Improved design of unimodular waveforms for MIMO radar

Zhuang, Shanna; Zhu, Xiaohua

doi:10.1007/s11045-011-0171-2

Cited by 10 publications

(4 citation statements)

References 12 publications

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“…Multiple-input multiple-output (MIMO) radar which refers to radar systems with multiple antennas to transmit diverse waveforms and multiple antennas to receive targets echoes, has shown enhanced capability compared with its phased array counterpart [1]- [2]. Compared with the traditional radar, it has advantages in anti-stealth, anti-jamming, freedom of freedom, angle resolution and angle measurement precision [3]- [4].…”

Section: Introductionmentioning

confidence: 99%

Joint DOD and DOA Estimation in Bistatic MIMO Radar With Distributed Nested Arrays

2019

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In this paper, we investigate the problem of joint direction of departure (DOD) and the direction of arrival (DOA) estimation in bistatic MIMO radar. A new bistatic MIMO radar with the distributed nested array is proposed. Based on the new array, the DOD and DOA estimation algorithm called automatically paired DR-ESPRIT based on the angle disambiguation algorithm by using the range information of targets is proposed. By designing distributed nested array and using Khatri-Rao product processing, the long baseline and short baseline in the transceiver arrays are virtually extended simultaneously. The non-ambiguous and high-accuracy sine estimations of the DOD and DOA can be accomplished using DR-ESPRIT algorithm and the range information of targets and the geometry of bistatic MIMO radar. The virtual extension of array aperture and high angle estimation accuracy can be achieved for the MIMO radar with automatic pairing and without increasing the number of antennas compared with traditional uniform linear MIMO array. And, the proposed corresponding algorithm gives significant improvement in the DOD and DOA estimation performance. The simulation results validate the theoretical algorithm. INDEX TERMS Bistatic MIMO radar, distributed nested array, DOD and DOA estimation, disambiguation, DR-ESPRIT.

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Section: Introductionmentioning

confidence: 99%

Joint DOD and DOA Estimation in Bistatic MIMO Radar With Distributed Nested Arrays

2019

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“…In addition to autocorrelation, they minimized the crosscorrelation between the generated waveforms. In [35], the waveform design in presence of clutter and white Gaussian noise is assessed. Accordingly, a cyclic algorithm is developed to maximize signal-to-clutter-plus-noise ratio (SCNR) under the constant modulus constraint.…”

Section: Introductionmentioning

confidence: 99%

Designing Sequence With Minimum PSL Using Chebyshev Distance and its Application for Chaotic MIMO Radar Waveform Design

Najafabadi

Ataei

Sabahi

2017

IEEE Trans. Signal Process.

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Controlling peak side-lobe level (PSL) is of great importance in high-resolution applications of multiple input multiple output (MIMO) radars. In this paper, designing sequences with good autocorrelation properties are studied. The PSL of the autocorrelation is regarded as the main merit and is optimized through newly introduced cyclic algorithms, namely; PSL Minimization Quadratic Approach (PMQA), PSL Minimization Algorithm, the smallest Rectangular (PMAR) and PSL Optimization Cyclic Algorithm (POCA). It is revealed that minimizing PSL results in better sequences in terms of autocorrelation side-lobes when compared with traditional integrated side-lobe level (ISL) minimization. In order to improve the performance of these algorithms, fast-randomized Singular Value Decomposition (SVD) is utilized. To achieve waveform design for MIMO radars, this algorithm is applied to the waveform generated from a modified Bernoulli chaotic system. The numerical experiments confirm the superiority of the newly developed algorithms compared to high-performance algorithms in mono-static and MIMO radars.

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“…Large‐scale multiple‐input multiple‐output (MIMO) (see Fig. 1), is considered as one of the most promising technologies for realising next‐generation wireless communications systems (5G) [1–3] and MIMO radar applications [4–6]. One of the main reasons is the attractive spectral efficiency up to several tens of bps/Hz, which could be achieved by large‐scale MIMO systems with tens of antennas or even more [7–11].…”

Section: Introductionmentioning

confidence: 99%

Low‐complexity large‐scale multiple‐input multiple‐output channel estimation using affine combination of sparse least mean square filters

Gui

Liu

et al. 2015

IET Communications

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Improved design of unimodular waveforms for MIMO radar

Cited by 10 publications

References 12 publications

Joint DOD and DOA Estimation in Bistatic MIMO Radar With Distributed Nested Arrays

Joint DOD and DOA Estimation in Bistatic MIMO Radar With Distributed Nested Arrays

Designing Sequence With Minimum PSL Using Chebyshev Distance and its Application for Chaotic MIMO Radar Waveform Design

Low‐complexity large‐scale multiple‐input multiple‐output channel estimation using affine combination of sparse least mean square filters

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