joint design problem and demonstrate, after some transformation, that the problem is non-convex unless all clutter patches are known to be nulled a priori.…”

mentioning

confidence: 99%

Relaxed Biquadratic Optimization for Joint Filter-Signal Design in Signal-Dependent STAP

O’Rourke

Setlur

Rangaswamy

et al. 2018

IEEE Trans. Signal Process.

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We investigate an alterative solution method to the joint signal-beamformer optimization problem considered by Setlur and Rangaswamy [1]. First, we directly demonstrate that the problem, which minimizes the recieved noise, interference, and clutter power under a minimum variance distortionless response (MVDR) constraint, is generally non-convex and provide concrete insight into the nature of the nonconvexity. Second, we employ the theory of biquadratic optimization and semidefinite relaxations to produce a relaxed version of the problem, which we show to be convex. The optimality conditions of this relaxed problem are examined and a variety of potential solutions are found, both analytically and numerically.

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“…When combined with random fluctuations of spectrum width, these characteristics give the spectra a temporal and spatial variability. In [3], unlike traditional signal-dependent stochastic models, a new "stochastic transfer function" approach is presented that results from a fundamental physics scattering model. In [4], the authors propose a new method of modeling and simulation of temporal-spatial-correlated (TPC) clutter, based on the weighted norm in discrete complex linear space and a simple matrix transformation.…”

Section: Introductionmentioning

confidence: 99%

Generation of Rayleigh Distribution Clutter in CR

Wang¹,

Song²,

Xin³

2017

dtetr

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Abstract. Research on clutter modeling and generation is very important in echo analysis, especially for CR (cognitive radar) working in complex environment. In this paper, we propose a novel generation method for Rayleigh distribution clutter in CR. This method adopts white Gaussian noise sequence and Bessel filter, and Rayleigh distribution clutter can be generated through nonlinear transformation. Simulation results demonstrate the validity of the method, and the estimated value and theoretical value are consistent with each other in both clutter amplitude and spectrum. Finally, the whole paper is summarized.

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A new MIMO clutter model for cognitive radar

Cited by 35 publications

References 8 publications

Generalized Multiplexed Waveform Design Framework for Cost-Optimized MIMO Radar

Generalized Multiplexed Waveform Design Framework for Cost-Optimized MIMO Radar

Relaxed Biquadratic Optimization for Joint Filter-Signal Design in Signal-Dependent STAP

Generation of Rayleigh Distribution Clutter in CR

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