New Algorithms for Designing Unimodular Sequences With Good Correlation Properties

Stoica, Petre; He, Hao; Li, Jian

doi:10.1109/tsp.2009.2012562

Cited by 401 publications

(350 citation statements)

References 23 publications

(54 reference statements)

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“…In order to obtain waveforms with desired characteristics, existing approaches usually resort to manipulations with correlation properties, such as the auto-and cross-correlations between different time lags of waveforms, which serve as the determinant factors for evaluating the quality of designed waveforms [7], [8]. Perfect auto-and cross-correlation properties indicate that the emitted waveforms are mutually uncorrelated to any time-delayed replica of them, meaning that the target located at the range bin of interest can be easily extracted after matched filtering, and the sidelobes from other range bins are unable to attenuate it.…”

Section: Introductionmentioning

confidence: 99%

“…There is a number of existing waveform design methods based on consideration of the correlation properties [2], [5], [7], [8], [26]- [28]. The integrated sidelobe level (ISL), which serves as an evaluation metric for correlation levels of waveforms, or equivalently, the accumulated sidelobes at all time lags, is typically used.…”

Section: Introductionmentioning

confidence: 99%

“…Corresponding waveform designs use the fact that the matched filter can be implemented in terms of the correlation between the waveform and its delayed replica. For example, the method of [7] has proposed to design unimodular waveform in frequency domain using a cyclic procedure based on iterative calculations. A surrogate objective which is minimized by a cyclic algorithm has been introduced, and the methods associated with the ISL and weighted ISL (WISL) minimization therein have been named as CAN and WeCAN, respectively.…”

Section: Introductionmentioning

confidence: 99%

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

Vorobyov

2018

IEEE Trans. Signal Process.

129

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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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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Vorobyov

2018

IEEE Trans. Signal Process.

129

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“…We denote the specified time-lags of interest by a set . The second metric is the weighted sum of the sidelobe levels (WSSL) of the AC function [27]. We denote the weighting coefficients by an -by-1 vector with .…”

Section: B Problem Formulationmentioning

confidence: 99%

“…The design objective can also be a certain convex function of the sequence AC sidelobes. The two metrics PSL and WSSL had been adopted as design criteria in [21], [22], [25]- [27]. To demonstrate an example of practical application, we will present the connection between the AC metrics and the channel estimation error when the proposed sequence is applied as the training sequence for channel estimation.…”

mentioning

confidence: 99%

Synthesizing Low Autocorrelation and Low PAPR OFDM Sequences Under Spectral Constraints Through Convex Optimization and GS Algorithm

Tsai

Chung

Shiu

2011

IEEE Trans. Signal Process.

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Abstract-Sequences with low autocorrelation (AC) and low peak to average power ratio (PAPR) are desired in many communication or signal processing applications. This work investigates the synthesis of OFDM sequences with the desired low AC and low PAPR under spectral constraints. The spectral constraints limit the maximum allowable power on each subcarrier to avoid interference on particular reserved bands and undesirable DC-offset. The first part of this work discusses the design of sequences with periodic AC property under spectral constraints. Specifically, we present a convex optimization method for synthesizing OFDM sequences with minimized peak sidelobe level (PSL) or weighted sum of sidelobe levels (WSSL) of the periodic AC function within specified time lags. The design objective to be minimized can also be a certain convex function of the sequence AC sidelobes. Furthermore, we present methods based on Gerchberg-Saxton (GS) algorithm to decrease the PAPR of the sequences, while maintaining the optimized AC characteristic. The second part of this work investigates the aperiodic AC under spectral constraints. In this case, the optimal sequence design problem is nonconvex. By relaxing the nonconvex problem to a convex problem, we provide lower bounds for PSL and WSSL of the aperiodic AC function. Based on the optimal solution for the relaxed convex problem, we present an efficient algorithm to find sequences with low PAPR and near-optimal aperiodic AC property while the spectral constraints are satisfied.

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Coherent Mimo Radar and Waveform Diversity

Gianelli

Stoica

2015

Wiley Encyclopedia of Electrical and Electronics Engineering

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Multiple‐input multiple‐output (MIMO) radar technology has gained considerable attention, from both theorists and practitioners, in the past decade due to its capability to expand radar system functionality and open previously unexplored design space. This work seeks to provide a basic understanding of coherent MIMO radar technology, the performance enhancements that can be attained by using the technology, and the associated drawbacks involved in operating a coherent MIMO radar. Attention is paid to achieve the required waveform orthogonality for a MIMO radar system, and several operating concepts are presented and described. Radar basics are discussed first, followed by a description of the MIMO radar concept. Examples of radar applications that may benefit from the application of MIMO radar are presented. Methods for achieving waveform orthogonality in practical MIMO radar systems are described, and the performance tradeoffs involved in implementing these operation modes are discussed. Information on general radar waveforms, and their suitability for use in a MIMO radar system, is provided. Two examples of MIMO radar systems are discussed, with special emphasis placed on the benefit obtained by applying MIMO radar technology.

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New Algorithms for Designing Unimodular Sequences With Good Correlation Properties

Cited by 401 publications

References 23 publications

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

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

Synthesizing Low Autocorrelation and Low PAPR OFDM Sequences Under Spectral Constraints Through Convex Optimization and GS Algorithm

Coherent Mimo Radar and Waveform Diversity

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