MIMO Radar Waveform Design in Colored Noise Based on Information Theory

Tang, Bo; Tang, Jun; Peng, Yingning

doi:10.1109/tsp.2010.2050885

Cited by 175 publications

(174 citation statements)

References 29 publications

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“…When considering the orthogonality of the transmitted waveforms and the influence of ionosphere to echoes, it is important to design optimized waveforms that are suitable for the multi-layer ionospheric propagation circumstance, which should also be able to reduce the impact of clutter, interference and noise. Based on the groundwork from [15,16,19,20], which applied mutual information theory to design of MIMO radar waveform in order to improve target detection performance, we propose a novel two-step waveform optimization algorithm (named Max-Min algorithm) for MIMO-OTHR.…”

Section: Two-step Waveform Optimization Algorithmmentioning

confidence: 99%

“…In this paper, based on the two-layer ionospheric model proposed in [13] and mutual information theory studied in [14] and mutual information theory studied in [15,16], we propose a two-step waveform optimization algorithm: Max-Min optimization algorithm. The first step is to maximize the mutual information between the echo and target response from the same direction of arrival (DOA) in order to reduce the impact of noise.…”

Section: Introductionmentioning

confidence: 99%

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Mimo-Othr Waveform Optimization Based on the Mutual Information Theory

Luo¹,

Zhao

Luo³

2016

PIER M

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Abstract-In traditional over-the-horizon radar (OTHR), multipath propagation due to the multilayer ionospheric structure always deteriorates the detection performance. The properties of multipleinput multiple-output (MIMO) radar technique, which transmits wide beams with low gain at the transmitter and achieves receiver beam-forming to obtain narrow beams with high gain, make it an ideal choice for OTHR to detect target through multi-layer ionosphere and suppress strong clutter. This paper investigates the assumption of a two-layer ionospheric model and proposes a two-step MaxMin algorithm based on the mutual information theory to optimize MIMO-OTHR waveform so as to suppress clutter, interference and noise. The first step is to maximize the mutual information between the echo and target response from the same direction of arrival (DOA) in order to reduce the impact of noise. The second step is to minimize the mutual information between the echoes from different DOAs, in order to suppress the clutter and interference by reducing the correlation of the echoes from the different DOAs. Numerical experiments validate that this algorithm can improve range resolution and detection probability significantly. Experiment results also demonstrate that the previously harmful multipath propagation can be utilized to enhance the detection performance in MIMO-OTHR.

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Section: Two-step Waveform Optimization Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mimo-Othr Waveform Optimization Based on the Mutual Information Theory

Luo¹,

Zhao

Luo³

2016

PIER M

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“…In [16,17], mutual information is utilized to design radar waveform. The researches in [18,19] apply relative entropy to select the waveform in the point target model.…”

Section: Introductionmentioning

confidence: 99%

Random Radiation Source Optimization Method for Microwave Staring Correlated Imaging Based on Temporal-Spatial Relative Distribution Entropy

Meng¹,

Qian²,

Yuan³

et al. 2018

PIER M

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Abstract-Microwave Staring Correlated Imaging (MSCI) is a high-resolution radar imaging modality, whose resolution is mainly determined by the randomness of radiation source. To optimize the design of random radiation source, a novel concept of temporal-spatial relative distribution entropy (TSRDE) is proposed to describe the temporal-spatial stochastic characteristics of radiation source. The TSRDE can be utilized as the optimization criterion to design the array configuration and signal parameters by means of optimization algorithms. In this paper the genetic algorithm is applied to search for the best design. Numerical simulations are performed and the results show that the TSRDE is an effective method to characterize the randomness of radiation source, and the source parameters optimized by this method can dramatically improve the imaging resolution.

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“…The cited paper uses a weighted sum of the KLdivergences associated with probability density functions for observations in the detection problem. The authors of [6] consider both mutual information and KL-divergence as design metrics for a problem related to that of [3]. Note that in a majority of MIMO radar code design studies in the literature, no constraints (on codes) other than energy constraint are considered.…”

Section: Introductionmentioning

confidence: 99%

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)

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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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MIMO Radar Waveform Design in Colored Noise Based on Information Theory

Cited by 175 publications

References 29 publications

Mimo-Othr Waveform Optimization Based on the Mutual Information Theory

Mimo-Othr Waveform Optimization Based on the Mutual Information Theory

Random Radiation Source Optimization Method for Microwave Staring Correlated Imaging Based on Temporal-Spatial Relative Distribution Entropy

Unimodular code design for MIMO radar using Bhattacharyya distance

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