MIMO radar sequence design with constant envelope and low correlation side-lobe levels

Thakur, Ankur; Saini, Davinder S.

doi:10.1016/j.aeue.2021.153769

Cited by 11 publications

(3 citation statements)

References 29 publications

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“…x n x * n+n =α * −n (x) to denote the range sidelobes of MF output in lieu of α n (s) in ( 1) and (2). In modern electronic countermeasures scenarios, range sidelobes units occupied by some powerful interference or extended-scatters which mask the interesting target need to be suppressed [8,10,17]. Namely, local low range sidelobes is more convenient for weak targets detection and anti-masking effect as discussed in (3) and ( 4).…”

Section: The Signal Model and Problem Descriptionmentioning

confidence: 99%

“…In mathematical sense, the MF output is usually the convolution between the received signal and the time-reversed replica of the transmitted signal, which is also regarded as the aperiodic auto-correlation [4][5][6]. Generally, to suppress range sidelobes which might obscure small targets of interest (especially, some dot targets or low RCS target) and further improve the anti-interference ability, the transmitting waveforms with desirable auto-correlation property are imperative by using some prior information [7][8][9][10]. Moreover, in engineering, the constant modulus (CM) of waveform (in most cases, i.e., unimodular property) could maximize the transmitter's efficiency, but also makes the mathematical problem of generating waveform be more non-convex [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

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Radar Phase-Coded Waveform Design with Local Low Range Sidelobes Based on Particle Swarm-Assisted Projection Optimization

Feng

Zhao

et al. 2022

Remote Sensing

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In modern electronic warfare, cognitive radar with knowledge-aided waveforms would show significant flexibility in anti-interference. In this paper, a novel method, named particle swarm-assisted projection optimization (PSAP), is introduced to design phase-coded waveforms with multi-level low range sidelobes, which mainly considers the stability for randomized initialization under the unimodular constraint. Firstly, the mathematical problem corresponding to avoid the range sidelobe masking from multiple non-cooperative targets or interference is formulated by giving different threat levels. Then, based on the alternating direction decomposition idea, the original problem is divided into triple-variable ones where these non-linear approximations can be solved via alternating projections along with FFT. Furthermore, the PSAP method with swarm intelligence, learning factor, and particle-assisted projection could ensure the optimization convergence in a parallel way, which could relax the non-convex constraint and enhance the global exploiting performance. Finally, simulations for several typical scenarios and numerical results are all provided to assess the waveforms generated by PSAP and other prevalent ones.

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Section: The Signal Model and Problem Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Radar Phase-Coded Waveform Design with Local Low Range Sidelobes Based on Particle Swarm-Assisted Projection Optimization

Feng

Zhao

et al. 2022

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…The authors have achieved better results in terms of side-lobe reduction. Thakur and Saini [16], investigated two constraints for reducing the effect of non-linear amplifiers and reducing the interference in transmitting sequence. Their experimental results suppress side-lobe levels and present better performance.…”

Section: Literature Reviewmentioning

confidence: 99%

Prediction of operation vibration state of coal mine mechatronics equipment based on data mining

Jia¹,

Deb²,

Sajja³

2022

J. vibroeng.

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In order to explore the prediction of the operation vibration state of coal mine mechatronics equipment, the author proposes a method based on data mining in response to the problems of large amount of data in the operating state of coal mine electromechanical equipment, low data utilization, and slow speed of single-machine massive data mining, using Map Reduce technology, a dual Map Reduce mining prediction framework is proposed, establish a data mining prediction model for the running state of dual Map Reduce, using MapReduce1 to extract features of monitoring data, use MapReduce2 to predict and analyze feature data. Finally, by building the Hadoop platform, reveal the relationship between Hadoop cluster nodes and parallel processing speed, the efficiency of the data mining prediction framework is verified: Perform an experimental comparative analysis of the single prediction model and the proposed AGB combined prediction model, the prediction accuracy of the AGB combined prediction model is verified.

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Mitigating peak side-lobe levels in pulse compression radar using classical orthogonal polynomials

Thakur

Saini

2022

Wireless Netw

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MIMO radar sequence design with constant envelope and low correlation side-lobe levels

Cited by 11 publications

References 29 publications

Radar Phase-Coded Waveform Design with Local Low Range Sidelobes Based on Particle Swarm-Assisted Projection Optimization

Radar Phase-Coded Waveform Design with Local Low Range Sidelobes Based on Particle Swarm-Assisted Projection Optimization

Prediction of operation vibration state of coal mine mechatronics equipment based on data mining

Mitigating peak side-lobe levels in pulse compression radar using classical orthogonal polynomials

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