Unified Optimization Framework for Multi-Static Radar Code Design Using Information-Theoretic Criteria

Naghsh, Mohammad Mahdi; Modarres-Hashemi, Mahmoud; Shahbazpanahi, Shahram; Soltanalian, Mojtaba; Stoica, Petre

doi:10.1109/tsp.2013.2278154

Cited by 90 publications

(95 citation statements)

References 49 publications

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“…Signal-to-noise ratio (SNR) and MI based matched illumination waveform design approaches for extended target are developed in [23] [24]. Other existing works can refer to [25] [26].…”

Section: B Brief Survey Of Similar Workmentioning

confidence: 99%

Power Minimization-Based Robust OFDM Radar Waveform Design for Radar and Communication Systems in Coexistence

Shi

Wang

Sellathurai

et al. 2018

IEEE Trans. Signal Process.

253

144

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“…Signal-to-noise ratio (SNR) and MI based matched illumination waveform design approaches for extended target are developed in [23] [24]. Other existing works can refer to [25] [26].…”

Section: B Brief Survey Of Similar Workmentioning

confidence: 99%

Power Minimization-Based Robust OFDM Radar Waveform Design for Radar and Communication Systems in Coexistence

Shi

Wang

Sellathurai

et al. 2018

IEEE Trans. Signal Process.

253

144

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“…To reduce the computational complexity to a reasonable one, many relevant works resort to the majorization-minimization (MaMi) technique [26]- [28], [31]- [34], which is the basic technique for addressing large-scale and/or non-convex optimization problems with complex objectives [31]. For example, [32] have dealt with multistatic radar waveform design, where an information-theoretic criterion has been utilized, while [26], [28] have been concerned with singleand [27] multiple-waveform designs.…”

Section: Introductionmentioning

confidence: 99%

Fast Algorithms for Designing Unimodular Waveform(s) With Good Correlation Properties

Vorobyov

2018

IEEE Trans. Signal Process.

127

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In this paper, we develop new fast and efficient algorithms for designing single/multiple unimodular waveforms/codes with good auto-and cross-correlation or weighted correlation properties, which are highly desired in radar and communication systems. The waveform design is based on the minimization of the integrated sidelobe level (ISL) and weighted ISL (WISL) of waveforms. As the corresponding optimization problems can quickly grow to large scale with increasing the code length and number of waveforms, the main issue turns to be the development of fast large-scale optimization techniques.The difficulty is also that the corresponding optimization problems are non-convex, but the required accuracy is high. Therefore, we formulate the ISL and WISL minimization problems as non-convex quartic optimization problems in frequency domain, and then simplify them into quadratic problems by utilizing the majorization-minimization technique, which is one of the basic techniques for addressing large-scale and/or non-convex optimization problems. While designing our fast algorithms, we find out and use inherent algebraic structures in the objective functions to rewrite them into quartic forms, and in the case of WISL minimization, to derive additionally an alternative quartic form which allows to apply the quartic-quadratic transformation. Our algorithms are applicable to large-scale unimodular waveform design problems as they are proved to have lower or comparable computational burden (analyzed theoretically) and faster convergence speed (confirmed by comprehensive simulations) than the state-of-the-art algorithms.In addition, the waveforms designed by our algorithms demonstrate better correlation properties compared to their counterparts.

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“…Therefore, maximization of the Bhattacharyya distance minimizes the upper bound on P f a and, at the same time, it maximizes the lower bound on P d . 2 The Bhattacharyya distance B for two multivariate Gaussian distributions, CN (0, Σ 1 ) and CN (0, Σ 2 ), can be expressed as [11]:…”

Section: Design Problemmentioning

confidence: 99%

“…However, a solution to this problem can be obtained using the iterative method discussed in [2,16]. More concretely, the problem in (19) can be equivalently written as the following UQP:…”

Section: • Minimizationmentioning

confidence: 99%

“…Waveform design for statistical MIMO radars is mainly concerned with detection performance improvement. In [2], a unified optimization framework has been developed for code design in MIMO radars with orthogonal transmission using information theoretic criteria. Regarding MIMO radars employing arbitrary signals, reference [3] considers space-time code design for This work was supported in part by the European Research Council (ERC) under Grant #228044 and the Swedish Research Council.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Unimodular code design for MIMO radar using Bhattacharyya distance

Naghsh

Modarres-Hashemi

Sheikhi

et al. 2014

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Self Cite

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In this paper, we study the problem of unimodular code design to improve the detection performance of statistical multipleinput multiple-output (MIMO) radar systems. To this end, we consider a system transmitting arbitrary unimodular signals and a discrete-time formulation of the problem. Due to the complicated form of the performance metric of the optimal detector, we resort to the Bhattacharyya distance for code design. We devise a novel method based on the majorization of matrix functions to obtain solutions to the constrained design problem. Simulation results show the effectiveness of the proposed method.

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Unified Optimization Framework for Multi-Static Radar Code Design Using Information-Theoretic Criteria

Cited by 90 publications

References 49 publications

Power Minimization-Based Robust OFDM Radar Waveform Design for Radar and Communication Systems in Coexistence

Power Minimization-Based Robust OFDM Radar Waveform Design for Radar and Communication Systems in Coexistence

Fast Algorithms for Designing Unimodular Waveform(s) With Good Correlation Properties

Unimodular code design for MIMO radar using Bhattacharyya distance

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